Stories with Tag compiler

• Rust to C compiler – 95.9% test pass rate, odd platforms

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  Posted: 2025-04-12 04:21:15

  Verbose tl;dr

  The cg_clif project has made significant progress in compiling Rust to C, achieving a 95.9% pass rate on the Rust test suite. This compiler leverages Cranelift as a backend and utilizes a custom ABI for passing Rust data structures. Notably, it's now functional on more unusual platforms like wasm32-wasi and thumbv6m-none-eabi (for embedded ARM devices). While performance isn't a primary focus currently, basic functionality and compatibility are progressing rapidly, demonstrating the potential for compiling Rust to a portable C representation.

  This blog post by Fractal Fir details the ongoing development of cg_clif (now clif-util), a tool designed to compile Rust code into C code. The author focuses on recent progress and challenges encountered while targeting "odd platforms"—specifically, WebAssembly (Wasm) and embedded systems like the AVR microcontroller family.

  A significant milestone is reaching a 95.9% pass rate on the Rust compiler's extensive test suite when compiling to C and subsequently to Wasm. This achievement highlights the project's increasing maturity and ability to handle complex Rust constructs even when targeting non-traditional environments. The author attributes this success partly to the use of Cranelift, a code generation library that facilitates targeting diverse architectures.

  However, the journey isn't without hurdles. The post explains that supporting inline assembly, a feature frequently used for low-level optimization and hardware interaction, presents significant difficulties. The disparity between the assembly syntax understood by the Rust compiler's LLVM backend and the syntax expected by the Wasm target requires intricate translation, a problem not yet fully solved. The author acknowledges this as a major area of ongoing work.

  Furthermore, the post discusses the challenges in targeting the AVR microcontroller architecture. AVR, a popular choice for resource-constrained embedded systems, poses unique constraints due to its limited instruction set and memory capacity. The author describes working on implementing calling conventions compatible with AVR and tackling the intricacies of handling data types and memory management specific to this platform. While significant progress has been made, targeting AVR remains a work in progress, with complete support still on the horizon.

  The overarching goal of cg_clif is to expand the reach of Rust code by enabling compilation to C, thereby unlocking the ability to target platforms not directly supported by the standard Rust compiler. The project leverages the Cranelift code generation library and the clif intermediate representation to achieve this cross-compilation. While challenges remain, particularly regarding inline assembly and support for resource-constrained environments like AVR, the project demonstrates promising progress towards enabling broader platform compatibility for Rust code. The author expresses optimism about future developments and invites contributions from the community.

  • Rust
  • C
  • compiler
  • Cross-Compilation
  • Code Generation
  • mrustc
  • Fractal Fir
  • testing
  • performance
  • WebAssembly
  • Game Boy Advance
  • Uncommon Architectures
  • Portable Code

  Summary of Comments ( 164 )
  https://news.ycombinator.com/item?id=43661329

  Verbose tl;dr

  Hacker News users discussed the impressive 95.9% test pass rate of the Rust-to-C compiler, particularly its ability to target unusual platforms like the Sega Saturn and Sony PlayStation. Some expressed skepticism about the practical applications, questioning the performance implications and debugging challenges of such a complex transpilation process. Others highlighted the potential benefits for code reuse and portability, enabling Rust code to run on legacy or resource-constrained systems. The project's novelty and ambition were generally praised, with several commenters expressing interest in the developer's approach and future developments. Some also debated the suitability of "compiler" versus "transpiler" to describe the project. There was also discussion around specific technical aspects, like memory management and the handling of Rust's borrow checker within the C output.

  The Hacker News post titled "Rust to C compiler – 95.9% test pass rate, odd platforms" sparked a discussion with several interesting comments. Many commenters focused on the complexities and nuances of compiling Rust to C, particularly given Rust's unique memory management features.

  One commenter highlighted the challenges inherent in translating Rust's borrow checker and ownership model into C, which lacks these built-in mechanisms. They questioned how the compiler handled these crucial aspects of Rust, expressing skepticism about achieving true compatibility without significant runtime overhead or limitations. This comment resonated with others who also expressed concern about the potential performance implications and the difficulty of replicating Rust's safety guarantees in C.

  Another commenter pointed out the inherent difficulty in targeting "odd platforms," as mentioned in the title. They elaborated on the potential issues with varying C standard library implementations and the complexities of ensuring compatibility across diverse architectures and operating systems. This prompted a discussion about the trade-offs between portability and performance when attempting such a compilation process.

  Several comments also touched on the potential use cases of such a compiler. Some suggested it could be valuable for embedded systems or environments where Rust isn't directly supported. Others questioned the practicality, arguing that if the target platform supports a C compiler, it might also be feasible to support a Rust compiler directly, potentially negating the need for a transpilation step.

  The discussion also explored alternative approaches, such as compiling Rust to LLVM bitcode and then using LLVM to generate C code. This was presented as a potentially more robust approach that could leverage LLVM's optimizations and platform support.

  Finally, some comments expressed interest in the specific platforms targeted by the project and requested more details about the remaining 4.1% of failing tests. They were curious about the nature of these failures and whether they represented fundamental limitations or solvable issues. Overall, the comments reflected a mixture of curiosity, skepticism, and cautious optimism about the potential of a Rust-to-C compiler.

• A surprising enum size optimization in the Rust compiler

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  Posted: 2025-04-07 22:30:45

  Verbose tl;dr

  Rust enums can surprisingly be smaller than expected. While naively, one might assume an enum's size is determined by the largest variant plus a discriminant to track which variant is active, the compiler optimizes this. If an enum's largest variant contains data with internal padding, the discriminant can sometimes be stored within that padding, avoiding an increase in the overall size. This optimization applies even when using #[repr(C)] or #[repr(u8)], so long as the layout allows it. Essentially, the compiler cleverly utilizes existing unused space within variants to store the variant tag, minimizing the enum's memory footprint.

  This blog post by James Fennell explores a fascinating optimization performed by the Rust compiler regarding the size of enums, specifically how it leverages the niche-filling technique to reduce memory footprint. The author begins by establishing the fundamental concept of enum representation in memory. Enums, by their nature, can hold values of different types, meaning the compiler needs to allocate enough space to accommodate the largest possible variant. This often results in padding if the variants have significantly different sizes.

  The post then dives into the concept of "niche filling." A niche, in this context, refers to a bit pattern or value that a specific data type cannot represent. For instance, references in Rust are guaranteed to be non-null. This means the all-zeros bit pattern (representing a null pointer) becomes a niche that can be exploited. The compiler cleverly uses these niches to store smaller enum variants, thus avoiding the need for additional padding and reducing the overall size of the enum.

  Fennell illustrates this optimization with a concrete example involving an enum containing a reference and a boolean. Naively, one might expect this enum to require the size of a reference plus a boolean (e.g., 8 bytes for a 64-bit pointer and 1 byte for a boolean, potentially padded to 16 due to alignment). However, the Rust compiler recognizes that the null pointer value is a niche for references. It then assigns this niche bit pattern to represent the boolean variant, allowing the entire enum to fit within the size of a single reference (e.g., 8 bytes). This effectively eliminates the need for extra space to store the boolean value, leveraging the unused bit pattern of the null pointer.

  The post further explains that this optimization doesn't only apply to references. It extends to other types with niches, such as NonZeroU8 and NonZeroUsize, demonstrating a broader applicability of this memory-saving technique. The author provides clear code examples and diagrams to visually illustrate the memory layout before and after the optimization, highlighting the efficiency gains.

  Finally, the post acknowledges limitations and complexities. The niche-filling optimization is not always guaranteed. Factors like generic types and platform-specific representations can influence whether the compiler can successfully implement it. Even so, the article clearly demonstrates a powerful optimization employed by the Rust compiler to minimize the memory footprint of enums, showcasing a nuanced understanding of data representation and clever utilization of unused bit patterns.

  • Rust
  • compiler
  • optimization
  • enum
  • size
  • Memory
  • data structures
  • performance
  • Low-level
  • Programming Languages
  • Systems Programming

  Summary of Comments ( 1 )
  https://news.ycombinator.com/item?id=43616649

  Verbose tl;dr

  Hacker News users discussed the surprising optimization where Rust can reduce the size of an enum if its variants all have the same representation. Some commenters expressed admiration for this detail of the Rust compiler and its potential performance benefits. A few questioned the long-term stability of relying on this optimization, wondering if changes to the enum's variants could inadvertently increase its size in the future. Others delved into the specifics of how this optimization interacts with features like repr(C) and niche filling optimizations. One user linked to a relevant section of the Rust Reference, further illuminating the compiler's behavior. The discussion also touched upon the potential downsides, such as making the generated assembly more complex, and how using #[repr(u8)] might offer a more predictable and explicit way to control enum size.

  The Hacker News post titled "A surprising enum size optimization in the Rust compiler," linking to an article about enum size optimization in Rust, has generated several comments discussing the nuances of this optimization and its implications.

  Several commenters delve into the specifics of the niche-filling optimization discussed in the article. One commenter explains how this optimization interacts with the repr attribute in Rust, clarifying that while #[repr(u8)] forces the enum to be represented as a u8, the niche-filling optimization still applies when possible, even without explicitly setting a representation. They provide an example of how this works in practice, illustrating that even with #[repr(u8)], the enum can still be optimized to a smaller size if its variants allow.

  Another commenter discusses the trade-offs between size optimization and runtime performance, pointing out that while smaller sizes are generally desirable, they can sometimes lead to increased runtime costs due to extra operations needed for encoding and decoding the optimized representation. This commenter also explains how the Rust compiler's zero-cost abstraction principle influences these decisions.

  The discussion also touches on the complexity of enum representations and the challenges in predicting the final size. One commenter mentions that the compiler's behavior can sometimes be counterintuitive, leading to unexpected sizes. They provide an example where adding a field to a struct within an enum variant can surprisingly decrease the overall size of the enum due to the way niche-filling interacts with alignment requirements.

  Furthermore, a commenter contrasts Rust's approach with that of C/C++, highlighting the differences in enum representation and the potential for optimization in each language. They note that while C/C++ enums typically default to the size of an integer, Rust's approach allows for more compact representations, especially when niche-filling is possible.

  Finally, the topic of Option<NonZeroU8> is brought up, with commenters explaining how the compiler can optimize its size down to a single byte because the None variant can occupy the niche value of zero, while the Some variant stores the non-zero value directly. This example illustrates a common and practical use case of niche-filling optimization in Rust.

  Overall, the comments section provides valuable insights into the intricacies of Rust's enum size optimization and its practical implications. They offer a deeper understanding of the trade-offs involved, the compiler's behavior, and how these optimizations can impact code size and performance.

• Faster interpreters in Go: Catching up with C++

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  Posted: 2025-04-05 17:59:55

  Verbose tl;dr

  PlanetScale's Vitess project, which uses a Go-based MySQL interpreter, historically lagged behind C++ in performance. Through focused optimization efforts targeting function call overhead, memory allocation, and string conversion, they significantly improved Vitess's speed. By leveraging Go's built-in profiling tools and making targeted changes like using custom map implementations and byte buffers, they achieved performance comparable to, and in some cases exceeding, a similar C++ interpreter. These improvements demonstrate that with careful optimization, Go can be a competitive choice for performance-sensitive applications like database interpreters.

  This PlanetScale blog post explores the performance evolution of their Vitess database's VTAdmin tool, specifically focusing on its migration from C++ to Go. Initially, the Go version of VTAdmin was significantly slower than its C++ counterpart, leading to concerns about Go's suitability for performance-sensitive applications like database tooling. The blog post meticulously details the journey of optimizing the Go implementation to eventually match and even surpass the C++ version's performance in certain scenarios.

  The authors begin by outlining the challenges faced during the initial port to Go. They emphasize that a straightforward translation of the C++ code resulted in a substantially slower Go program. They attribute this performance gap to several factors, including Go's garbage collection, its handling of strings (which are immutable in Go, unlike C++), and differences in data structures and memory management.

  The optimization process is broken down into several key stages. First, they profiled the Go code extensively to identify performance bottlenecks. Profiling tools like pprof played a crucial role in pinpointing areas requiring attention. One of the major culprits was excessive string allocations and conversions, stemming from the frequent manipulation of string data within VTAdmin.

  To address the string issues, the authors explored various strategies, including using byte slices ([]byte) instead of strings where possible, pre-allocating buffers to minimize allocations during string manipulation, and carefully managing string conversions between Go and C++ libraries. These targeted optimizations resulted in significant performance improvements.

  Furthermore, the authors investigated the impact of Go's garbage collector. While recognizing that Go's garbage collection offers benefits in terms of developer productivity and memory safety, they also acknowledged its potential to introduce performance overhead. Through careful analysis and tuning, they managed to minimize the impact of garbage collection on VTAdmin's performance.

  Another area of focus was optimizing interactions with underlying C++ libraries. VTAdmin relies on certain C++ components, and the communication between the Go code and these libraries was initially a source of inefficiency. By streamlining these interactions and minimizing data copying across the language boundary, the authors achieved further performance gains.

  Finally, the blog post presents benchmark results comparing the optimized Go version of VTAdmin against the original C++ implementation. These results demonstrate that the Go version has not only caught up with but, in some cases, even outperformed the C++ version, particularly in scenarios involving high concurrency. The authors conclude that Go, when used judiciously and optimized effectively, can be a viable choice for building high-performance applications, even in demanding domains like database administration. They highlight the importance of profiling, understanding Go's runtime characteristics, and strategically managing memory allocations and string operations for achieving optimal performance. They also emphasize that the performance characteristics of Go are continuously evolving, and future improvements to the language and its runtime could further enhance the performance of Go applications like VTAdmin.

  • Go
  • Golang
  • interpreter
  • performance
  • C++
  • benchmarking
  • optimization
  • compiler
  • Interpreted Languages
  • Programming Languages
  • Software Development
  • planetScale

  Summary of Comments ( 42 )
  https://news.ycombinator.com/item?id=43595283

  Verbose tl;dr

  Hacker News users discussed the benchmarks presented in the PlanetScale blog post, expressing skepticism about their real-world applicability. Several commenters pointed out that the microbenchmarks might not reflect typical database workload performance, and questioned the choice of C++ implementation used for comparison. Some suggested that the Go interpreter's performance improvements, while impressive, might not translate to significant gains in a production environment. Others highlighted the importance of considering factors beyond raw execution speed, such as memory usage and garbage collection overhead. The lack of details about the specific benchmarks and the C++ implementation used made it difficult for some to fully assess the validity of the claims. A few commenters praised the progress Go has made, but emphasized the need for more comprehensive and realistic benchmarks to accurately compare interpreter performance.

  The Hacker News post titled "Faster interpreters in Go: Catching up with C++" (linking to a PlanetScale blog post about optimizing their Vitess database's VTGate component) generated a moderate amount of discussion, with a number of commenters focusing on the nuances of benchmarking and optimization in Go and C++.

  Several commenters expressed skepticism about the methodology used in the benchmarks presented in the blog post. One commenter questioned whether the benchmarks accurately reflected real-world usage, pointing out that microbenchmarks often don't translate to performance gains in production systems. Another highlighted the importance of considering the specific workload when evaluating performance, suggesting that different workloads might yield different results. There was a general sentiment that while the demonstrated performance improvements were impressive, more context was needed to fully understand their implications.

  The discussion also touched upon the complexities of garbage collection in Go and its impact on performance. One commenter noted that Go's garbage collector can introduce variability in benchmark results, making it challenging to obtain consistent measurements. Another discussed the trade-offs between performance and ease of development when using Go, acknowledging that while Go might not always match C++ in raw speed, its developer-friendly features can often outweigh the performance difference.

  Some commenters shared their own experiences with optimizing Go code, offering insights into techniques for improving performance. One suggested using profiling tools to identify bottlenecks and focusing optimization efforts on the most critical sections of code. Another mentioned the importance of careful memory management in Go to minimize the overhead of the garbage collector.

  A few commenters also delved into the technical details of the optimizations described in the blog post, discussing the benefits of using techniques like code generation and avoiding unnecessary allocations. They pointed out that while these optimizations can be effective, they can also increase code complexity and make it harder to maintain.

  Finally, some comments shifted the focus from performance to other aspects of software development, such as code readability and maintainability. One commenter argued that while performance is important, it shouldn't come at the cost of code clarity and maintainability. Another suggested that choosing the right tool for the job is crucial and that Go's advantages in terms of developer productivity can often outweigh its potential performance limitations compared to C++.

  In summary, the comments on the Hacker News post offer a range of perspectives on the topic of Go performance optimization, highlighting the importance of careful benchmarking, considering real-world workloads, and balancing performance with other software development considerations. While the blog post itself focuses on specific optimizations in a particular project, the comments broaden the discussion to encompass broader themes related to performance, optimization strategies, and the trade-offs between performance and other software development goals.

• A Vision for WebAssembly Support in Swift

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  Posted: 2025-04-05 13:58:18

  Verbose tl;dr

  This post outlines a vision for first-class WebAssembly support in Swift, enabling developers to compile Swift code directly to Wasm for use in web browsers and other Wasm environments. The proposal emphasizes seamless integration with existing JavaScript ecosystems, allowing bidirectional communication between Swift and JavaScript code. It also aims for near-native performance by leveraging Wasm's capabilities, and proposes tools and workflows to simplify the development process, such as automatic generation of JavaScript bindings for Swift code. The ultimate goal is to empower Swift developers to build high-performance web applications and leverage the growing Wasm ecosystem, while maintaining Swift's core values of safety, performance, and expressiveness.

  This forum post outlines a comprehensive vision for integrating WebAssembly (Wasm) support into the Swift programming language, aiming to enable Swift developers to target the web and other Wasm-compatible environments seamlessly. The author emphasizes that this integration should prioritize ergonomics, performance, and interoperability, ensuring a smooth and efficient developer experience.

  The proposal suggests a two-pronged approach: "Swift-in-Wasm" and "Wasm-in-Swift." Swift-in-Wasm focuses on compiling Swift code directly into WebAssembly, allowing developers to write web applications and other Wasm-targeted software using familiar Swift syntax and libraries. This approach entails significant modifications to the Swift compiler and runtime to support the Wasm target. Key aspects include efficient memory management within the Wasm environment, handling Swift's runtime features like automatic reference counting (ARC), and ensuring compatibility with JavaScript and the Web API through well-defined interoperability mechanisms. Performance is a crucial consideration, and the proposal emphasizes generating optimized Wasm code that leverages the capabilities of modern web browsers and other Wasm runtimes.

  Conversely, Wasm-in-Swift aims to enable the embedding and execution of pre-existing Wasm modules within Swift applications. This functionality would allow developers to leverage existing Wasm libraries and components within their Swift projects, expanding the ecosystem available to them. This aspect involves designing robust APIs within Swift to load, interact with, and manage Wasm modules. It also requires addressing issues such as type mapping between Swift and Wasm types, and ensuring safe and efficient communication between the Swift and Wasm environments.

  The long-term vision described in the post envisions Swift becoming a first-class language for Wasm development, empowering developers to build high-performance web applications, serverless functions, and other Wasm-based software. The proposal also highlights the potential for leveraging Wasm to distribute Swift code to various platforms beyond the web, extending the reach and applicability of the language. The author anticipates that this integration will benefit both the Swift and Wasm communities, fostering collaboration and growth in both ecosystems. Finally, the post acknowledges that realizing this vision requires significant effort and invites community feedback and contributions to shape the future of Wasm support in Swift.

  • Swift
  • WebAssembly
  • Wasm
  • Web Development
  • Programming Languages
  • compiler
  • LLVM
  • Frontend Development
  • Backend Development
  • Full-Stack Development
  • Cross-Platform Development
  • Server-Side Swift
  • Client-Side Swift

  Summary of Comments ( 97 )
  https://news.ycombinator.com/item?id=43593596

  Verbose tl;dr

  Hacker News users discussed the potential and challenges of Swift for WebAssembly. Some expressed excitement about the prospect of using Swift for frontend development, highlighting its performance and type safety as advantages over JavaScript. Others were more cautious, pointing to the existing maturity of JavaScript and its ecosystem, and questioning whether Swift could gain significant traction. Concerns were raised about the size of Swift compiled output and the integration with existing JavaScript libraries and frameworks. The potential for full-stack Swift development and server-side applications with WebAssembly was also mentioned as a motivating factor. Several users suggested that prioritizing the developer experience and tooling would be crucial for adoption.

  The Hacker News post "A Vision for WebAssembly Support in Swift," linking to a Swift forums discussion about bringing WebAssembly support to the Swift programming language, generated a moderate amount of discussion. Several commenters expressed enthusiasm and interest in the possibilities.

  A significant thread focused on the potential benefits and drawbacks compared to existing solutions like JavaScript and TypeScript. One commenter questioned whether Swift offered enough advantages over TypeScript to justify the effort, pointing out that TypeScript already enjoys wide adoption and robust tooling for web development. Counterarguments highlighted Swift's performance potential, strong typing, and modern language features as reasons why it could be a compelling alternative. This back-and-forth explored the trade-offs between a potentially faster, more robust language like Swift and the established ecosystem of JavaScript/TypeScript.

  Several commenters discussed the potential impact of WebAssembly support on Swift's overall adoption. Some speculated that it could broaden Swift's reach significantly, allowing it to break free from its primary association with Apple platforms and become a more general-purpose language. Others expressed skepticism, suggesting that the web development landscape is already crowded and that Swift might struggle to gain traction against established players.

  Another recurring theme was the practical considerations of implementing WebAssembly support in Swift. Commenters discussed the challenges of garbage collection and interoperability with existing JavaScript code. The intricacies of efficiently bridging Swift's runtime environment with the browser's WebAssembly implementation were also touched upon.

  Some commenters brought up specific use cases where Swift in the browser could be particularly advantageous, including computationally intensive tasks and porting existing Swift code to the web. The potential for improved performance in web applications was a recurring point of interest.

  While there was general excitement about the prospect, many comments acknowledged the significant work involved and the need for careful consideration of the technical challenges. The overall sentiment leaned towards cautious optimism, with commenters expressing interest in seeing how the project evolves and whether it can deliver on its potential.

• Show HN: The C3 programming language (C alternative language)

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  Posted: 2025-04-03 13:55:38

  Verbose tl;dr

  C3 is a new programming language designed as a modern alternative to C. It aims to be safer and easier to use while maintaining C's performance and low-level control. Key features include optional memory safety through compile-time checks and garbage collection, improved syntax and error messages, and built-in modularity. The project is actively under development and includes a self-hosting compiler written in C3. The goal is to provide a practical language for systems programming and other performance-sensitive domains while mitigating common C pitfalls.

  A new programming language named C3 has been introduced as a potential alternative to C. The project, hosted on GitHub, aims to provide a language that addresses some of C's perceived shortcomings while retaining its strengths, particularly its performance characteristics and low-level control. The developers emphasize C3's focus on being a practical language for systems programming, game development, and other performance-sensitive applications.

  C3 borrows heavily from C in terms of syntax and semantics, providing a familiar environment for C programmers. However, it introduces several modern features and enhancements designed to improve developer productivity, code safety, and maintainability. These enhancements include optional garbage collection, compile-time function evaluation, improved error handling mechanisms, and native support for generics. The goal is to offer a more robust and expressive language that minimizes common C pitfalls like memory leaks and dangling pointers, without sacrificing the fine-grained control that makes C so powerful.

  The C3 compiler, c3c, is itself written in C3, demonstrating a commitment to bootstrapping and showcasing the language's capabilities. The project is actively being developed and is currently considered experimental. While not yet production-ready, it offers a glimpse into a potential future for C-like languages, incorporating modern language features while retaining the core principles that have made C a cornerstone of systems programming for decades. The language aims to strike a balance between performance and productivity, appealing to developers who value both speed and a more modern development experience. The GitHub repository provides source code, documentation, and examples to explore the language's features and contribute to its development.

  • C
  • C3
  • programming language
  • compiler
  • Systems Programming
  • Low-Level Programming
  • alternative language
  • Open Source
  • GitHub
  • HN
  • Show HN

  Summary of Comments ( 98 )
  https://news.ycombinator.com/item?id=43569724

  Verbose tl;dr

  HN users discuss C3's goals and features, expressing both interest and skepticism. Several question the need for another C-like language, especially given the continued development of C and C++. Some appreciate the focus on safety and preventing common C errors, while others find the changes too drastic a departure from C's philosophy. There's debate about the practicality of automatic memory management in systems programming, and some concern over the runtime overhead it might introduce. The project's early stage is noted, and some express reservations about its long-term viability and community adoption. Others are more optimistic, praising the clear documentation and expressing interest in following its progress. The use of Python for the compiler is also a point of discussion.

  The Hacker News post about the C3 programming language generated a moderate amount of discussion, with several commenters expressing interest and raising relevant points. Several threads of conversation emerged around the language's features and goals.

  One prominent thread discussed C3's approach to memory management. Some users questioned the decision to retain manual memory management, a common source of bugs in C, while others defended it as crucial for performance and control. The discussion explored various aspects of manual memory management, including its complexity, its benefits in certain contexts, and the potential for memory leaks. Some commenters suggested alternative approaches, such as incorporating features like borrow checking from Rust or offering optional garbage collection.

  Another significant thread focused on C3's compatibility with existing C code. Some users emphasized the importance of seamless interoperability, allowing developers to gradually integrate C3 into existing projects, while others highlighted the challenges of achieving full compatibility while also introducing new language features. There was some discussion about the level of compatibility C3 aimed for and the practical implications for migration and code reuse.

  The language's syntax and overall design also drew comments. Some users appreciated the efforts to modernize C while preserving its familiar feel, while others expressed skepticism about the necessity of a new language or suggested improvements to specific language constructs. There was discussion comparing C3's syntax to other languages like Go and Rust, and some commenters offered specific suggestions for improving readability or reducing boilerplate.

  Several commenters also touched on the development status and community around C3. Some inquired about the language's maturity, tooling, and documentation, while others expressed interest in contributing to the project. The topic of community building and the importance of attracting developers and users was briefly discussed.

  In addition to these broader themes, there were individual comments raising more specific points, such as questions about the language's performance characteristics, its target use cases, and the rationale behind certain design choices. Some commenters provided links to related projects or resources, and others shared their personal experiences with similar languages or tools.

• Compiler Options Hardening Guide for C and C++

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  Posted: 2025-03-31 11:01:50

  Verbose tl;dr

  This guide provides a curated list of compiler flags for GCC, Clang, and MSVC, designed to harden C and C++ code against security vulnerabilities. It focuses on options that enable various exploit mitigations, such as stack protectors, control-flow integrity (CFI), address space layout randomization (ASLR), and shadow stacks. The guide categorizes flags by their protective mechanisms, emphasizing practical usage with clear explanations and examples. It also highlights potential compatibility issues and performance impacts, aiming to help developers choose appropriate hardening options for their projects. By leveraging these compiler-based defenses, developers can significantly reduce the risk of successful exploits targeting their software.

  The OpenSSF's "Compiler Options Hardening Guide for C and C++" provides a comprehensive set of recommendations for enhancing the security of software built using these languages. The guide focuses on utilizing compiler features and options to mitigate various vulnerabilities that can arise during the compilation process or during the execution of the compiled code. It recognizes that while secure coding practices are paramount, leveraging compiler capabilities offers an additional layer of defense against exploits.

  The guide is structured around different categories of vulnerabilities and the corresponding compiler flags that can help prevent them. It covers a wide spectrum of potential issues, including buffer overflows, format string vulnerabilities, integer overflows, and injection attacks. For each vulnerability class, the guide explains the underlying problem, its potential impact, and how specific compiler options can mitigate the risk.

  A key emphasis of the guide is portability across different compilers. While it acknowledges that certain flags are compiler-specific, the recommendations strive for generality whenever possible. It offers equivalent flags for widely used compilers like GCC, Clang, and MSVC, enabling developers to apply the hardening techniques across diverse development environments. The guide also discusses the potential trade-offs associated with certain flags, such as performance impact or compatibility issues.

  The guide delves into several specific hardening techniques, including:

  • Stack protection: This involves employing compiler features like stack canaries and shadow stacks to detect and prevent stack-based buffer overflows, a common attack vector.
  • Control-flow integrity (CFI): CFI mechanisms restrict the possible control flow paths within a program, making it significantly harder for attackers to hijack the program's execution.
  • Address Space Layout Randomization (ASLR): This technique randomizes the base addresses of key memory regions like the stack, heap, and libraries, making it more difficult for attackers to predict memory locations and execute exploits.
  • Position Independent Executables (PIE): PIE enables ASLR for the program's code segment itself, further enhancing the randomization and making exploitation harder.
  • Read-only relocations (RELRO): RELRO protects key data sections, such as the Global Offset Table (GOT), from being modified, preventing attacks that rely on overwriting these critical structures.
  • Integer overflow protection: This includes flags that detect and handle integer overflows, mitigating potential vulnerabilities that can arise from unexpected arithmetic results.
  • Fortify Source: This set of enhancements strengthens various standard library functions, making them more resistant to common vulnerabilities.

  The guide is presented in a detailed yet accessible manner, providing clear explanations of each vulnerability class and the corresponding mitigation techniques. It includes concrete examples of compiler invocations, demonstrating how to apply the recommended flags in practice. The guide aims to empower developers with the knowledge and tools necessary to build more secure and robust software by leveraging the full potential of compiler-based hardening techniques. It emphasizes that while these techniques are not a silver bullet, they represent a significant step towards improving overall software security.

  • C
  • C++
  • compiler
  • Hardening
  • Security
  • Compiler Options
  • best practices
  • OpenSSF
  • Software Security
  • Vulnerability Mitigation
  • Code Hardening
  • Exploit Mitigation

  Summary of Comments ( 27 )
  https://news.ycombinator.com/item?id=43533516

  Verbose tl;dr

  Hacker News users generally praised the OpenSSF's compiler hardening guide for C and C++. Several commenters highlighted the importance of such guides in improving overall software security, particularly given the prevalence of C and C++ in critical systems. Some discussed the practicality of implementing all the recommendations, noting potential performance trade-offs and the need for careful consideration depending on the specific project. A few users also mentioned the guide's usefulness for learning more about compiler options and their security implications, even for experienced developers. Some wished for similar guides for other languages, and others offered additional suggestions for hardening, like using static and dynamic analysis tools. One commenter pointed out the difference between control-flow hijacking mitigations and memory safety, emphasizing the limitations of the former.

  The Hacker News post titled "Compiler Options Hardening Guide for C and C++" linking to the OpenSSF's guide on the same topic generated a moderate discussion with several insightful comments.

  Several commenters praised the guide for its comprehensiveness and clarity. One user specifically appreciated the guide's organization, highlighting how it clearly categorized compiler options by the issues they addressed, such as buffer overflows, format string vulnerabilities, and integer overflows. They felt this made it easier to understand the purpose of each option and select the appropriate ones for their project.

  Another commenter focused on the practical implications of the guide, noting that while enabling all the recommended options might be ideal, it's often not feasible due to compatibility issues with existing codebases or libraries. They suggested a pragmatic approach of prioritizing the most critical options and gradually incorporating others as possible. This commenter also highlighted the tension between security and performance, acknowledging that some hardening options can impact performance and that developers need to find a suitable balance.

  There was a discussion around the use of sanitizers like AddressSanitizer (ASan) and UndefinedBehaviorSanitizer (UBSan). One user emphasized the value of using these tools during development to catch issues early, even though they come with a performance overhead, making them less suitable for production environments.

  Another thread of conversation centered on the importance of static analysis tools. A commenter pointed out that compiler options alone are not sufficient for ensuring code security and that static analysis tools can play a crucial role in identifying potential vulnerabilities that compiler options might miss. They specifically mentioned the benefit of using tools that can analyze code for compliance with secure coding standards.

  A few comments delved into specific compiler options. For example, one commenter discussed the -fstack-protector-strong option, explaining its purpose and how it helps mitigate stack-based buffer overflows. Another commenter mentioned the importance of understanding the implications of each option, cautioning against blindly enabling options without understanding their potential side effects.

  Finally, there was a brief discussion about the role of language choice in security. While the guide focuses on C and C++, one commenter mentioned that using memory-safe languages like Rust or Go can significantly reduce the risk of memory-related vulnerabilities.

  Overall, the comments on the Hacker News post provided a valuable supplement to the OpenSSF guide, offering practical insights, highlighting trade-offs, and emphasizing the importance of a multi-layered approach to security that combines compiler hardening, static analysis, and careful consideration of language choice.

• Tail Call Recursion in Java with ASM (2023)

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  Posted: 2025-03-30 12:47:07

  Verbose tl;dr

  This blog post demonstrates how to achieve tail call optimization (TCO) in Java, despite the JVM's lack of native support. The author uses the ASM bytecode manipulation library to transform compiled Java bytecode, replacing recursive tail calls with goto instructions that jump back to the beginning of the method. This avoids stack frame growth and prevents StackOverflowErrors, effectively emulating TCO. The post provides a detailed example, transforming a simple factorial function, and discusses the limitations and potential pitfalls of this approach, including the handling of local variables and debugging challenges. Ultimately, it offers a working, albeit complex, solution for achieving TCO in Java for specific use cases.

  This blog post, titled "Tail Call Recursion in Java with ASM (2023)," explores the implementation of tail call optimization in Java, a feature not natively supported by the Java Virtual Machine (JVM). The author acknowledges that while true tail call optimization might be detrimental in Java due to its reliance on stack traces for debugging, they focus on achieving tail call elimination for specific, annotated functions to improve performance and prevent stack overflow errors in recursive algorithms.

  The core of the solution revolves around using the ASM bytecode manipulation framework. The author details a process where they create a custom annotation, @TailRecursive, to mark methods intended for tail call optimization. A Java agent then intercepts class loading and modifies the bytecode of these annotated methods. Instead of generating the standard recursive call instructions, the agent rewrites the bytecode to effectively transform the recursive call into a loop. This involves manipulating the local variables to mirror the arguments of the recursive call and then jumping back to the beginning of the method, thus mimicking the behavior of a tail call optimized function. This transformation avoids pushing additional frames onto the stack for each recursive call, preventing stack overflow exceptions for deeply recursive calls.

  The article provides a detailed explanation of the ASM code used to achieve this transformation, walking through the logic of visiting method instructions, identifying tail recursive calls based on specific criteria (like invoking the same method and being the last instruction), and finally, replacing those calls with the appropriate bytecode for variable manipulation and a jump instruction back to the method's start. The author clarifies that the method must be static and the recursive call has to be the very last operation for this specific implementation to work correctly.

  The author illustrates the concept with a concrete example of calculating the factorial function recursively. They demonstrate how the standard recursive approach can lead to a StackOverflowError for large inputs, while the ASM-transformed version successfully computes the result without exceeding stack limitations. This example serves to underscore the practical benefits of the implemented tail call elimination, showcasing its ability to enable deep recursion without the associated stack overflow risks. The article concludes by pointing to a GitHub repository containing the complete code for the Java agent and example usage, encouraging readers to explore and experiment with the presented technique.

  • Java
  • Recursion
  • Tail Call Optimization
  • ASM
  • Bytecode Manipulation
  • performance
  • JVM
  • compiler

  Summary of Comments ( 21 )
  https://news.ycombinator.com/item?id=43523741

  Verbose tl;dr

  Hacker News users generally expressed skepticism about the practicality and value of the approach described in the article. Several commenters pointed out that while technically interesting, using ASM to achieve tail-call optimization in Java is likely to be more trouble than it's worth due to the complexity and potential for subtle bugs. The performance benefits were questioned, with some suggesting that iterative solutions would be simpler and potentially faster. Others noted that relying on such a technique would make code less portable and harder to maintain. A few commenters appreciated the cleverness of the solution, but overall the sentiment leaned towards considering it more of a curiosity than a genuinely useful technique.

  The Hacker News post "Tail Call Recursion in Java with ASM (2023)" has generated several comments discussing the article's approach to implementing tail call optimization in Java using the ASM bytecode manipulation library.

  Several commenters express skepticism about the practical benefits and maintainability of this approach. One commenter points out that while intellectually interesting, using bytecode manipulation for this purpose introduces significant complexity and potential debugging challenges. They argue that the performance gains might not be worth the added difficulty in understanding and maintaining the code. This sentiment is echoed by others who question the real-world applicability of this technique, particularly in larger projects where readability and maintainability are paramount.

  Another commenter suggests that relying on the JVM to perform tail call optimization, even if it's not guaranteed, is a more sensible approach. They argue that future JVM versions might implement tail call optimization more broadly, making this bytecode manipulation technique unnecessary. Furthermore, they highlight the risk of relying on undocumented JVM behavior.

  Some commenters delve into more technical aspects of the implementation. One discusses the challenges of handling exceptions and the potential complexities that arise when trying to maintain proper stack traces with this approach. Another commenter explores the potential performance implications in more detail, considering different scenarios and workloads.

  The discussion also touches upon alternative approaches to achieving similar results, such as using trampolines or iterative methods. One commenter points out the trade-offs between different techniques and emphasizes the importance of choosing the right approach based on the specific needs of the project.

  Several users express appreciation for the author's work in exploring and demonstrating this technique, even if they are not convinced of its practical utility. They acknowledge the educational value of the article in showcasing the capabilities of ASM and providing insights into the inner workings of the JVM.

  Finally, some comments delve into the limitations of the JVM's current approach to tail call optimization and the reasons why it hasn't been fully implemented yet. One commenter mentions the complexities related to security and reflection, which make implementing proper tail call optimization in the JVM a challenging endeavor.

• MilliForth-6502: The smallest Forth real programming language for 6502

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  Posted: 2025-03-28 11:04:40

  Verbose tl;dr

  MilliForth-6502 is a minimalist Forth implementation for the 6502 processor, designed to be incredibly small while remaining a practical programming language. It features a 1 KB dictionary, a 256-byte parameter stack, and implements core Forth words including arithmetic, logic, stack manipulation, and I/O. Despite its size, MilliForth allows for defining new words and includes a simple interactive interpreter. Its compactness makes it suitable for resource-constrained 6502 systems, and the project provides source code and documentation for building and using it.

  MilliForth-6502 is presented as an incredibly compact implementation of the Forth programming language, specifically designed for the 6502 microprocessor, a popular 8-bit processor used in systems like the Apple II, Commodore 64, and Atari 8-bit computers. The project's primary goal is to create a functional Forth system within an extremely limited memory footprint, aiming for a size under 1 kilobyte. This makes it suitable for resource-constrained environments or as a foundational layer for building more complex software on 6502-based platforms.

  The core features of a traditional Forth system are retained, including a dictionary (a symbol table that maps words to their corresponding code), an interpreter for executing Forth words, and a compiler for defining new words. MilliForth-6502 utilizes a threaded interpretation model, where each word's definition consists of a sequence of pointers to other words, creating an efficient execution flow.

  The system provides a minimal set of primitive words, allowing for basic arithmetic, logical operations, stack manipulation, memory access, and input/output functions. These primitives serve as the building blocks for creating more complex words and programs through Forth's unique approach to programming, which relies heavily on combining smaller, defined words into larger, more specialized words.

  A key aspect of MilliForth-6502's design is its simplicity. The code is meticulously crafted to minimize its size while maintaining functionality. This minimalistic approach is not just about conserving memory but also about providing a clear and understandable implementation of Forth, making it a valuable resource for learning or exploring the inner workings of both Forth and the 6502 architecture. The source code is provided for users to examine, modify, and adapt to their specific needs.

  While complete, MilliForth-6502 acknowledges its own limited nature. It is a foundational system designed for expansion. Users are expected to build upon the core functionalities and extend the vocabulary with custom words tailored to their particular applications. It provides a compact and robust basis for further Forth development on the 6502 platform.

  • Forth
  • 6502
  • programming language
  • Retrocomputing
  • Low-Level Programming
  • Embedded Systems
  • MilliForth
  • Assembly Language
  • virtual machine
  • interpreter
  • compiler
  • Open Source
  • GitHub

  Summary of Comments ( 2 )
  https://news.ycombinator.com/item?id=43503897

  Verbose tl;dr

  Hacker News users discussed the practicality and minimalism of MilliForth, a Forth implementation for the 6502 processor. Some questioned its usefulness beyond educational purposes, citing limited memory and awkward programming style compared to assembly language. Others appreciated its cleverness and the challenge of creating such a compact system, viewing it as a testament to Forth's flexibility. Several comments highlighted the historical context of Forth on resource-constrained systems and drew parallels to other small language implementations. The maintainability of generated code and the debugging experience were also mentioned as potential drawbacks. A few commenters expressed interest in exploring MilliForth further and potentially using it for small embedded projects.

  The Hacker News post for MilliForth-6502 has a modest number of comments, focusing primarily on its size, speed, and potential applications.

  Several commenters express fascination with the extreme minimalism of MilliForth, marveling at how a functional Forth system can be implemented in such a small footprint. They discuss the challenges and ingenuity involved in fitting a complete language within such tight constraints. Some commenters delve into the technical details of its implementation, analyzing how certain features are achieved with limited resources.

  A recurring theme is comparing MilliForth to other small language implementations, particularly FORTHs and BASICs on similar hardware. Commenters share anecdotes and experiences with historical systems, highlighting the tradeoffs between size, speed, and functionality. Some discuss how MilliForth's size compares favorably to other FORTHs on the 6502, while acknowledging that its minimalist nature may impact usability for larger projects.

  The speed of MilliForth is also a point of discussion. Some commenters question its performance relative to other FORTHs and even assembly language, wondering if the extreme size optimization comes at the cost of execution speed. Others express interest in benchmarking MilliForth against similar systems to quantify its performance characteristics.

  Regarding applications, some commenters speculate on potential uses for such a small FORTH, suggesting embedded systems, retrocomputing projects, and educational purposes as possible areas where MilliForth could be valuable. The idea of fitting a complete language within the limited memory of older hardware is particularly appealing to retrocomputing enthusiasts. One commenter mentions using a similar small FORTH on an Apple II, demonstrating the practicality of such systems.

  Finally, a few comments focus on the readability and maintainability of the code. Due to its highly optimized nature, some commenters acknowledge that MilliForth might be challenging to understand and modify. However, the overall sentiment leans towards appreciation for the technical achievement, even if the code itself is not intended for extensive modification.

• Xee: A Modern XPath and XSLT Engine in Rust

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  Posted: 2025-03-28 06:48:18

  Verbose tl;dr

  Xee is a new XPath and XSLT engine written in Rust, focusing on performance, security, and WebAssembly compatibility. It aims to be a modern alternative to existing engines, offering a safe and efficient way to process XML and HTML in various environments, including browsers and servers. Leveraging Rust's ownership model and memory safety features, Xee minimizes vulnerabilities like use-after-free errors and buffer overflows. Its WebAssembly support enables client-side XML processing without relying on JavaScript, potentially improving performance and security for web applications. While still under active development, Xee already supports a substantial portion of the XPath 3.1 and XSLT 3.0 specifications, with plans to implement streaming transformations and other advanced features in the future.

  The blog post "Xee: A Modern XPath and XSLT Engine in Rust" by Startifact announces and details their newly developed XPath 3.1 and XSLT 3.0 engine written in Rust. The post emphasizes the performance benefits gained from using Rust, highlighting its memory safety and speed. Xee is designed to be embeddable in other applications, providing a robust and efficient way to process XML documents.

  The authors explain their motivations for creating Xee, citing the limitations and complexities of existing XPath and XSLT engines, particularly in regard to integration with modern software development practices. They sought a solution that was fast, reliable, and easily integrated into their own projects and those of other developers. Rust, with its focus on performance and safety, emerged as the ideal language for this undertaking.

  The post delves into some of the technical challenges faced during the development process, such as efficiently managing string handling, optimizing numerical computations relevant to XPath, and the complexities of implementing the complete XPath and XSLT specifications. It also highlights the advantages of using Rust's ownership and borrowing system for memory management, leading to fewer memory leaks and a more predictable runtime behavior compared to engines written in languages with garbage collection.

  Furthermore, the post showcases Xee’s performance benchmarks, demonstrating significant speed improvements compared to established XPath and XSLT engines like libxslt and Saxon-HE. These benchmarks involved various common XPath and XSLT operations, illustrating Xee’s efficiency in handling diverse processing tasks.

  The post also touches upon the API design of Xee, emphasizing its ease of use and integration within Rust projects. They provide code examples demonstrating how to evaluate XPath expressions and apply XSLT stylesheets using Xee. This ease of integration is a key selling point, allowing developers to seamlessly incorporate XML processing capabilities into their applications.

  Finally, the post concludes with a look towards the future of Xee, outlining plans for further development and improvements. This includes potential features such as schema validation, streaming transformations for large XML documents, and further performance optimizations. The authors express their enthusiasm for community involvement and contributions to the project, inviting developers to explore and utilize Xee in their own work. They position Xee not just as a Startifact project, but as a potential key component in the broader ecosystem of XML processing tools.

  • XPath
  • XSLT
  • Rust
  • XML
  • JSON
  • Query Language
  • data processing
  • Transformation Language
  • Web Development
  • programming language
  • parser
  • compiler
  • performance
  • Efficiency
  • Open Source

  Summary of Comments ( 16 )
  https://news.ycombinator.com/item?id=43502291

  Verbose tl;dr

  HN commenters generally praise Xee's speed and the author's approach to error handling. Several highlight the impressive performance benchmarks compared to libxml2, with some noting the potential for Xee to become a valuable tool in performance-sensitive XML processing scenarios. Others appreciate the clean API design and Rust's memory safety advantages. A few discuss the niche nature of XPath/XSLT in modern development, while some express interest in using Xee for specific tasks like web scraping and configuration parsing. The Rust implementation also sparked discussions about language choices for performance-critical applications. Several users inquire about WASM support, indicating potential interest in browser-based applications.

  The Hacker News post discussing Xee, a modern XPath and XSLT engine written in Rust, has generated several comments exploring various aspects of the project.

  Several commenters express enthusiasm for the project, particularly praising its performance. One user highlights the speed improvements observed in their own testing, emphasizing the significance of a faster XSLT engine for their workflow. Another commenter points out the potential benefits of Rust's memory safety features for preventing crashes and improving the overall reliability of the engine. The choice of Rust itself is lauded, with several comments mentioning its growing popularity and suitability for tasks demanding performance and safety.

  Some discussion revolves around the complexities of XPath and XSLT, acknowledging their power while also noting the steep learning curve. One commenter mentions their infrequent use of these technologies, expressing interest in revisiting them with a tool like Xee. Another points to the niche nature of XSLT, suggesting its relevance primarily within specific industries or for particular tasks like XML transformations.

  A few comments delve into technical details. One user asks about the engine's handling of extensions, a crucial feature for extending the functionality of XPath and XSLT. Another inquires about the implementation of the document() function and its behavior. The creator of Xee actively participates in the thread, responding to these technical queries and providing insights into the project's design choices and future plans. They discuss the challenges of supporting extensions and outline potential approaches for implementing them.

  The conversation also touches on alternative XPath and XSLT engines, with mentions of Libxml2 and Saxon. Comparisons are drawn in terms of performance and features, highlighting Xee's potential advantages in certain areas.

  Overall, the comments reflect a positive reception towards Xee. Commenters express interest in its performance gains and the potential of Rust for creating robust and efficient XML processing tools. The discussion also acknowledges the complexities of XPath and XSLT, and explores technical nuances of the engine's implementation and its place within the existing ecosystem of XML processing tools.

• The Jakt Programming Language

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  Posted: 2025-03-21 16:34:26

  Verbose tl;dr

  Jakt is a statically-typed, compiled programming language designed for performance and ease of use, with a focus on systems programming, game development, and GUI applications. Inspired by C++, Rust, and other modern languages, it features manual memory management, optional garbage collection, compile-time evaluation, and a friendly syntax. Developed alongside the SerenityOS operating system, Jakt aims to offer a robust and modern alternative for building performant and maintainable software while prioritizing developer productivity.

  The GitHub repository introduces Jakt, a novel, general-purpose programming language currently under active development, primarily intended for integration within the SerenityOS operating system. Jakt aims to fill a perceived gap in the programming language landscape, offering a modern, performant, and developer-friendly experience specifically tailored for systems programming, while also remaining suitable for other domains.

  Inspired by a blend of C++, Rust, and other contemporary languages, Jakt seeks to incorporate the strengths of these predecessors while mitigating some of their perceived weaknesses. The language designers prioritize memory safety, aiming to prevent common pitfalls like dangling pointers and memory leaks, without resorting to garbage collection. This is achieved through a system of ownership and borrowing, reminiscent of Rust, enabling compile-time verification of memory access patterns.

  Jakt boasts a static type system, contributing to both performance and code reliability by catching type errors early in the development process. The language syntax is designed for clarity and readability, with an emphasis on expressiveness and minimizing boilerplate. It incorporates features such as algebraic data types, pattern matching, and generics, promoting concise and elegant code.

  While deeply integrated with SerenityOS, where it serves as the primary language for developing system components and applications, Jakt's aspirations extend beyond the confines of a single operating system. The long-term goal is to establish Jakt as a versatile and robust language capable of tackling a wide range of programming tasks across different platforms. The repository contains a comprehensive set of documentation, including a language specification, a style guide, and tutorials, indicating a commitment to fostering a thriving community around the language. The project is open-source and actively encourages contributions, inviting developers to participate in its ongoing evolution and refinement. The development roadmap outlines future enhancements, including improvements to the standard library, tooling, and compiler optimizations.

  • Jakt
  • programming language
  • SerenityOS
  • compiler
  • C++
  • Systems Programming
  • performance
  • Open Source
  • Software Development
  • GitHub

  Summary of Comments ( 18 )
  https://news.ycombinator.com/item?id=43437752

  Verbose tl;dr

  Hacker News users discuss Jakt's resemblance to C++, Rust, and Swift, noting its potential appeal to those familiar with these languages. Several commenters express interest in its development, praising its apparent simplicity and clean design, particularly the ownership model and memory management. Some skepticism arises about the long-term viability of another niche language, and concerns are voiced about potential performance limitations due to garbage collection. The cross-compilation ability for WebAssembly also generated interest, with users envisioning potential applications. A few commenters mention the project's active and welcoming community as a positive aspect. Overall, the comments indicate a cautious optimism towards Jakt, with many intrigued by its features but also mindful of the challenges facing a new programming language.

  The Hacker News post titled "The Jakt Programming Language," linking to the GitHub repository for the Jakt programming language, has generated a moderate amount of discussion. Several commenters express interest and enthusiasm for the project, focusing on specific aspects they find appealing.

  One recurring theme is appreciation for Jakt's memory management strategy using regions and arenas, seen as a simpler alternative to full-blown garbage collection while avoiding the pitfalls of manual memory management. Commenters discuss the benefits of this approach for performance and predictability, contrasting it with Rust's borrow checker and C++'s complexity. There's a comparison to Lobster's memory management system and discussion around whether arenas are a fully general solution for all use cases.

  Another significant point of discussion revolves around Jakt's focus on being a pragmatic, "C++ done right" language. Commenters compare and contrast it with other languages like Carbon, arguing that Jakt's smaller scope and clearer direction might contribute to its success. The influence of C++ and Rust on Jakt's design is noted, along with the potential benefits of incorporating good features from various sources. Some express skepticism about yet another new programming language, questioning whether it offers enough unique advantages to justify its existence.

  The project's active development and relatively accessible codebase are also highlighted as positive aspects. Commenters discuss the feasibility of contributing to the project and the overall welcoming nature of the SerenityOS community.

  Specific technical aspects, such as compile times and the language's overall performance, are also brought up. Some users share anecdotes about their experiences building and running Jakt code, while others inquire about potential optimizations and future plans.

  Finally, there are brief mentions of other related projects, like Zig, and discussions about the general landscape of modern programming languages. Several commenters express a desire to see Jakt mature and gain wider adoption, suggesting that it holds promise as a viable alternative to existing languages for certain use cases. While there's a general sense of cautious optimism, many acknowledge that the project is still relatively young and its long-term success remains to be seen.

• Autology: A Lisp with access to its own interpreter

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  Posted: 2025-03-21 10:37:16

  Verbose tl;dr

  Autology is a Lisp dialect designed for self-modifying code and introspection. It exposes its own interpreter and data structures, allowing programs to analyze and manipulate their own source code, execution state, and even the interpreter itself during runtime. This capability enables dynamic code generation, on-the-fly modifications, and powerful metaprogramming techniques. It aims to provide a flexible environment for exploring novel programming paradigms and building self-aware, adaptive systems.

  The GitHub repository titled "Autology: A Lisp with access to its own interpreter" introduces a novel Lisp dialect designed with a core principle of self-reflection, enabling the language to introspect and manipulate its own internal workings. This self-referential capability, a form of metacircularity, is achieved by granting Autology direct access to its own interpreter's state and functions. This means Autology programs can analyze and modify their own code, execution environment, and even the interpreter itself during runtime.

  The implementation, written in Raku (formerly known as Perl 6), focuses on providing a minimalistic core language featuring typical Lisp constructs like s-expressions, symbols, lists, and basic arithmetic operations. However, the key distinguishing feature, as highlighted in the title, is the exposure of the interpreter's internal functions as first-class citizens within the language. This empowers Autology programs to perform actions such as: inspecting the current execution environment, manipulating the abstract syntax tree (AST) of the code being executed, dynamically redefining functions, and even altering the behavior of the interpreter itself.

  The README provides examples demonstrating this self-modifying capability. One such example showcases how a user-defined function can access and modify the interpreter's environment, effectively allowing the program to rewrite itself on the fly. This dynamism opens possibilities for unique programming paradigms and allows for a high degree of flexibility and introspection not typically found in traditional Lisp dialects. While the project is still in its early stages of development, it offers a compelling exploration of the concept of a language having direct access to its own interpreter, potentially opening up new avenues for metaprogramming, code generation, and runtime adaptation. The Raku implementation further contributes to the project's novelty by leveraging Raku's expressiveness and modern features in constructing this unconventional Lisp interpreter.

  • Lisp
  • programming language
  • interpreter
  • metaprogramming
  • Self-Modifying Code
  • reflection
  • Autology
  • compiler
  • Code Generation
  • Symbolic Computation

  Summary of Comments ( 28 )
  https://news.ycombinator.com/item?id=43434010

  Verbose tl;dr

  HN users generally expressed interest in Autology, a Lisp dialect with access to its own interpreter. Several commenters compared it favorably to Rebol in terms of metaprogramming capabilities. Some discussion focused on its potential use cases, including live coding and creating interactive development environments. Concerns were raised regarding its apparent early stage of development, the lack of documentation beyond the README, and the potential performance implications of its design. A few users questioned the practicality of such a language, while others were excited by the possibilities it presented for self-modifying code and advanced debugging tools. The reliance on Python for its implementation also sparked some debate.

  The Hacker News post titled "Autology: A Lisp with access to its own interpreter" sparked a discussion with several interesting comments. Here's a summary:

  • Reflection and introspection capabilities: Several commenters focused on the power and potential of Autology's ability to access its own interpreter. They highlighted how this feature allows for powerful metaprogramming, enabling the language to modify and extend itself in dynamic ways. This capacity for introspection was seen as a key differentiator, enabling advanced techniques like creating new language constructs or modifying existing ones on the fly.

  • Comparison to other Lisps: The discussion naturally drew comparisons to other Lisp dialects, especially Common Lisp. Commenters debated the similarities and differences in their metaprogramming capabilities. Some pointed out that Common Lisp already offers significant introspection features, while others emphasized that Autology's approach, by giving direct access to the interpreter, potentially simplifies certain metaprogramming tasks.

  • Implementation details and performance: Some comments delved into the technical aspects of Autology's implementation. Questions were raised about how the interpreter access is managed and its potential impact on performance. Concerns about the overhead of such dynamic capabilities were also expressed.

  • Practical applications: While acknowledging the theoretical power of Autology's approach, some commenters questioned its practical applications. They wondered about real-world scenarios where direct access to the interpreter would be genuinely beneficial, and not just an academic curiosity. The need for concrete examples showcasing the practical advantages of this feature was highlighted.

  • The spirit of Lisp: Some commenters appreciated Autology for embracing the spirit of Lisp and pushing the boundaries of metaprogramming. They viewed it as a positive exploration of the potential of self-modifying code and a demonstration of the flexibility inherent in the Lisp family of languages.

  One of the more compelling threads involved a discussion of the tradeoffs between powerful metaprogramming features and the potential for increased complexity and difficulty in reasoning about code. Some argued that while the ability to modify the interpreter offered incredible flexibility, it could also lead to code that is harder to understand, debug, and maintain. The discussion revolved around finding a balance between power and practicality.

  Another interesting exchange focused on the differences between Autology's approach and existing metaprogramming techniques in other Lisps. This explored the nuances of manipulating the interpreter directly versus using more established mechanisms like macros. The discussion highlighted the subtle yet potentially significant distinctions between these methods and their implications for code organization and expressiveness.

• The earliest versions of the first C compiler known to exist

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  Posted: 2025-03-21 08:17:19

  Verbose tl;dr

  This GitHub repository preserves incredibly early versions of Dennis Ritchie's Portable C Compiler, including pre-1.0 snapshots dating back to the late 1970s. These versions offer a fascinating glimpse into the evolution of C, showcasing its transition from a research language to the widespread programming powerhouse it became. The repository aims to archive these historically significant artifacts, making them available for study and exploration by those interested in the origins and development of C. It includes various versions for different architectures, providing valuable insights into early compiler design and the challenges of portability in the nascent days of Unix.

  This GitHub repository, titled "legacy-cc," meticulously documents and preserves remarkably early versions of the first C compiler, specifically focusing on pre-1.0 iterations. These nascent compilers, dating back to the formative years of the C language itself, offer a fascinating glimpse into the evolution of both the language and its compilation process. The repository's author has undertaken the painstaking task of collecting and organizing these historical artifacts, many of which are scattered across various archives and personal collections, providing a centralized and accessible resource for researchers, historians, and anyone interested in the origins of C.

  The earliest compiler version present appears to be from 1972, showcasing the nascent state of the compiler technology and the C language itself. These archaic compilers likely represent a pivotal stage in the transition from the B language to C, exhibiting features and syntax that may appear unfamiliar to modern C programmers. The repository's contents likely include not just the compiler executables themselves but also accompanying documentation, source code (where available), and potentially even test suites used during the initial development and refinement of the compiler.

  The significance of this archive lies in its potential to shed light on the design decisions, compromises, and innovations made during C's infancy. By examining these early compilers, one could trace the development of core language features, observe the evolution of code optimization techniques, and perhaps even uncover forgotten or abandoned concepts. The preserved compilers likely represent a unique and invaluable resource for understanding the historical context surrounding the creation of one of the most influential programming languages in computing history, providing crucial insights into the foundation upon which modern systems and software are built. The effort to gather and maintain this collection undoubtedly represents a significant contribution to preserving the history of computer science.

  • C
  • C Compiler
  • compiler
  • History of C
  • legacy code
  • Retrocomputing
  • vintage computing
  • early computing
  • Software History
  • Programming language history
  • Source Code
  • GitHub
  • preservation
  • PDP-7
  • PDP-11

  Summary of Comments ( 97 )
  https://news.ycombinator.com/item?id=43433030

  Verbose tl;dr

  Hacker News users discussed the historical significance of the rediscovered C compiler source code, noting its use of PDP-11 assembly and the challenges of porting it to modern systems due to its tight coupling with the original hardware. Several commenters expressed interest in its educational value for understanding early compiler design and the evolution of C. Some debated the compiler's true "firstness," acknowledging earlier, possibly lost, versions, while others focused on the practical difficulties of building and running such old code. A few users shared personal anecdotes about their experiences with early C compilers and PDP-11 machines, adding a personal touch to the historical discussion. The overall sentiment was one of appreciation for the preservation and sharing of this piece of computing history.

  The Hacker News thread discussing "The earliest versions of the first C compiler known to exist" contains a modest number of comments, primarily focusing on the historical significance of the code and some technical details. No one expresses strong disagreement with the premise of the post.

  Several commenters express fascination and appreciation for the historical context of the code. One user notes the importance of seeing these early versions to understand the evolution of the language and compiler technology. Another marvels at the simplicity and directness of the early code, highlighting the limited hardware resources of the time. A few commenters express a sense of nostalgia, reminiscing about their early experiences with C and PDP-11 systems.

  There's some discussion of the technical aspects of the compiler, including the use of PDP-11 assembly language and the limited optimization strategies employed. One commenter points out the clear connection between the C code and the generated assembly, emphasizing the straightforward nature of the compilation process in these early versions. Another commenter highlights the comment about the lack of register allocation in the oldest version, explaining how this would impact performance.

  A couple of users point out the significance of seeing how features like floating-point support were added incrementally to the compiler. One commenter contrasts the manual optimization efforts required in the past with modern compiler optimization techniques.

  A few commenters provide additional historical context or links to related resources. One user links to an oral history of Dennis Ritchie discussing the development of C. Another mentions the book "Lions' Commentary on UNIX 6th Edition," which provides a detailed analysis of an early Unix kernel, including parts written in C using a similar compiler.

  Overall, the comments demonstrate a shared appreciation for the historical value of the preserved code, reflecting on the evolution of C and the ingenuity of its early developers. While the discussion isn't extensive, it provides valuable insights and context for understanding the significance of this piece of computing history.

• Converting C to ASM to specs and then to a working Z/80 Speccy tape

  permalink

  Posted: 2025-03-17 11:17:09

  Verbose tl;dr

  The author details the process of creating a ZX Spectrum game from scratch, starting with C code for core game logic. This C code was then manually translated into Z80 assembly, a challenging process requiring careful consideration of memory management and hardware limitations. After the assembly code was complete, they created a loading screen and integrated everything into a working .tap file, the standard format for Spectrum games. This involved understanding the intricacies of the Spectrum's tape loading system and manipulating audio frequencies to encode the game data for reliable loading on original hardware. The result was a playable game demonstrating a complete pipeline from high-level language to a functional retro game program.

  This blog post chronicles the author's intricate journey of transforming a simple C program into a functional program on a ZX Spectrum, a classic 8-bit home computer from the 1980s. The process involved multiple stages of translation and conversion, each requiring careful consideration of the target platform's limitations and quirks.

  Initially, the author began with a rudimentary C program designed to display a sequence of color changes on the screen. This C code served as the high-level blueprint for the subsequent transformations. The first step involved compiling the C code into Z80 assembly language, the native language understood by the ZX Spectrum's Z80 processor. This translation process necessitated adapting the C code's logic and data structures to the more primitive constructs available in assembly language.

  Next, the generated assembly code was further refined into a format suitable for the ZX Spectrum's specific hardware and operating system. This involved incorporating system calls and memory management techniques particular to the ZX Spectrum. The author meticulously addressed details such as screen memory mapping and color palette manipulation to ensure compatibility with the target platform.

  The final stage involved converting the tailored assembly code into a format that could be loaded and executed on the ZX Spectrum. This involved packaging the code into a .TAP file, a standard format used for distributing programs on audio cassette tapes, the primary storage medium for the ZX Spectrum. This .TAP file contained not just the program code itself, but also the necessary loading instructions and metadata for the ZX Spectrum's tape loading system. The author accomplished this using a dedicated tool designed specifically for generating .TAP files from assembly code. This tool handled the intricacies of encoding the data into an audio format suitable for playback on a cassette player and subsequent loading into the ZX Spectrum.

  The successful outcome of this process was a functional .TAP file that, when played back on a cassette player connected to a ZX Spectrum, correctly reproduced the color sequence originally defined in the C program. The author's journey demonstrates the intricate process of developing software for retro hardware platforms, showcasing the multiple layers of abstraction and conversion required to bridge the gap between modern programming languages and the limitations of vintage computing systems.

  • C
  • Assembly Language
  • ASM
  • Z80
  • ZX Spectrum
  • Retrocomputing
  • Emulation
  • Low-Level Programming
  • Computer Architecture
  • Software Development
  • compiler
  • tape
  • ROM
  • binary
  • Machine Code

  Summary of Comments ( 56 )
  https://news.ycombinator.com/item?id=43387259

  Verbose tl;dr

  Hacker News users discuss the impressive feat of converting C code to Z80 assembly and then to a working ZX Spectrum tape. Several commenters praise the author's clear explanation of the process and the clever tricks used to optimize for the Z80's limited resources. Some share nostalgic memories of working with the ZX Spectrum and Z80 assembly, while others delve into technical details like memory management and the challenges of cross-development. A few highlight the educational value of the project, showing the direct connection between high-level languages and the underlying hardware. One compelling comment thread discusses the efficiency of the generated Z80 code compared to hand-written assembly, with differing opinions on whether the compiler's output could be further improved. Another interesting exchange revolves around the practical applications of such a technique today, ranging from embedded systems to retro game development.

  The Hacker News post discussing the blog post "Converting C to ASM to specs and then to a working Z/80 Speccy tape" has generated a moderate number of comments, mostly focusing on the intricacies of Z80 programming, the Spectrum's limitations, and the author's approach.

  Several commenters expressed admiration for the author's dedication and the ingenuity required to work within the constraints of the ZX Spectrum. One user highlighted the complexity of managing memory and timing on such a limited system, particularly noting the challenge of fitting code within the Spectrum's tight memory constraints. Another commenter reminisced about the challenges and rewards of programming for the Spectrum during its heyday, emphasizing the creativity fostered by its limitations. The clever use of the undocumented HALT instruction to achieve precise timing was specifically pointed out and praised by multiple commenters.

  There's a discussion around the tools and techniques used in the Z80 development ecosystem back then. One user mentioned the use of disassemblers and how they helped understand the inner workings of games and other programs, sometimes even leading to modifications and improvements. Another recalled the prevalence of manually crafted assembly routines and the importance of understanding hardware nuances.

  The conversation also touched upon the differences between the Z80 and other processors like the 6502, with comparisons being made regarding their architectures, instruction sets, and the resulting programming paradigms. One comment delved into the specifics of how the Z80 handles interrupts, contrasting it with the 6502's approach.

  Some users expressed a desire for more technical details in the blog post itself, particularly regarding the author's choices in assembly optimization and memory management. A specific request was made for more information on how the author interfaced the C code with the Z80 assembly.

  Finally, there's a thread discussing the broader context of retrocomputing and the enduring fascination with older hardware and software. The challenges and satisfaction of working with these systems were highlighted, emphasizing the different mindset required compared to modern development practices. One user pointed out the significant cognitive overhead involved in managing limited resources and the deeper understanding of hardware it necessitated.

• C Plus Prolog

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  Posted: 2025-03-13 22:48:45

  Verbose tl;dr

  C Plus Prolog is a project that embeds a Prolog interpreter within C++ code, allowing for logic programming within a C++ application. It aims to provide a seamless integration where Prolog predicates can be called directly from C++ and vice-versa, enabling the combination of Prolog's declarative power with C++'s performance and imperative features. The project leverages a modified version of SWI-Prolog, a popular open-source Prolog implementation, and offers a bidirectional interface for data exchange between the two languages. This facilitates the development of applications that benefit from both efficient procedural code and the logical reasoning capabilities of Prolog.

  The GitHub repository titled "C Plus Prolog" by user needleful presents an ambitious undertaking: the creation of a programming language that seamlessly blends the strengths of C++ and Prolog. This hybrid language aims to leverage C++'s performance and low-level control capabilities alongside Prolog's declarative logic programming paradigm. The project envisions a synergistic relationship where C++ code can call Prolog predicates and vice versa, facilitating a powerful combination of procedural and logical programming styles.

  The integration is envisioned to be deep and bidirectional. C++ programmers would gain access to Prolog's logic and reasoning capabilities, allowing for complex tasks like pattern matching, constraint solving, and knowledge representation to be embedded directly within their C++ programs. Conversely, Prolog programmers would be empowered to leverage the performance and extensive libraries of C++, enabling them to write Prolog code that can interact directly with system resources and perform computationally intensive tasks that might be inefficient in pure Prolog.

  The repository details a complex implementation strategy involving a sophisticated parsing mechanism and a custom runtime environment. It sketches a plan for converting Prolog's logical expressions into a form suitable for execution within the C++ environment, potentially leveraging C++'s template metaprogramming capabilities for optimization. While the project appears to be in its early stages of development, the outlined architecture suggests a desire for a robust and performant implementation that goes beyond simple interoperability and aims for a genuine fusion of the two languages. The repository highlights the potential benefits of such a hybrid language, particularly in areas like artificial intelligence, natural language processing, and expert systems, where both performance and logical reasoning are crucial. The outlined approach intends to address the shortcomings of each language in isolation by complementing them with the other's strengths, ultimately leading to a more expressive and versatile programming paradigm.

  • C++
  • Prolog
  • Logic Programming
  • Integration
  • Embedding
  • Foreign Function Interface
  • FFI
  • Hybrid Language
  • Programming Languages
  • parser
  • compiler

  Summary of Comments ( 45 )
  https://news.ycombinator.com/item?id=43357955

  Verbose tl;dr

  Hacker News users discussed the practicality and niche appeal of C Plus Prolog. Some expressed interest in its potential for specific applications like implementing rule engines or program analysis tools, while others questioned the performance implications of embedding Prolog within C++. One commenter suggested that a cleaner approach might involve interfacing Prolog with a language like Rust. Several pointed out the project's age and apparent inactivity, raising concerns about maintainability and documentation. The potential for improved tooling using C++-based IDEs was mentioned as a possible benefit. Overall, the discussion centered around the specialized nature of the project and the trade-offs involved in its approach.

  The Hacker News post titled "C Plus Prolog" (https://news.ycombinator.com/item?id=43357955) has a modest number of comments, generating a brief discussion around the project. No single comment overwhelmingly dominates the conversation, but a few key themes and interesting points emerge.

  One commenter expresses intrigue, questioning whether the project acts as a Prolog interpreter embedded within C++, allowing Prolog code to be executed directly. They further ponder the possibility of bidirectional communication between the C++ and Prolog components, imagining scenarios where Prolog could be utilized for tasks like constraint solving or symbolic manipulation within a larger C++ application.

  Another commenter, seemingly familiar with Prolog development, points out that the "cut" operator (!) and negation by failure are notably absent from the project's feature list. They suggest these are essential features for practical Prolog programming, hinting that their absence might limit the project's usefulness for more complex logic programming tasks. This comment also raises the question of whether the project implements a full unification algorithm, crucial for Prolog's core functionality.

  A subsequent reply acknowledges the missing features but clarifies that the primary goal of the project isn't to create a fully-fledged Prolog implementation. Instead, it aims to demonstrate a simpler approach to implementing a Prolog-like system within C++. This comment effectively reframes the project, suggesting it should be viewed more as an educational exercise or a proof-of-concept rather than a production-ready tool.

  Finally, another commenter briefly mentions a different Prolog interpreter written in C++, called "scryer-prolog," implying it might be a more mature or feature-complete alternative for those seeking a robust Prolog implementation. This comment serves as a helpful pointer for anyone interested in exploring other options within the same domain.

  In summary, the discussion around "C Plus Prolog" on Hacker News focuses on its functionality, clarifying its scope as a demonstrative implementation rather than a full Prolog interpreter. Commenters highlight missing features crucial for complex Prolog programming and suggest alternative, potentially more robust implementations. The overall tone remains inquisitive and informative, providing context and further avenues for exploration within the realm of Prolog and C++ integration.

• A 10x Faster TypeScript

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  Posted: 2025-03-11 14:32:23

  Verbose tl;dr

  Microsoft is developing a new TypeScript compiler implementation called "tsc-native" built using native C++. This new compiler aims to drastically improve TypeScript compilation speed, potentially making it up to 10x faster than the existing JavaScript-based compiler. The project leverages the V8 JavaScript engine's TurboFan JIT compiler to optimize performance-critical parts of the type checking process. While still experimental, initial benchmarks show significant improvements, particularly for large projects. The team is actively working on refining the compiler and invites community feedback as they progress towards a production-ready release.

  This Microsoft Developer Blog post announces a significant performance boost for TypeScript compilation through a new project called "TypeScript Native". The post highlights the inherent performance limitations of JavaScript, the language TypeScript currently compiles to, and posits that achieving substantial further speed improvements using JavaScript as an intermediary is unlikely. Therefore, the TypeScript team has embarked on exploring compiling TypeScript directly to native machine code, bypassing JavaScript entirely.

  This new compilation strategy leverages the established and highly optimized LLVM compiler infrastructure. By emitting LLVM Intermediate Representation (LLVM IR) instead of JavaScript, TypeScript Native can harness the power of LLVM's optimizations for speed and potentially size reductions in the final compiled output. The blog post details that this approach could theoretically yield up to a 10x performance improvement in compilation times, although actual results are still preliminary and vary based on the specific codebase.

  The project is still in its early stages, explicitly labeled as experimental. The current implementation focuses specifically on targeting Node.js using the Node-API (N-API). This allows the native compiled code to interact seamlessly with the Node.js runtime environment. Other platforms like the browser or standalone executables are not currently supported but represent potential future expansions of the project.

  The post emphasizes that TypeScript Native aims to maintain full compatibility with existing TypeScript code. Developers shouldn't need to modify their code to leverage the benefits of native compilation. The goal is to provide a transparent performance upgrade without disrupting established workflows.

  The post also underscores that this is an exploratory project and does not represent a finalized or guaranteed future direction for TypeScript. The team is actively soliciting feedback from the community to assess the viability and desirability of this native compilation approach. They are interested in understanding the potential use cases, performance gains observed in real-world projects, and any challenges or limitations encountered by developers experimenting with TypeScript Native. The blog post provides links and instructions for how interested developers can try out the experimental build and contribute their feedback to the project.

  • TypeScript
  • performance
  • javascript
  • Web Development
  • compiler
  • Native Compilation
  • Speed
  • optimization
  • Microsoft
  • developer tools
  • Programming Languages
  • software engineering

  Summary of Comments ( 616 )
  https://news.ycombinator.com/item?id=43332830

  Verbose tl;dr

  Hacker News users discussed the potential impact of a native TypeScript compiler. Some expressed skepticism about the claimed 10x speed improvement, emphasizing the need for real-world benchmarks and noting that compile times aren't always the bottleneck in TypeScript development. Others questioned the long-term viability of the project given Microsoft's previous attempts at native compilation. Several commenters pointed out that JavaScript's dynamic nature presents inherent challenges for ahead-of-time compilation and optimization, and wondered how the project would address issues like runtime type checking and dynamic module loading. There was also interest in whether the native compiler would support features like decorators and reflection. Some users expressed hope that a faster compiler could enable new use cases for TypeScript, like scripting and game development.

  The Hacker News post "A 10x Faster TypeScript" (linking to a Microsoft blog post about a native port of TypeScript) generated a moderate discussion with several interesting comments. Many commenters expressed cautious optimism about the project, acknowledging the potential performance benefits while also raising concerns and questions.

  A recurring theme was skepticism about whether the claimed 10x speed improvement would translate to real-world scenarios. Some users pointed out that the benchmarks presented might not be representative of typical TypeScript projects. One commenter highlighted the importance of I/O operations in many workflows and questioned whether a native port would significantly impact those. Another user suggested that the speed improvements might be more pronounced in specific use cases, like build processes, but less noticeable during regular development.

  Several commenters also discussed the trade-offs associated with a native implementation. One user raised the issue of platform compatibility, questioning whether the native port would be available on all operating systems supported by the existing TypeScript implementation. Concerns were also expressed about potential debugging challenges and the maturity of the native toolchain.

  Some commenters expressed interest in the potential for improved IDE performance. They speculated that a native TypeScript compiler could lead to faster code completion and error checking within integrated development environments.

  A few comments touched on the technical aspects of the native port. One user inquired about the memory management implications and whether the native implementation would introduce any garbage collection overhead. Another comment mentioned the possibility of using WebAssembly as an alternative approach to improving TypeScript performance.

  While there was general excitement about the prospect of a faster TypeScript, the comments reflected a pragmatic outlook, with many users emphasizing the need for more information and real-world testing before drawing definitive conclusions. Notably, several commenters requested more detailed benchmarks and comparisons with alternative solutions. The overall sentiment was one of cautious interest and a desire to see how the project evolves.

• Three Implementation Models for Scheme (1987) [pdf]

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  Posted: 2025-03-11 13:19:29

  Verbose tl;dr

  This 1987 paper by Dybvig explores three distinct implementation models for Scheme: compilation to machine code, abstract machine interpretation, and direct interpretation of source code. It argues that while compilation offers the best performance for finished programs, the flexibility and debugging capabilities of interpreters are crucial for interactive development environments. The paper details the trade-offs between these models, emphasizing the advantages of a mixed approach that leverages both compilation and interpretation techniques. It concludes that an ideal Scheme system would utilize compilation for optimized execution and interpretation for interactive use, debugging, and dynamic code loading, hinting at a system where the boundaries between compiled and interpreted code are blurred.

  This 1987 paper by Dybvig, Hieb, and Bruggeman, titled "Three Implementation Models for Scheme," explores and contrasts three distinct models for implementing Scheme interpreters and compilers, aiming to illustrate the design space and trade-offs involved. These models, each representing a different point in the spectrum of implementation strategies, are termed the "Abstract Machine Model," the "Compiler Model," and the "Control Model." The authors delve into the strengths and weaknesses of each, considering factors such as performance, portability, debugging capabilities, and ease of implementation.

  The Abstract Machine Model involves defining an abstract machine specifically designed for executing Scheme code. This abstract machine is characterized by a set of instructions tailored to Scheme's semantics, and an implementation consists of a virtual machine or interpreter for these instructions, often written in a lower-level language. This model offers a relatively straightforward implementation path and facilitates portability, as the interpreter can be implemented on various platforms. However, it can introduce performance overhead compared to compiled approaches due to the interpretation layer. The paper uses the Orbit compiler as an exemplary case of this model.

  The Compiler Model focuses on directly translating Scheme code into native machine code for the target architecture. This approach prioritizes execution speed and leverages existing compiler technologies. The compiler performs various optimizations to generate efficient machine code, potentially resulting in significantly faster execution than interpreted approaches. However, this model can be more complex to implement due to the intricacies of code generation and optimization. Furthermore, portability is sacrificed as the compiler needs to be tailored for each target architecture. The paper references the Rabbit compiler as an example of this model, highlighting its focus on efficient code generation.

  The Control Model takes a novel approach by representing Scheme programs as data structures that can be directly manipulated and evaluated by a core interpreter. This model emphasizes flexibility and dynamic behavior, particularly for features like continuations, which are challenging to implement efficiently in other models. Scheme programs are transformed into continuation-passing style (CPS), enabling sophisticated control flow manipulations. While this model provides elegance and powerful expressiveness, it can present performance challenges due to the overhead of representing and manipulating the control structures. The paper discusses the Chez Scheme system as an embodiment of the control model, illustrating its use of CPS and its focus on supporting advanced Scheme features efficiently.

  The authors meticulously dissect each model, presenting their underlying mechanisms, advantages, and disadvantages. They provide insightful comparisons, emphasizing how each model addresses fundamental implementation challenges. The paper concludes by summarizing the key characteristics of each model and offering guidance on choosing the appropriate model based on specific project requirements and priorities. The overall contribution lies not in advocating for a single best approach, but rather in providing a comprehensive framework for understanding the trade-offs inherent in implementing a Scheme system, empowering developers to make informed design decisions.

  • Scheme
  • programming language
  • Implementation
  • interpreter
  • compiler
  • virtual machine
  • 1987
  • PDF
  • Computer Science
  • programming language design
  • Programming Language Theory
  • formal methods

  Summary of Comments ( 4 )
  https://news.ycombinator.com/item?id=43332143

  Verbose tl;dr

  HN commenters discuss the historical significance of the paper in establishing Scheme's minimalist design and portability. They highlight the cleverness of the three implementations, particularly the threaded code interpreter, and its influence on later languages like Lua. Some note the paper's accessibility and clarity, even for those unfamiliar with Scheme, while others reminisce about using the techniques described. A few comments delve into technical details like register allocation and garbage collection, comparing the approaches to modern techniques. The overall sentiment is one of appreciation for the paper's contribution to computer science and programming language design.

  The Hacker News post linking to the 1987 paper "Three Implementation Models for Scheme" has generated a moderate number of comments, mostly focusing on the historical context of the paper and its significance in understanding Scheme implementations.

  One commenter highlights the paper's importance for its clear explanation of the tradeoffs between different implementation strategies for Scheme, even today. They specifically mention how the paper's discussion of the "big picture" helps in understanding modern compiler discussions about register allocation and garbage collection.

  Another comment points out the historical significance of the paper being published before the standardization of Scheme, resulting in the paper using a slightly different Scheme dialect. They also mention how the paper elegantly illustrates the common trade-offs in language implementation using a relatively small language like Scheme.

  Several comments discuss the efficiency of various Scheme implementations and their approaches to compilation. One user mentions Indiana University's historical connection to Scheme and its compiler technology.

  One comment delves deeper into the technical aspects, discussing how the paper's approach to environment representation is less relevant today due to advancements in generational garbage collection and precise stack maps. However, they acknowledge that the register allocation techniques discussed are still relevant.

  Some users also shared anecdotal experiences about learning Scheme and using different implementations, highlighting personal connections to the historical context of the paper.

  A few comments briefly touch upon the broader context of language design and implementation, comparing Scheme to other languages. One commenter notes the influence of the paper's authors on later work at Sun Microsystems related to Self and Java JIT compilers.

  While the number of comments isn't extensive, they offer valuable insights into the historical relevance of the paper, its technical contributions, and its influence on subsequent developments in language implementation. The discussion largely revolves around appreciating the clarity and conciseness of the paper in explaining fundamental tradeoffs that remain relevant in contemporary compiler design.

• Compiling C++ with the Clang API

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  Posted: 2025-03-09 11:51:36

  Verbose tl;dr

  This blog post demonstrates how to compile C++ code using the Clang API, focusing on practical examples and clear explanations. It walks through creating a simple compiler driver, configuring compilation arguments like include paths and optimization levels, and invoking the Clang frontend to generate LLVM IR. The post highlights key components of the Clang API like clang::FrontendAction and clang::ASTConsumer, and showcases how to handle diagnostics and access compilation results. It provides a foundation for building tools that leverage Clang's powerful analysis and transformation capabilities.

  This blog post by MaskRay details how to compile C++ code using the Clang API, offering a practical guide for programmatically controlling the compilation process. It begins by highlighting the common use case of embedding Clang for tasks like static analysis or source-to-source transformations, where invoking the compiler driver directly isn't ideal. The author then dives into a concrete example, presenting C++ code that leverages the Clang library to compile a simple "Hello, world!" program.

  The post meticulously walks through the code, explaining the essential steps involved. It starts with creating a clang::CompilerInstance, the primary object representing a single invocation of the compiler. It emphasizes the importance of configuring this instance properly, including setting up diagnostics for error reporting, a target information object describing the target architecture, and a file system for accessing source files. The example specifically shows how to configure these components for a simple x86-64 Linux target.

  The core of the compilation process is explained through the creation and execution of a clang::FrontendAction. The author opts for the clang::EmitLLVMOnlyAction in the example, which generates LLVM bitcode instead of fully compiled machine code. This choice simplifies the demonstration by avoiding the complexities of backend code generation. The process of creating and executing this action within the CompilerInstance is detailed, including how to set up the necessary input source file.

  A significant portion of the post is dedicated to explaining the diagnostic handling mechanism. It describes how to create and configure a clang::DiagnosticConsumer to process compilation errors and warnings. The example uses a clang::TextDiagnosticPrinter to output diagnostics to the console in a human-readable format. The author further illustrates how to collect diagnostic options, such as the desired format and warning flags, and associate them with the diagnostic printer.

  Finally, the post demonstrates how to execute the compilation by calling the ExecuteAction method on the CompilerInstance. It highlights the importance of checking the return value of this function to determine if the compilation was successful. The generated LLVM bitcode is not explicitly handled in the example as the focus remains on the compilation process itself. The post concludes by providing the complete, compilable code example, allowing readers to readily experiment and adapt it for their own projects. The author also briefly touches upon the possibility of extending the example to compile multiple files and handle different output formats, encouraging further exploration of the Clang API.

  • C++
  • Clang
  • compiler
  • API
  • Compilation
  • Code Generation
  • abstract syntax tree (AST)
  • LibTooling
  • LLVM

  Summary of Comments ( 13 )
  https://news.ycombinator.com/item?id=43308259

  Verbose tl;dr

  Hacker News users discussed practical aspects of using the Clang API. Some pointed out the steep learning curve and lack of comprehensive documentation, making it challenging to navigate and debug. Others highlighted the API's power and flexibility for tasks like code analysis, transformation, and generation, exceeding the capabilities of simpler tools. A few commenters shared alternative approaches or libraries for specific use cases, such as libTooling for simpler tasks and Tree-sitter for parsing. The lack of good error messages from the Clang API was also mentioned, along with the difficulty of integrating it into build systems like CMake.

  The Hacker News post "Compiling C++ with the Clang API" has generated a modest discussion with several insightful comments.

  One commenter highlights the complexity of the Clang API, mentioning that even seemingly simple tasks can require delving into the source code. They appreciate the author's clear explanation and example code, which they believe will be helpful to others navigating the Clang ecosystem. This comment resonates with the overall sentiment that the Clang API, while powerful, presents a steep learning curve.

  Another user focuses on the utility of the Clang API for tasks like code generation and refactoring, pointing out its advantages over simpler approaches like string manipulation. This comment emphasizes the power and flexibility of the Clang API for complex code manipulations, where understanding the underlying Abstract Syntax Tree (AST) is crucial. They also suggest that this approach allows for more robust and accurate transformations.

  A further comment questions the necessity of building with CMake, suggesting that a simpler build system could suffice for the provided example. This sparks a brief discussion about the trade-offs of build system complexity, with arguments for and against using a powerful build system like CMake for smaller projects. While the commenter acknowledges the potential benefits of CMake for larger projects, they imply that its overhead might be excessive for this particular use case.

  Finally, another commenter shares their own struggles with the Clang API, particularly in dealing with templates and the AST. This comment reinforces the previously mentioned difficulty of the Clang API and emphasizes the value of readily available examples like the one provided by the blog post author.

  In summary, the comments section expresses appreciation for the author's clear explanation of a complex topic. The discussion revolves around the challenges and power of the Clang API, the trade-offs of build system complexity, and the importance of practical examples for navigating the intricacies of programmatically interacting with the Clang compiler.

• Gleam v1.9.0 Released

  permalink

  Posted: 2025-03-09 11:06:38

  Verbose tl;dr

  Gleam v1.9.0 introduces improved error messages, specifically around type errors involving records and incorrect argument counts. It also adds the gleam echo command, a helpful tool for debugging pipelines by printing values at different stages. Additionally, the release includes experimental support for Git integration, allowing Gleam to leverage Git information for dependency resolution and package management. This simplifies workflows and improves dependency management within projects, especially for local development and testing.

  The Gleam programming language has reached a significant milestone with the release of version 1.9.0. This update introduces several noteworthy features and improvements that enhance the language's capabilities and developer experience. A primary focus of this release is improved interoperability with Erlang and Elixir, achieved through the introduction of the gleam_erlang package. This package facilitates seamless interaction with existing Erlang and Elixir code by allowing Gleam to directly call Erlang functions, significantly expanding the ecosystem accessible to Gleam developers.

  The addition of the gleam echo command provides developers with a new tool for prototyping and experimentation. This command enables the immediate execution of Gleam code snippets directly from the command line, streamlining the process of testing small pieces of code without the need for complex project setup or compilation. This rapid feedback loop can significantly boost developer productivity, particularly during the exploratory phases of development.

  Further enhancing developer workflow, Gleam v1.9.0 introduces improved integration with Git. The compiler now embeds Git commit hashes into compiled artifacts, offering valuable insights into the specific version of the code used to produce a given build. This feature enhances reproducibility and simplifies debugging by enabling precise tracking of the codebase's state. Furthermore, errors originating from macros now include line numbers, making it easier to identify and rectify issues within macro definitions.

  Finally, the release incorporates various bug fixes and performance optimizations that contribute to a more stable and efficient Gleam development experience. These under-the-hood improvements, while not always immediately visible, play a crucial role in ensuring the overall quality and reliability of the language. In summary, Gleam v1.9.0 represents a notable step forward for the language, offering enhanced interoperability, improved tooling, and greater developer convenience.

  • Gleam
  • release
  • v1.9.0
  • programming language
  • Functional Programming
  • Erlang VM
  • BEAM
  • concurrency
  • Static Typing
  • compiler

  Summary of Comments ( 16 )
  https://news.ycombinator.com/item?id=43307987

  Verbose tl;dr

  Hacker News users discussed the Gleam v1.9.0 release, largely focusing on its novel approach to error handling. Several commenters praised the explicit and exhaustive nature of error handling in Gleam, contrasting it favorably with Elixir's approach, which some found less strict. The discussion also touched upon the tradeoffs between Gleam's stricter error handling and potential verbosity, with some acknowledging the benefits while others expressed concerns about potential boilerplate. A few comments highlighted the language's growing maturity and ecosystem, while others inquired about specific features like concurrency and performance. One commenter appreciated the clear and concise changelog, a sentiment echoed by others who found the update informative and well-presented. The overall tone was positive, with many expressing interest in exploring Gleam further.

  The Hacker News post titled "Gleam v1.9.0 Released" linking to the Gleam v1.9.0 release announcement has a modest number of comments, focusing primarily on comparisons to other languages and ecosystems, and some discussion of Gleam's specific features.

  One commenter expresses excitement about Gleam, noting its resemblance to Elm, but built on Erlang. They appreciate the robustness of the Erlang VM and the familiar syntax for those coming from Elm. This commenter sees potential in Gleam for front-end development through compilation to JavaScript, though they acknowledge this is not the primary focus.

  Another comment draws a comparison to Elixir, highlighting the choice between Gleam's static typing and Elixir's dynamic typing. This commenter also mentions Gleam's focus on "correctness," which presumably refers to the benefits of its static type system. They also point out Gleam’s JavaScript compilation target, though they also acknowledge this is likely not the primary target.

  A third comment focuses on the choice of JavaScript as a compilation target, questioning its long-term viability compared to WebAssembly (Wasm). This commenter acknowledges Gleam's primary target as Erlang/Elixir, but expresses a desire for languages to prioritize Wasm for broader frontend applicability.

  A further comment expands on the WebAssembly discussion, suggesting that targeting JavaScript limits Gleam's potential reach for front-end developers. This commenter sees value in targeting both JavaScript and Wasm, allowing developers to choose the best option for their needs.

  The remainder of the comments are shorter and less substantive. One user simply expresses their enjoyment of using Gleam, while another asks a clarifying question about whether Gleam uses BEAM (the Erlang virtual machine), which is confirmed by another user. Finally, one comment promotes an alternative statically typed language for the Erlang VM called Caramel.

  In summary, the comments on this Hacker News post generally express interest in and appreciation for Gleam. Key discussion points include comparisons to Elm and Elixir, the advantages of static typing, and the choice of JavaScript as a compilation target versus WebAssembly. The conversation remains focused on Gleam's features and its place within the broader ecosystem of functional programming languages.

• LFortran Compiles Prima

  permalink

  Posted: 2025-03-06 15:00:23

  Verbose tl;dr

  LFortran can now compile Prima, a Python plotting library, demonstrating its ability to compile significant real-world Python code into performant executables. This milestone was achieved by leveraging LFortran's Python transpiler, which converts Python code into Fortran, and then compiling the Fortran code. This allows users to benefit from both the ease of use of Python and the performance of Fortran, potentially accelerating scientific computing workflows that utilize Prima for visualization. This achievement highlights the progress of LFortran toward its goal of providing a modern, performant Fortran compiler while also serving as a performance-enhancing tool for Python.

  The LFortran blog post titled "LFortran Compiles Prima" details a significant advancement in the LFortran compiler's capabilities: the successful compilation of the Prima codebase. Prima is a sophisticated plotting library written in Fortran, historically reliant on the pgplot graphics library for its rendering backend. This reliance on pgplot presented a challenge for modern Fortran development due to pgplot's older design and limitations in areas like interactive plotting. LFortran's accomplishment lies in its ability to compile and execute Prima's code without requiring pgplot, leveraging instead its own modern ASR (Abstract Syntax Tree) based architecture and a modern plotting backend.

  This achievement is broken down into multiple facets. First, LFortran's ability to parse and analyze Prima's extensive Fortran codebase demonstrates its maturity and robustness as a compiler. Second, the successful compilation indicates compatibility between LFortran and a substantial, real-world scientific code, showcasing its practical applicability. Third, LFortran's capacity to replace the pgplot dependency with a more contemporary alternative underlines the project's commitment to modernizing the Fortran ecosystem. This not only streamlines the compilation and execution process but also paves the way for enhanced plotting functionalities and potentially improved performance. The post highlights the modifications implemented within LFortran's own ASR and built-in functions to accommodate Prima’s specific requirements, which included replicating some of pgplot’s core functionalities. This involved significant work to ensure accurate and efficient emulation of pgplot's behavior within LFortran's framework. Furthermore, the post emphasizes the goal of moving beyond mere emulation towards fully integrating modern plotting backends. This implies that LFortran's team intends to provide native support for contemporary graphics libraries, offering a significant advantage to Fortran programmers utilizing plotting functionalities. Finally, the successful compilation of Prima serves as a substantial step forward in LFortran's development, demonstrating its capability to handle complex, real-world codebases and pushing the boundaries of modern Fortran development by enabling the use of updated, powerful graphics libraries.

  • LFortran
  • Fortran
  • compiler
  • Prima
  • Scientific Computing
  • High-Performance Computing
  • Numerical Computation
  • Programming Languages
  • Open Source
  • LLVM

  Summary of Comments ( 9 )
  https://news.ycombinator.com/item?id=43280985

  Verbose tl;dr

  Hacker News users discussed LFortran's ability to compile Prima, a computational physics library. Several commenters expressed excitement about LFortran's progress and potential, particularly its interactive mode and ability to modernize Fortran code. Some questioned the choice of Prima as a demonstration, suggesting it's a niche library. Others discussed the challenges of parsing Fortran's complex grammar and the importance of tooling for scientific computing. One commenter highlighted the potential benefits of transpiling Fortran to other languages, while another suggested integration with Jupyter for enhanced interactivity. There was also a brief discussion about Fortran's continued relevance and its use in high-performance computing.

  The Hacker News post "LFortran Compiles Prima" (https://news.ycombinator.com/item?id=43280985) has generated several comments discussing LFortran's progress and its potential impact on scientific computing.

  Several commenters express excitement about LFortran's ability to compile Prima, a computational physics library. They see this as a significant step forward, demonstrating LFortran's increasing maturity and capability to handle complex scientific codebases. The successful compilation of Prima is viewed as a validation of LFortran's approach and its potential to become a viable alternative to existing Fortran compilers.

  Some commenters highlight the potential benefits of LFortran, particularly its interactive mode and potential for improved debugging and code exploration. The interactive nature of LFortran is seen as a major advantage for scientific computing, where iterative development and experimentation are common.

  There's a discussion around the challenges of modernizing Fortran and the role LFortran might play in this process. Commenters acknowledge the legacy of Fortran in scientific computing and the need for modern tools to maintain and enhance existing codebases. LFortran is mentioned as a possible solution, offering a more modern development experience while maintaining compatibility with existing Fortran code.

  A few commenters inquire about LFortran's performance compared to established compilers like gfortran and ifort. Performance is a critical factor in scientific computing, and the community is keen to understand how LFortran compares in this regard. While some preliminary benchmarks are mentioned, there's a general desire for more comprehensive performance data.

  One commenter expresses skepticism about the long-term viability of Fortran, questioning the language's relevance in the modern scientific computing landscape. However, other commenters counter this argument by emphasizing the vast amount of existing Fortran code and the continued use of Fortran in high-performance computing. They argue that LFortran can help bridge the gap between legacy code and modern tooling, extending the lifespan of Fortran in scientific research.

  Overall, the comments reflect a generally positive sentiment towards LFortran and its potential to revitalize Fortran development. The successful compilation of Prima is seen as a major milestone, and the community is eager to see how the project continues to evolve. There is also a healthy discussion about the future of Fortran and the role LFortran might play in shaping that future.

• Type++: Prohibiting Type Confusion with Inline Type Information [pdf]

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  Posted: 2025-02-28 12:19:00

  Verbose tl;dr

  Type++ is a novel defense against type confusion vulnerabilities that leverages inline type information to enforce type constraints at runtime with minimal overhead. It embeds compact type metadata directly within objects, enabling efficient runtime checks to ensure that memory accesses and operations are consistent with the declared type. The system utilizes a flexible metadata representation supporting diverse types and inheritance hierarchies, and employs a selective instrumentation strategy to minimize performance impact. Evaluation across various benchmarks and real-world applications demonstrates that Type++ effectively detects and prevents type confusion exploits with a modest runtime overhead, typically under 5%, making it a practical solution for enhancing software security.

  The NDSS paper "Type++: Prohibiting Type Confusion with Inline Type Information" introduces a novel defense mechanism against type confusion vulnerabilities, a prevalent and dangerous class of memory safety bugs. These vulnerabilities arise when a program mistakenly interprets a memory region as belonging to a different type than the one it actually holds, leading to potentially exploitable behavior like arbitrary code execution. Existing solutions often suffer from performance overhead, compatibility issues, or limitations in their scope of protection.

  Type++ addresses these shortcomings by embedding type information directly within objects in memory, enabling runtime checks to verify the consistency between the expected type and the actual type of an object before performing potentially dangerous operations. This "inline type information" is meticulously crafted to minimize performance impact while maximizing security guarantees.

  The core innovation of Type++ lies in its compact representation of type information. It leverages a hierarchical type system, allowing related types to share common information and reducing the overhead of storing redundant data. This hierarchical structure, combined with careful placement of type information relative to the object's data, allows Type++ to maintain type metadata with minimal memory overhead. Furthermore, the design explicitly considers alignment requirements, ensuring that the introduction of type information doesn't inadvertently introduce new vulnerabilities or performance bottlenecks.

  Type++ is implemented through a combination of compiler modifications and runtime library support. The compiler instruments the code to inject checks at strategic locations, primarily before type-dependent operations such as dereferencing pointers and calling virtual functions. These checks compare the expected type, derived from the program's static type system, with the runtime type information embedded within the object. If a mismatch is detected, indicating a potential type confusion vulnerability, the program is safely terminated, preventing exploitation. The runtime library provides functions for managing type information during object creation, destruction, and dynamic type conversions.

  The paper presents a thorough evaluation of Type++ across various benchmarks and real-world applications. The results demonstrate that Type++ effectively detects and prevents a wide range of type confusion vulnerabilities, including those involving C++ classes, virtual functions, and downcasting. Importantly, the performance overhead introduced by Type++ is shown to be relatively low, typically within a few percent, making it practical for deployment in performance-sensitive environments. Furthermore, the authors discuss the compatibility of Type++ with existing codebases, highlighting its ability to be integrated incrementally and without requiring extensive code modifications.

  In conclusion, Type++ offers a robust and efficient defense against type confusion vulnerabilities by leveraging inline type information for runtime verification. Its compact representation, hierarchical type system, and careful consideration of performance and compatibility factors make it a promising solution for improving the security of C++ applications. The paper's evaluation demonstrates its effectiveness in detecting and preventing a broad range of type confusion attacks while incurring minimal performance overhead.

  • C++
  • Type Safety
  • Type Confusion
  • Memory Safety
  • static analysis
  • compiler
  • Programming Languages
  • Software Security
  • Vulnerability Mitigation
  • NDSS
  • Inline Type Information
  • performance
  • Runtime Checks

  Summary of Comments ( 0 )
  https://news.ycombinator.com/item?id=43204796

  Verbose tl;dr

  HN commenters discuss the Type++ paper, generally finding the approach interesting but expressing concerns about performance overhead. Several suggest that a compile-time approach might be preferable, questioning the practicality of runtime checks. Some raise concerns about the complexity of implementation and the potential for bugs within the Type++ system itself. A few highlight the potential benefits for security and catching subtle errors, but the overall sentiment leans towards skepticism regarding the trade-off between safety and performance. The reliance on compiler modifications is also noted as a potential barrier to adoption.

  The Hacker News post titled "Type++: Prohibiting Type Confusion with Inline Type Information [pdf]" has a moderate number of comments discussing the linked PDF, which details a C++ type safety mechanism. Several commenters engage with the core ideas presented in the paper.

  One compelling thread discusses the performance implications of Type++. A commenter points out the potential overhead introduced by the runtime checks required by the system. Another commenter responds, acknowledging the trade-off between safety and performance, and suggesting that the cost might be acceptable in certain contexts, particularly where security is paramount. This exchange highlights a central tension inherent in the proposed solution: increased safety often comes at the expense of performance.

  Another commenter expresses skepticism about the practicality of Type++ for large, existing codebases. They argue that retrofitting Type++ into a complex project could be prohibitively difficult due to the extensive code modifications that would be necessary. This raises a valid concern about the real-world applicability of the research, particularly for established software projects.

  Further discussion centers on the comparison between Type++ and other type safety mechanisms, like Rust's borrow checker. Commenters debate the relative merits and drawbacks of each approach, considering factors like complexity, performance, and ease of use. Some suggest that Rust's approach might be more robust, while others argue that Type++ offers a more gradual path towards improved type safety within the C++ ecosystem.

  One commenter proposes alternative approaches to achieving similar type safety guarantees, such as using fat pointers. This sparks a brief discussion about the trade-offs between different implementation strategies.

  Finally, some commenters delve into the specifics of the Type++ implementation, questioning certain design choices and proposing potential improvements or modifications. This technical discussion demonstrates a deeper engagement with the details of the proposed system.

  Overall, the comments on the Hacker News post reflect a mixture of interest, skepticism, and technical analysis of the Type++ proposal. The discussion highlights both the potential benefits of enhanced type safety in C++ and the challenges associated with implementing and adopting such a system.

• MichiganTypeScript: A WebAssembly runtime implemented in TypeScript types

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  Posted: 2025-02-26 16:26:18

  Verbose tl;dr

  MichiganTypeScript is a proof-of-concept project demonstrating a WebAssembly runtime implemented entirely within TypeScript's type system. It doesn't actually execute WebAssembly code, but instead uses advanced type-level programming techniques to simulate its execution. By representing WebAssembly instructions and memory as types, and leveraging TypeScript's type inference and checking capabilities, the project can statically verify the behavior of a given WebAssembly program. This effectively transforms TypeScript's type checker into an interpreter, showcasing the power and flexibility of its type system, albeit in a non-practical, purely theoretical manner.

  The GitHub repository "MichiganTypeScript/typescript-types-only-wasm-runtime," also known as MichiganTypeScript, presents a novel approach to WebAssembly (Wasm) runtime implementation. Instead of using traditional programming languages like C++, Rust, or JavaScript, this project leverages the TypeScript type system itself to emulate a Wasm runtime environment entirely within the type checker. This means no actual JavaScript code is generated or executed; the entire runtime logic, including loading Wasm modules, executing instructions, managing memory, and handling system calls, is encoded and enforced through complex type definitions and manipulations.

  MichiganTypeScript achieves this by representing Wasm concepts as TypeScript types. For example, Wasm instructions are modeled as type-level functions, memory is represented using tuples, and the stack is simulated using recursive type definitions. The execution of a Wasm program within this system involves a series of intricate type transformations, where the TypeScript compiler effectively "steps through" the program by applying type-level functions that correspond to Wasm instructions. The compiler's type checking mechanism verifies that these transformations are valid according to the defined Wasm semantics.

  The primary objective of this project is not to create a practical, performant Wasm runtime for real-world applications. Instead, it serves as an exploration of the boundaries of TypeScript's type system and a demonstration of its expressive power. By implementing a complex system like a Wasm runtime purely within the type system, the project showcases the potential of using types for advanced static analysis, program verification, and potentially even code generation in the future. While currently limited in terms of the Wasm features it supports and the size of programs it can handle, MichiganTypeScript represents a compelling experiment in pushing the limits of type-driven development. The project highlights the increasing sophistication of type systems in modern programming languages and opens up new avenues for research into leveraging them for tasks traditionally performed by runtime environments.

  • TypeScript
  • WebAssembly
  • Wasm
  • Runtime
  • Type System
  • Types
  • compiler
  • virtual machine
  • javascript
  • Web Development
  • Programming Languages
  • Static Typing
  • MichiganTypeScript

  Summary of Comments ( 5 )
  https://news.ycombinator.com/item?id=43185174

  Verbose tl;dr

  Hacker News users discussed the cleverness of using TypeScript's type system for computation, with several expressing fascination and calling it "amazing" or "brilliant." Some debated the practical applications, acknowledging its limitations while appreciating it as a demonstration of the type system's power. Concerns were raised about debugging complexity and the impracticality for larger programs. Others drew parallels to other Turing-complete type systems and pondered the potential for generating optimized WASM code from such TypeScript code. A few commenters pointed out the project's connection to the "ts-sql" project and speculated about leveraging similar techniques for compile-time query validation and optimization. Several users also highlighted the educational value of the project, showcasing the unexpected capabilities of TypeScript's type system.

  The Hacker News post titled "MichiganTypeScript: A WebAssembly runtime implemented in TypeScript types" sparked a discussion with several interesting comments.

  Many users expressed fascination and amusement at the project, highlighting the ingenuity and absurdity of implementing a Wasm runtime purely within TypeScript's type system. Some saw it as a clever demonstration of the power and flexibility of TypeScript's type system, pushing its boundaries beyond what might be considered practical. Others viewed it more as a playful experiment or a form of esoteric programming.

  One commenter questioned the practical implications of the project, wondering about its potential use cases beyond being a proof of concept. This sparked a small thread discussing the potential for verifying Wasm modules at compile time or exploring new possibilities in type-level computation. However, the general consensus seemed to be that the project's primary value lies in its demonstration of the theoretical possibilities, rather than immediate practical applications.

  Several users pointed out the similarities to other projects that explore the computational capabilities of type systems, particularly within languages like Idris and Haskell. This highlighted the connection between TypeScript's advanced type features and the concepts found in dependently-typed languages.

  There was also some discussion regarding the performance and scalability of such an approach. Some commenters expressed skepticism about the feasibility of using this for real-world Wasm execution, anticipating potential performance bottlenecks.

  A few users highlighted the educational value of the project, suggesting that it could be a useful tool for learning about both TypeScript's type system and the inner workings of Wasm.

  Finally, some comments simply expressed amazement and appreciation for the creativity and technical skill demonstrated by the project's creators. Phrases like "mind-blowing," "absolutely bonkers," and "amazingly pointless" were used to capture the general sentiment of bewildered admiration.

• Gleam, Coming from Erlang

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  Posted: 2025-02-25 07:54:00

  Verbose tl;dr

  The blog post "Gleam, Coming from Erlang" explores the author's experience transitioning from Erlang to Gleam, a newer language built on the Erlang Virtual Machine (BEAM). It highlights Gleam's similarities to Erlang, such as its functional nature, immutability, and the benefits of the BEAM ecosystem like concurrency and fault tolerance. However, the author emphasizes key differences, primarily Gleam's static typing, more approachable syntax inspired by Rust and Elm, and its focus on clearer error messages. While acknowledging some current limitations in tooling and library availability compared to Erlang's mature ecosystem, the post ultimately presents Gleam as a promising alternative for building robust, concurrent applications, particularly for developers coming from other statically-typed languages who might find Erlang's syntax challenging.

  This blog post, titled "Gleam, Coming from Erlang," explores the author's experience transitioning from Erlang to Gleam, a newer language designed to compile to Erlang. The author begins by highlighting their extensive background with Erlang and Elixir, emphasizing a deep appreciation for the Erlang virtual machine (BEAM) and its robust ecosystem. They praise Erlang's fault tolerance, concurrency model, and tooling, establishing these as key features they sought to retain when exploring alternative languages.

  The post then introduces Gleam, characterizing it as a statically-typed language that offers several advantages over Erlang while maintaining compatibility with the BEAM. The author systematically compares and contrasts Gleam with Erlang, focusing on key differences in syntax, type systems, and tooling.

  One significant difference highlighted is Gleam's static typing. The author explains how this contributes to enhanced code clarity, improved error detection during compilation, and better tooling support, like autocompletion and refactoring, compared to Erlang's dynamic typing. They elaborate on how Gleam's type system helps prevent common runtime errors, leading to more robust and maintainable code. Furthermore, they discuss the benefits of improved tooling afforded by static typing, which streamlines the development process.

  The post also details Gleam's syntax, describing it as being influenced by languages like Rust and Elm, which results in a more familiar and arguably more readable syntax for developers coming from those backgrounds. Specific examples are provided to illustrate how Gleam’s syntax differs from Erlang’s, showcasing its arguably cleaner and more concise nature.

  Crucially, the author underscores the interoperability between Gleam and Erlang. They explain how Gleam code can seamlessly integrate with existing Erlang libraries and projects, allowing developers to leverage the vast Erlang ecosystem. This interoperability is presented as a significant advantage, facilitating a gradual adoption of Gleam within existing Erlang projects. The ability to call Erlang code from Gleam and vice-versa is emphasized, allowing for a smooth transition and mixed codebases.

  Finally, the post concludes with the author's positive overall impression of Gleam. They reiterate the benefits of Gleam's static typing and modern syntax while preserving the advantages of the Erlang ecosystem. The author portrays Gleam as a viable option for both new projects targeting the BEAM and for incrementally modernizing existing Erlang projects. They suggest that Gleam offers a compelling blend of modern language features and the proven reliability of the Erlang VM, making it an attractive choice for developers seeking improved developer experience and code maintainability without sacrificing the benefits of the BEAM.

  • Gleam
  • Erlang
  • Functional Programming
  • Static Typing
  • concurrency
  • BEAM
  • compiler
  • Programming Languages
  • Software Development
  • Type Inference
  • Immutability

  Summary of Comments ( 57 )
  https://news.ycombinator.com/item?id=43169323

  Verbose tl;dr

  Hacker News commenters generally expressed interest in Gleam, praising its friendly syntax and the benefits it inherits from the Erlang ecosystem, like the BEAM VM. Some saw it as a potentially strong competitor to Elixir, appreciating its stricter type system and simpler tooling. A few users familiar with Erlang questioned the necessity of Gleam, suggesting that learning Erlang directly might be more worthwhile. Performance comparisons with Elixir and other BEAM languages were also a topic of discussion, with some expressing hope for benchmarks. A recurring sentiment was curiosity about Gleam's potential to attract a larger community and gain wider adoption. Several commenters also appreciated the author's candid comparison between Gleam and Erlang, finding the article helpful for understanding Gleam's niche.

  The Hacker News post titled "Gleam, Coming from Erlang" (https://news.ycombinator.com/item?id=43169323) has generated several comments discussing various aspects of Gleam and its relationship to Erlang.

  Several commenters discuss the benefits of Gleam's type system and its impact on developer experience. One user highlights how Gleam allows for compile-time verification of data structures, reducing runtime errors and enhancing overall code reliability, something they contrast positively with Erlang. Another commenter specifically appreciates the improvements Gleam offers in terms of error messages compared to Erlang, suggesting that this makes it a more approachable language for newcomers. The ability to refactor with greater confidence due to the type system is also mentioned as a significant advantage.

  The discussion also touches upon Gleam's performance characteristics. One commenter wonders about the performance implications of using Gleam compared to pure Erlang. While acknowledging they haven't benchmarked it themselves, they speculate that the overhead might be negligible, especially given that Gleam compiles to Erlang.

  Another thread in the comments focuses on the tooling and ecosystem surrounding Gleam. Users discuss the availability of a formatter and the integration with the Erlang ecosystem, noting that Gleam seamlessly leverages existing Erlang libraries. The relative nascency of the language and its ecosystem is acknowledged, with one user expressing anticipation for further tooling enhancements as the language matures.

  The choice of immutability as a core principle in Gleam is also a subject of discussion. A commenter notes that immutability simplifies reasoning about code, especially in concurrent scenarios, echoing the benefits often associated with functional programming paradigms.

  Finally, the topic of interoperability between Gleam and JavaScript is brought up. One commenter expresses their desire for improved JavaScript interop to facilitate wider adoption and use cases beyond the backend.

  In summary, the comments on Hacker News generally reflect a positive sentiment toward Gleam, praising its type system, Erlang integration, and the benefits it derives from functional programming principles. While acknowledging its relative youth, commenters express optimism about the future development and broader adoption of the language.

• Neut Programming Language

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  Posted: 2025-02-24 01:12:18

  Verbose tl;dr

  Neut is a statically-typed, compiled programming language designed for building reliable and maintainable systems software. It emphasizes simplicity and explicitness through its C-like syntax, minimal built-in features, and focus on compile-time evaluation. Key features include a powerful macro system enabling metaprogramming and code generation, algebraic data types for representing data structures, and built-in support for pattern matching. Neut aims to empower developers to write efficient and predictable code by offering fine-grained control over memory management and avoiding hidden runtime behavior. Its explicit design choices and limited standard library encourage developers to build reusable components tailored to their specific needs, promoting code clarity and long-term maintainability.

  The Neut programming language, as described on its overview page, presents itself as a novel approach to software development, aiming to simplify the creation and maintenance of complex software systems. It achieves this through a core philosophy centered around immutability and relational programming principles, coupled with a unique execution model designed for efficiency and predictable behavior.

  At the heart of Neut lies its immutable data model. All data within a Neut program is immutable, meaning that once a value is created, it cannot be modified. This inherent immutability eliminates a large class of potential bugs related to shared state and side effects, thereby increasing the reliability and predictability of the program's behavior. This contributes to a more straightforward reasoning process during development and debugging.

  Neut embraces a relational programming paradigm, where computation is expressed as relationships between data, rather than as sequences of imperative instructions. This declarative style further enhances code clarity and maintainability, as it focuses on describing what the program should accomplish, rather than how it should achieve it. This approach allows the compiler to optimize execution more effectively, potentially exploiting parallelism and other performance enhancements.

  The language incorporates a novel execution model based on a "pull-based" approach. Instead of explicitly specifying the order of operations, computation is driven by data dependencies. Values are computed only when they are needed, and the system automatically manages the flow of data through the program. This "lazy evaluation" strategy can lead to significant performance gains, particularly in situations where not all computed values are ultimately required. Furthermore, this demand-driven execution model inherently supports parallel processing, as independent computations can be executed concurrently.

  Neut provides built-in support for concurrency and distributed computing, leveraging its immutable data model and pull-based execution to simplify the development of concurrent and distributed applications. The absence of mutable state eliminates the need for complex synchronization mechanisms, such as locks and mutexes, which are often sources of subtle bugs in concurrent programs.

  The language is statically typed, providing compile-time guarantees about the correctness of programs. This static typing helps to prevent a wide range of errors early in the development cycle, leading to more robust and reliable software. Furthermore, the type system can aid in code understanding and refactoring.

  Finally, Neut aims to be interoperable with existing software ecosystems, allowing integration with code written in other languages. This pragmatic approach acknowledges the reality of existing codebases and allows for gradual adoption of Neut in larger projects. This interoperability facilitates the leveraging of existing libraries and tools while benefiting from the advantages provided by Neut's innovative features.

  • Programming Languages
  • neut
  • Functional Programming
  • concatenative programming
  • stack-based languages
  • Esoteric Programming Languages
  • virtual machine
  • bytecode
  • compiler
  • interpreter
  • quine

  Summary of Comments ( 27 )
  https://news.ycombinator.com/item?id=43154883

  Verbose tl;dr

  HN commenters generally express interest in Neut, praising its focus on simplicity, safety, and explicitness. Several highlight the appealing aspects of linear types and the borrow checker, noting similarities to Rust but with a seemingly gentler learning curve. Some question the practical applicability of linear types for larger projects, while others anticipate its usefulness in specific domains like game development or embedded systems. A few commenters express skepticism about the limited standard library and the overall maturity of the project, but the overall tone is positive and curious about the language's potential. Performance, particularly relating to garbage collection or its lack thereof, is a recurring point of discussion, with some wondering about the potential for optimizations given the linear type system.

  The Hacker News post for "Neut Programming Language" (https://news.ycombinator.com/item?id=43154883) has a modest number of comments, sparking a discussion around the language's unique features and potential applications.

  Several commenters focus on Neut's core concept of "neural types," expressing interest in its potential for type-safe neural networks. One commenter highlights the challenge of representing complex neural network architectures within a type system, wondering how Neut handles concepts like skip connections and shared weights. Another commenter draws parallels with other typed functional programming languages used in machine learning, like Dex and F*. They question whether Neut offers significant advantages over these existing solutions.

  The discussion also touches upon the practicalities of using Neut. One commenter inquires about the language's performance characteristics and the availability of debugging tools. Another raises the crucial question of integration with existing machine learning frameworks like TensorFlow or PyTorch. A separate comment expresses skepticism about the overall usefulness of strict typing for neural networks, arguing that the dynamic nature of the field often necessitates flexibility over rigid type safety.

  A few comments delve into specific aspects of Neut's design. One points out the potential benefits of using dependent types for expressing tensor shapes and preventing common errors. Another discusses the implications of Neut's choice of Haskell as its implementation language.

  Overall, the comments reflect a mixture of curiosity, skepticism, and cautious optimism. While some commenters are intrigued by Neut's novel approach to type safety in neural networks, others remain unconvinced of its practical benefits and express concerns about its integration with existing tools and workflows. The limited number of comments, however, prevents a truly in-depth exploration of the language's potential and drawbacks.

• Ask HN: A retrofitted C dialect?

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  Posted: 2025-02-22 08:11:45

  Verbose tl;dr

  The author seeks a C-like language with modern features like generics, modules, and memory safety, while maintaining C's performance and close-to-the-metal nature. They desire a language suitable for systems programming, potentially as a replacement for C in performance-critical applications, but with the added benefits of contemporary language design. They are exploring if such a language already exists or whether retrofitting C would be a more viable approach. Essentially, they want the power and control of C without its inherent pitfalls and limitations.

  The Hacker News post titled "Ask HN: A retrofitted C dialect?" poses a question to the community regarding the potential for and interest in a modernized C dialect. The author expresses a desire for a language that retains the core strengths and philosophies of C, specifically its performance characteristics, low-level control, and predictable behavior. They are seeking a language that would offer improvements in areas where C is known to be deficient or cumbersome, such as memory management. Specifically, the author mentions a desire for automated memory management, possibly through mechanisms like garbage collection or borrow checking, while acknowledging the potential performance impact such features might introduce.

  The author emphasizes the importance of maintaining compatibility with existing C codebases, suggesting that this hypothetical dialect should allow seamless integration with C libraries and potentially even allow the gradual migration of existing C projects to the new dialect. They highlight the current landscape of systems programming languages, noting the existence of alternatives like Rust and Go, but express a preference for a language that adheres more closely to the spirit and syntax of C. The post concludes with an open-ended inquiry, inviting discussion and feedback on the feasibility and desirability of such a language, and asking for opinions on existing projects that may already be attempting to address this need. They are particularly interested in approaches that focus on practical application and minimize theoretical complexity.

  • C
  • programming language
  • dialect
  • retrofitting
  • Software Development
  • compiler
  • parser
  • language design
  • Ask HN
  • Hacker News

  Summary of Comments ( 16 )
  https://news.ycombinator.com/item?id=43137171

  Verbose tl;dr

  The Hacker News comments discuss the practicality and potential benefits of a "retrofitted" C dialect, primarily focusing on memory safety. Some suggest exploring existing options like Zig, Rust, or Odin, which already address many of C's shortcomings. Others express skepticism about the feasibility of such a project, citing the complexity of C's ecosystem and the difficulty of maintaining compatibility while introducing significant changes. A few commenters propose specific improvements, such as optional garbage collection or stricter type checking, but acknowledge the challenges in implementation and adoption. There's a general agreement that memory safety is crucial, but opinions diverge on whether a new dialect or focusing on tooling and better practices within existing C is the best approach. Some also discuss the potential benefits for embedded systems, where C remains dominant.

  The Hacker News post "Ask HN: A retrofitted C dialect?" sparked a discussion with several interesting comments. The original poster was inquiring about the feasibility and potential benefits of creating a C dialect that incorporates modern language features while maintaining compatibility with existing C codebases.

  Several commenters pointed out existing projects that attempt to address similar goals. One commenter mentioned Zig, highlighting its focus on being a simpler and more predictable systems programming language compared to C. They emphasized Zig's compile-time execution capabilities and how they can be used to generate optimized code. Another commenter brought up Beef, a language that transpiles to C, emphasizing its goal of adding higher-level features to C development. C2 was also mentioned as a language attempting to improve on C while remaining close to its core principles.

  A common theme in the discussion revolved around the complexities and potential pitfalls of trying to "fix" C. One commenter argued that many of the perceived problems with C stem from programmers misusing the language rather than inherent flaws in the language itself. They suggested that focusing on better education and tooling might be a more effective approach than creating a new dialect.

  Another commenter questioned the practical benefits of a retrofitted C dialect, arguing that the effort required to create and maintain such a language might outweigh the advantages gained. They also pointed out the challenges of ensuring compatibility with the vast existing C ecosystem.

  Some commenters discussed specific features they would like to see in a modernized C dialect, such as improved memory management, better error handling, and more robust type safety. The discussion also touched upon the trade-offs between performance and safety, with some arguing that C's performance characteristics are a key reason for its continued relevance.

  Overall, the comments reflect a mix of enthusiasm for the potential of a modernized C dialect and skepticism about its practicality. Several existing projects were highlighted as potential solutions, and the discussion explored various technical challenges and design considerations related to creating such a language.

• TinyCompiler: A compiler in a week-end

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  Posted: 2025-02-20 22:02:59

  Verbose tl;dr

  This blog post chronicles the author's weekend project of building a compiler for a simplified C-like language. It walks through the implementation of a lexical analyzer, parser (using recursive descent), and code generator targeting x86-64 assembly. The compiler handles basic arithmetic operations, variable declarations and assignments, if/else statements, and while loops. The post emphasizes simplicity and educational value over performance or completeness, providing a practical example of compiler construction principles in a digestible format. The code is available on GitHub for readers to explore and experiment with.

  This blog post, "TinyCompiler: A compiler in a week-end," chronicles the author's journey in creating a simplified compiler from scratch over a weekend. The primary goal wasn't to build a production-ready tool but rather a practical learning exercise to solidify the author's understanding of compiler construction principles. The compiler targets Monkey, a language inspired by the author's previous Monkey interpreter project. The post meticulously details each stage of the compiler's development, emphasizing clarity and simplicity over optimization or feature completeness.

  The process begins with lexical analysis (lexing), which transforms the raw Monkey source code into a stream of tokens. These tokens represent meaningful units like keywords, identifiers, operators, and punctuation. The author employs regular expressions to recognize these patterns in the input string and generate corresponding token objects. The post includes snippets of C++ code demonstrating the implementation of this lexing process.

  Following lexing, the compiler proceeds to parsing. The parser takes the stream of tokens and organizes them into an Abstract Syntax Tree (AST). This tree-like structure represents the grammatical structure of the source code, making it easier to analyze and manipulate. The author uses a recursive descent parsing technique, writing functions to handle each grammatical rule of the Monkey language. The post explains how the parser combines tokens into higher-level constructs like expressions, statements, and program blocks, mirroring the grammar rules defined for Monkey. Code examples illustrating the recursive nature of the parsing process are provided.

  The final stage covered in the post is code generation. With the AST constructed, the compiler translates it into assembly language for a hypothetical stack-based virtual machine. This process involves traversing the AST and emitting corresponding assembly instructions for each node. The post demonstrates how different AST nodes, representing various language constructs, are converted into equivalent VM instructions. The chosen assembly language targets a simple virtual machine, enabling the author to focus on the core principles of code generation without delving into the complexities of a real-world target architecture. The post includes detailed explanations and C++ code snippets showing how arithmetic expressions, variable assignments, and conditional statements are translated into assembly instructions. The author acknowledges that this simple compiler lacks optimization and error handling features, prioritizing educational value over practical utility. The post concludes by reflecting on the learning experience and offering potential avenues for extending the project further.

  • compiler
  • compiler design
  • Programming Languages
  • parsing
  • lexical analysis
  • Code Generation
  • virtual machine
  • Tutorial
  • DIY
  • weekend project
  • C++

  Summary of Comments ( 58 )
  https://news.ycombinator.com/item?id=43120873

  Verbose tl;dr

  HN users largely praised the TinyCompiler project for its educational value, highlighting its clear code and approachable structure as beneficial for learning compiler construction. Several commenters discussed extending the compiler's functionality, such as adding support for different architectures or optimizing the generated code. Some pointed out similar projects or resources, like the "Let's Build a Compiler" tutorial and the Crafting Interpreters book. A few users questioned the "weekend" claim in the title, believing the project would take significantly longer for a novice to complete. The post also sparked discussion about the practical applications of such a compiler, with some suggesting its use for educational purposes or embedding in resource-constrained environments. Finally, there was some debate about the complexity of the compiler compared to more sophisticated tools like LLVM.

  The Hacker News post "TinyCompiler: A compiler in a week-end" generated a fair amount of discussion, with several commenters sharing their perspectives and experiences related to compiler construction.

  A prevalent theme in the comments is the accessibility and educational value of the project. Many commenters praised the author for creating a simplified yet functional compiler, making the often-daunting task of compiler development more approachable for beginners. Some users shared their personal experiences of using similar projects as a starting point for learning about compilers, emphasizing the importance of hands-on projects in grasping the underlying concepts.

  Several comments delve into technical details, discussing specific aspects of the compiler's implementation, such as the parsing techniques, code generation strategies, and the choice of target language (assembly). Some commenters pointed out potential improvements or alternative approaches, fostering a constructive discussion about compiler design choices. For example, there's discussion around the use of recursive descent parsing and the handling of operator precedence.

  A few comments touch upon the project's scope and limitations. While acknowledging the project's educational merit, some commenters rightly point out that it's a simplified example and doesn't cover the full complexity of real-world compilers. They mention aspects like optimization, error handling, and support for more advanced language features as areas where the tiny compiler differs from production-ready compilers.

  The value of such simplified projects as learning tools is a recurring point of discussion. Commenters argue that focusing on a smaller, manageable project allows beginners to grasp the fundamental principles without being overwhelmed by the intricacies of a full-blown compiler. This sentiment reinforces the project's goal of making compiler development accessible to a wider audience.

  Finally, some comments offer links to related resources, including other compiler tutorials, open-source compiler projects, and books on compiler construction. This further contributes to the educational value of the discussion, providing avenues for those interested in exploring the topic further.

• Svelte 5 is not JavaScript

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  Posted: 2025-02-18 16:29:46

  Verbose tl;dr

  Svelte 5 significantly departs from its JavaScript framework roots by compiling components directly to vanilla JavaScript instructions that manipulate the DOM. This eliminates the virtual DOM diffing process typical of other frameworks, resulting in smaller bundle sizes and potentially faster performance. Instead of a framework mediating interactions, Svelte 5 generates imperative code tailored to each component, directly updating the DOM. This shift allows for optimized updates and reduces runtime overhead, making Svelte 5 applications more akin to handcrafted JavaScript than traditional framework-driven applications. While still using familiar Svelte syntax, the output is now a highly optimized, self-contained JavaScript module.

  The blog post "Svelte 5 is not JavaScript" elaborates on a fundamental shift in the Svelte framework's approach to compiling components. Traditionally, Svelte components, written using a combination of HTML, CSS, and JavaScript, were transformed into vanilla JavaScript code that directly manipulated the DOM during runtime. This compilation process effectively translated the developer-friendly Svelte syntax into browser-executable instructions. However, Svelte 5 introduces a departure from this model by compiling components into a distinct, optimized format that is no longer standard JavaScript.

  This new compilation target, referred to as "Svelte Intermediate Language" or SIL, represents a significant evolution in how Svelte components are processed. Instead of generating JavaScript, the compiler now produces SIL code, which is then interpreted by a small, dedicated runtime. This runtime, specifically designed to understand and execute SIL, efficiently manages updates and interactions within the component. The post highlights that this intermediate representation offers several advantages, including improved performance, reduced bundle size, and enhanced maintainability.

  The move to SIL signifies a strategic decision to prioritize optimization over direct JavaScript output. By utilizing a custom intermediate language, Svelte gains greater control over the execution environment, allowing for finer-grained optimizations that wouldn't be possible with traditional JavaScript compilation. The runtime, being purpose-built for SIL, can efficiently handle the specific instructions generated by the compiler, resulting in faster updates and a smaller overall footprint. Furthermore, this abstraction layer simplifies future improvements and modifications to the framework, as changes to SIL can be implemented without requiring wholesale changes to the JavaScript ecosystem. While the generated output is no longer immediately recognizable as JavaScript, the post emphasizes that the developer experience remains unchanged. Developers continue writing components in the familiar Svelte syntax, and the compiler seamlessly handles the conversion to SIL behind the scenes.

  • svelte
  • Svelte 5
  • javascript
  • Frontend Development
  • Web Development
  • compiler
  • ui framework
  • performance
  • Reactivity
  • Virtual DOM
  • No-Virtual-DOM
  • Compilation
  • Web Components

  Summary of Comments ( 192 )
  https://news.ycombinator.com/item?id=43091596

  Verbose tl;dr

  HN users discuss Svelte 5's compilation strategy, which moves reactivity out of the JavaScript runtime and into compiled code. Several commenters express excitement over the potential performance benefits and smaller bundle sizes, comparing it favorably to React and other frameworks. Some raise concerns about debugging and the implications for the ecosystem, particularly around tooling. A few express skepticism, questioning whether the performance gains are significant enough to warrant the shift and whether Svelte's approach will hinder wider adoption. There's also discussion about the blurring line between frameworks and compilers, and whether Svelte's compiled output still qualifies as JavaScript. The impact on hydration and server-side rendering is also a topic of interest.

  The Hacker News post "Svelte 5 is not JavaScript" (https://news.ycombinator.com/item?id=43091596) sparked a discussion revolving around Svelte's compilation strategy and its implications. Several commenters delve into the nuances of what "not JavaScript" truly means in this context.

  One compelling line of discussion centers around the distinction between Svelte's compiled output and traditional JavaScript frameworks. Commenters point out that while Svelte components are written in a language that resembles JavaScript, the compiler transforms them into highly optimized vanilla JavaScript code. This compiled code, devoid of the Svelte runtime, directly manipulates the DOM, leading to performance gains. The discussion clarifies that the "not JavaScript" claim refers to the runtime execution environment, not the origin of the code. The ultimate deliverable is still JavaScript, but it's a very different kind of JavaScript than what's produced by frameworks like React or Vue.

  Several comments explore the benefits of this compilation approach. Smaller bundle sizes, improved performance, and the potential for better tree-shaking are all highlighted. Commenters explain that by eliminating the runtime, Svelte avoids the overhead associated with virtual DOM diffing and other framework-specific processes. This leaner execution model contributes to faster initial load times and smoother updates.

  Some comments delve into the technical details of Svelte's compilation process. They discuss how Svelte analyzes the component code and generates highly specific DOM manipulation instructions. This tailored approach, in contrast to the more generic nature of virtual DOM diffing, results in more efficient updates.

  Another thread of discussion touches on the implications for developers. Some commenters express appreciation for Svelte's developer experience, highlighting the conciseness and readability of its component syntax. Others raise questions about debugging and tooling, noting the challenges that can arise when working with compiled code. The ability to easily step through and inspect original source code during debugging is mentioned as a potential area for improvement.

  Finally, a few comments compare and contrast Svelte with other frameworks like React, Vue, and Solid.js. The discussion acknowledges the trade-offs associated with each approach. While Svelte's compilation strategy offers performance advantages, the other frameworks may provide benefits in terms of community size, tooling maturity, and ecosystem breadth.

• A Clang regression related to switch statements and inlining

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  Posted: 2025-02-18 12:38:08

  Verbose tl;dr

  A recent Clang optimization introduced in version 17 regressed performance when compiling code containing large switch statements within inlined functions. This regression manifested as significantly increased compile times, sometimes by orders of magnitude, and occasionally resulted in internal compiler errors. The issue stems from Clang's attempt to optimize switch lowering by transforming it into a series of conditional moves based on jump tables. This optimization, while beneficial in some cases, interacts poorly with inlining, exploding the complexity of the generated intermediate representation (IR) when a function with a large switch is inlined multiple times. This ultimately overwhelms the compiler's later optimization passes. A workaround involves disabling the problematic optimization via a compiler flag (-mllvm -switch-to-lookup-table-threshold=0) until a proper fix is implemented in a future Clang release.

  This blog post details a performance regression discovered by the author, Adrian Nicula, in Clang versions 15 and 16 concerning the compilation of C++ code containing large switch statements within inline functions. The issue arises specifically when these switch statements are located inside inline functions that are called repeatedly within a hot loop. Prior to Clang 15, the compiler effectively optimized these scenarios, resulting in efficient code execution. However, in Clang 15 and 16, the optimization strategy changed, leading to a significant performance degradation in specific circumstances.

  The core problem stems from how Clang handles jump tables, a common optimization technique for switch statements. Previously, when an inline function with a large switch was called repeatedly, Clang would generate a single jump table for the switch statement and reuse it across all call sites. This approach minimized code size and maximized performance.

  Beginning with Clang 15, the compiler seemingly changed its inlining heuristics. Instead of creating a single shared jump table, Clang now generates a separate jump table for each instance of the inlined function within the loop. This duplication significantly increases the code size, particularly for large switch statements with numerous cases. The larger code size negatively impacts instruction cache performance, leading to the observed performance regression.

  Nicula demonstrates the issue with a concise example involving a benchmarking program that measures the execution time of code containing a large switch statement within an inline function. He provides performance measurements across different Clang versions, clearly showing the performance drop in versions 15 and 16. The benchmark also highlights that the issue only manifests when the inline function is called a substantial number of times within a loop.

  The author further investigates the generated assembly code, confirming the proliferation of jump tables in Clang 15 and 16 compared to earlier versions. This analysis solidifies the hypothesis that the change in jump table generation is the root cause of the performance problem.

  While Nicula did not pinpoint the exact commit introducing this regression, he suspects it may be related to modifications in Clang's inlining or jump table generation logic around the time of Clang 15's release. The author concludes by recommending users experiencing similar performance issues to revert to Clang 14 or explore compiler flags related to inlining and optimization to potentially mitigate the problem. He also expresses hope that the Clang community will address this regression in future releases.

  • Clang
  • compiler
  • C++
  • C
  • Regression
  • Switch Statement
  • Inlining
  • optimization
  • Code Generation
  • LLVM
  • bug
  • performance

  Summary of Comments ( 2 )
  https://news.ycombinator.com/item?id=43088797

  Verbose tl;dr

  The Hacker News comments discuss a performance regression in Clang involving large switch statements and inlining. Several commenters confirm experiencing similar issues, particularly when compiling large codebases. Some suggest the regression might be related to changes in the inlining heuristics or the way Clang handles jump tables. One commenter points out that using a constexpr hash table for large switches can be a faster alternative. Another suggests profiling and selective inlining as a workaround. The lack of clear identification of the root cause and the potential impact on compile times and performance are highlighted as concerning. Some users express frustration with the frequency of such regressions in Clang.

  The Hacker News post discussing the Clang regression related to switch statements and inlining sparked a conversation revolving primarily around compiler optimization, code generation, and debugging challenges. Several commenters delved into the technical intricacies of the issue.

  One commenter highlighted the complexities involved in compiler optimization, specifically mentioning the difficulty in striking a balance between performance gains and potential code bloat. They pointed out that aggressive inlining, while often beneficial, can sometimes lead to larger binaries and potentially slower execution in certain scenarios, as was seemingly the case with the Clang regression described in the article. This commenter also touched upon the trade-offs compilers must make and how these decisions can sometimes have unforeseen consequences.

  Another commenter focused on the debugging challenges introduced by such optimizations. They argued that overly aggressive inlining can obscure the relationship between the original source code and the generated assembly, making it harder to debug issues. This difficulty stems from the fact that the inlined code is effectively "merged" into the calling function, making it harder to trace back to the original source location when stepping through a debugger.

  The discussion also touched upon the specifics of switch statement optimization. One commenter explained how compilers often transform switch statements into various forms, such as jump tables or binary search trees, depending on the density and distribution of the cases. They suggested that the Clang regression might be related to a suboptimal choice of switch implementation in specific scenarios.

  Furthermore, a commenter mentioned the importance of profiling and benchmarking in identifying and addressing such performance regressions. They emphasized that relying solely on theoretical analysis of code transformations can be misleading and that empirical data is crucial for understanding the actual impact of compiler optimizations.

  Finally, some commenters discussed potential workarounds and suggested exploring compiler flags to fine-tune inlining behavior or to disable specific optimizations. This highlighted the importance of having granular control over the compiler's optimization strategies to mitigate potential performance issues.

  Overall, the comments on Hacker News provided valuable insights into the technical nuances of the Clang regression, focusing on the challenges related to compiler optimization, debugging, and the importance of profiling and benchmarking. The discussion demonstrated a deep understanding of compiler internals and offered practical suggestions for dealing with similar issues.

• Why I'm writing a Scheme implementation in 2025: Async Rust

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  Posted: 2025-02-17 20:30:26

  Verbose tl;dr

  The author is developing a Scheme implementation in async Rust to explore the synergy between the two. They believe Rust's robust tooling, performance, and memory safety, combined with its burgeoning async ecosystem, provide an ideal foundation for a modern Lisp dialect. Async capabilities offer exciting potential for concurrent Scheme programming, especially with features like lightweight tasks and channels. The project aims to leverage Rust's strengths while preserving the elegance and flexibility of Scheme, potentially offering a compelling alternative for both Lisp enthusiasts and Rust developers interested in functional programming.

  In a blog post titled "Why I'm Writing a Scheme Implementation in 2025: Async Rust," author Matthew Plant explains his motivations for embarking on a new Scheme implementation, emphasizing the advantages offered by utilizing asynchronous Rust. Plant, acknowledging the plethora of existing Scheme implementations, articulates that his primary drive isn't solely to create another Scheme, but rather to explore the intersection of Scheme's elegant design and the powerful features of asynchronous Rust. He believes this combination offers a unique opportunity to build a high-performance, concurrent Scheme system tailored for modern computing needs.

  Plant elaborates on the specific benefits of using async Rust. He highlights the language's memory safety features, eliminating concerns about data races and other memory-related bugs that can plague implementations in languages like C. This inherent safety allows for greater focus on the core logic of the Scheme interpreter and runtime, rather than tedious debugging of memory issues. Furthermore, async Rust provides powerful tools for concurrency and parallelism, allowing for efficient handling of asynchronous operations, which are increasingly prevalent in modern applications. This aligns perfectly with Plant's vision of a modern, high-performance Scheme system. He specifically mentions the desire to experiment with concurrent garbage collection, facilitated by async Rust, potentially leading to a more responsive and efficient runtime environment.

  The author discusses previous attempts at achieving similar goals with other languages, acknowledging that projects like CHICKEN Scheme have achieved a high level of performance. However, he argues that leveraging async Rust offers a unique blend of performance, safety, and concurrency features that makes it a particularly compelling choice for this project. He expresses excitement about the prospect of combining Scheme's simplicity and elegance with the robustness and modern capabilities of async Rust. Plant further details his intention to integrate modern tooling, specifically mentioning Language Server Protocol (LSP) support, to enhance the developer experience. This focus on tooling reflects a commitment to creating not only a performant implementation but also a user-friendly development environment.

  Finally, the post concludes with a look towards the future of the project. Plant states his intentions to release the code open-source, encouraging community involvement and contributions. He acknowledges that the project is in its early stages, but expresses optimism about its potential and invites others to join him in exploring the possibilities of a Scheme implementation powered by async Rust. He sees this project as an exciting opportunity to push the boundaries of Scheme implementations and leverage the best of what modern language design has to offer.

  • Scheme
  • Rust
  • Programming Languages
  • Implementation
  • async
  • concurrency
  • compiler
  • interpreter
  • WebAssembly
  • performance
  • Software Development

  Summary of Comments ( 74 )
  https://news.ycombinator.com/item?id=43083017

  Verbose tl;dr

  HN commenters generally expressed interest in the project, finding the combination of Scheme and async Rust intriguing. Several questioned the choice of Rust for performance reasons, arguing that garbage collection makes it a poor fit for truly high-performance async workloads, and suggesting alternatives like C, C++, or even Zig. Some suggested exploring other approaches within the Rust ecosystem, like using a different garbage collector or a stack-allocated scheme. Others praised the project's focus on developer experience and the potential of combining Scheme's expressiveness with Rust's safety features. A few commenters also discussed the challenges of integrating garbage collection with async runtimes and the potential trade-offs involved. The author's responses clarified some of the design choices and acknowledged the performance concerns, indicating they're open to exploring different strategies.

  The Hacker News post discussing the blog post "Why I'm writing a Scheme implementation in 2025: Async Rust" has generated a moderate number of comments, mostly focusing on the author's chosen technology stack and motivations.

  Several commenters express curiosity and interest in the project. One asks about the specific type of Scheme being implemented, questioning whether it's a "full R7RS Scheme" or a smaller subset. This commenter also mentions their own fondness for Scheme's "powerful macro system." Another commenter questions the choice of Rust for garbage collection, citing potential performance challenges. They suggest exploring other languages like Go or Zig, which might offer better performance for this specific task. However, another user counters this point by suggesting that the author likely chose Rust for its memory safety guarantees, even if it means potentially more complex garbage collection implementation.

  A recurring theme in the comments is the perceived complexity of implementing a garbage collector in Rust. Multiple users highlight this as a potentially significant hurdle. One commenter proposes using a tracing garbage collector as a potentially suitable approach. They further elaborate by suggesting that the author could leverage Rust's ownership system to enhance the efficiency of the garbage collector.

  Some commenters delve into more technical aspects of the project. One discusses the possibilities of integration with WebAssembly, specifically using WASI. They propose that such integration could allow the Scheme implementation to run in various environments, widening its potential use cases.

  There's also discussion about the practical applications of this new Scheme implementation. One commenter suggests potential use cases in game development, highlighting Scheme's suitability for scripting and embedded logic.

  Finally, a few comments offer alternative perspectives. One commenter suggests that the author's goal of combining Scheme and async Rust could be achieved by embedding a Lua interpreter instead, arguing that this might be a simpler and more efficient route. Another commenter wonders about the practical benefits of this project, questioning whether the combination of Scheme and async Rust offers significant advantages over existing solutions.

  Overall, the comments reflect a mixture of intrigue, skepticism, and practical advice regarding the author's endeavor. While some express enthusiasm for the project, others raise concerns about the chosen technologies and the project's overall practicality. The discussion revolves primarily around the technical challenges of garbage collection in Rust, the potential benefits and drawbacks of the technology stack, and the possible applications of the resulting Scheme implementation.

• Tiny JITs for a Faster FFI

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  Posted: 2025-02-12 22:20:19

  Verbose tl;dr

  This post explores optimizing Ruby's Foreign Function Interface (FFI) performance by using tiny Just-In-Time (JIT) compilers. The author demonstrates how generating specialized machine code for specific FFI calls can drastically reduce overhead compared to the generic FFI invocation process. They present a proof-of-concept implementation using Rust and inline assembly, showcasing significant speed improvements, especially for repeated calls with the same argument types. While acknowledging limitations and areas for future development, like handling different calling conventions and more complex types, the post concludes that tiny JITs offer a promising path toward a much faster Ruby FFI.

  The blog post "Tiny JITs for a Faster FFI" on Rails at Scale explores the performance challenges of Foreign Function Interfaces (FFIs) and introduces a novel approach using tiny Just-In-Time (JIT) compilers to mitigate these overheads. The author begins by establishing the context of FFIs, describing their role in bridging the gap between different programming languages, specifically highlighting their importance within Ruby on Rails applications for interacting with native extensions often written in C. They emphasize that FFIs are essential for leveraging performance-critical libraries and functionalities not readily available within Ruby's ecosystem.

  The core performance bottleneck with FFIs lies in the "marshaling" process, which involves converting data between the representations used by the two interacting languages. This conversion process can be computationally expensive, especially when dealing with complex data structures or frequent calls across the FFI boundary. The traditional approach to mitigating this overhead involves manually writing specialized C "shim" functions tailored for specific data types and operations. This manual optimization, however, is labor-intensive, error-prone, and difficult to maintain, especially as the complexity of the interaction grows.

  The post proposes a more automated and flexible solution: employing small, specialized JIT compilers to generate these conversion routines dynamically. These "tiny JITs" analyze the required data transformations at runtime and generate optimized machine code specifically designed for the task at hand. This eliminates the need for hand-written shims and allows for more efficient data marshaling. The authors explain their chosen implementation strategy using Rust and its procedural macro capabilities. They leverage Rust's powerful metaprogramming features to generate the necessary code at compile time, resulting in a more performant and maintainable solution.

  The post then delves into the practical application of this approach within the context of a Ruby gem named "fruity". Fruity uses this tiny JIT technique to optimize calls to C functions, demonstrating significant performance improvements in benchmark comparisons against traditional FFI methods. The authors provide concrete examples and performance data to showcase the effectiveness of their approach, emphasizing the substantial reduction in overhead achieved through JIT-generated conversion routines. They also highlight the portability of this technique, mentioning its potential applicability to other language combinations beyond Ruby and C.

  Finally, the post concludes by acknowledging the ongoing nature of the project and outlining future directions for research and development. This includes further exploration of potential optimizations, expanding support for more complex data structures and operations, and investigating the integration of this technique within other FFI frameworks. The authors express optimism about the potential of tiny JITs to significantly improve the performance and usability of FFIs in various programming environments.

  • JIT compilation
  • FFI
  • Foreign Function Interface
  • performance optimization
  • ruby
  • CRuby
  • YJIT
  • MJIT
  • interpreter
  • compiler
  • native code
  • C extensions
  • Dynamic languages
  • Runtime performance

  Summary of Comments ( 109 )
  https://news.ycombinator.com/item?id=43030388

  Verbose tl;dr

  The Hacker News comments on "Tiny JITs for a Faster FFI" express skepticism about the practicality of tiny JITs in real-world scenarios. Several commenters question the performance gains, citing the overhead of the JIT itself and the potential for optimization by the host language's runtime. They argue that a well-optimized native library, or even careful use of the host language's FFI, could often outperform a tiny JIT. One commenter notes the difficulties of debugging and maintaining such a system, and another raises security concerns related to executing untrusted code. The overall sentiment leans towards established optimization techniques rather than introducing a new layer of complexity with a tiny JIT.

  The Hacker News post "Tiny JITs for a Faster FFI" has generated a moderate discussion with several interesting comments. Many of the comments revolve around the trade-offs and nuances of using Just-In-Time (JIT) compilation for Foreign Function Interfaces (FFIs).

  One commenter points out the performance benefits observed when using a simple JIT for Lua's FFI, highlighting a significant speedup. They further discuss the inherent costs associated with traditional FFIs, such as argument marshaling and context switching, which a JIT can mitigate. The commenter's experience adds practical weight to the article's premise.

  Another comment thread delves into the complexities of implementing a truly portable JIT given the variations in Application Binary Interfaces (ABIs) across different operating systems and architectures. This discussion highlights the challenge of creating a "tiny" and efficient JIT compiler that remains universally applicable. One participant suggests focusing on specific, commonly used platforms initially to simplify the development process.

  A separate commenter mentions the potential security implications of JIT compilation, particularly in scenarios involving untrusted code. They emphasize the need for careful consideration of security risks when incorporating JIT techniques into an FFI, especially when dealing with external libraries or user-provided code. This comment serves as a valuable reminder of the security considerations associated with dynamic code generation.

  Another comment discusses the existing use of small JITs in various projects like WebKit, suggesting that the concept presented in the article is not entirely novel. They link to a relevant talk about a register-based virtual machine with a JIT compiler used for JavaScriptCore, providing further context for those interested in existing implementations.

  Some comments briefly touch upon alternative approaches to optimizing FFIs, such as using code generation during build time or employing specialized libraries. While these suggestions are not explored in detail, they offer additional perspectives on addressing FFI performance bottlenecks.

  Finally, one comment questions the necessity of a JIT compiler in some cases, arguing that careful optimization of the FFI itself can often achieve comparable performance gains without the complexity of dynamic code generation. This counterpoint adds balance to the discussion and encourages consideration of alternative optimization strategies.

  Overall, the comments on Hacker News provide valuable insights into the potential benefits, challenges, and trade-offs associated with using tiny JIT compilers for FFIs. They expand upon the article's core ideas by exploring practical experiences, security considerations, existing implementations, and alternative optimization techniques.

• Incremental compilation instantly rebuilds the Zig compiler [video]

  permalink

  Posted: 2025-02-11 19:10:16

  Verbose tl;dr

  This video demonstrates the incredibly fast incremental compilation of the Zig self-hosted compiler. By making a small, seemingly insignificant change to a source file within the compiler's codebase and rebuilding, the video showcases a rebuild time of just around 25 milliseconds. This highlights Zig's efficient build system and its focus on fast iteration times, a key advantage for developer productivity.

  This YouTube clip showcases a significant improvement in the build speed of the Zig compiler through the implementation of incremental compilation. The video demonstrates a rebuild of the compiler itself after a minor code modification, specifically the addition of two characters ("++") to increment a variable. The presenter emphasizes that the entire compiler is being rebuilt, not just a single file or module. He starts a timer before initiating the rebuild command. The rebuild process, leveraging the new incremental compilation feature, completes remarkably quickly, taking just around 0.06 seconds according to the displayed timer. This speed is highlighted as a substantial advancement compared to traditional full rebuilds, which could take considerably longer. The presenter expresses enthusiasm for this achievement, emphasizing the impact on developer productivity and the iterative coding process. The video visually confirms the successful rebuild by running the newly compiled Zig compiler. The demonstration powerfully illustrates the practical benefits of incremental compilation in reducing build times and accelerating the development cycle for the Zig programming language. The video’s focus is narrowly on exhibiting the speed improvement, not explaining the technical details of the incremental compilation implementation.

  • Zig
  • compiler
  • Incremental Compilation
  • Build Systems
  • Build Performance
  • video
  • Demo
  • Programming Languages
  • Software Development
  • performance optimization

  Summary of Comments ( 12 )
  https://news.ycombinator.com/item?id=43016944

  Verbose tl;dr

  Hacker News users generally praised the Zig compiler's fast incremental compilation demonstrated in the video. Several commenters highlighted the impressive speed and how it contributes to a positive developer experience. Some pointed out that while the demo is compelling, real-world project builds with dependencies might not be as instantaneous. Others discussed the potential of Zig's self-hosting capability and build system, comparing it favorably to other languages and build tools. A few users also expressed interest in Zig's memory management and safety features. There was some discussion about the practical limitations of incremental compilation and the importance of understanding its inner workings.

  The Hacker News post titled "Incremental compilation instantly rebuilds the Zig compiler [video]" sparked a discussion with several interesting comments focusing on the impressive speed of Zig's incremental compilation, its potential, and some caveats.

  Several commenters expressed awe at the demonstration in the video, highlighting how quickly the compiler rebuilds after changes. One user called it "insane" and "amazing," emphasizing how this rapid feedback loop could significantly improve developer productivity. The speed was compared favorably to other languages and build systems, with some mentioning their experiences with slower rebuild times in projects using languages like C++.

  The discussion also touched on the technical aspects enabling this speed. Commenters speculated about techniques Zig might be using, such as caching and clever dependency tracking. Some discussed the benefits of Zig being self-hosted, allowing it to leverage its own compiler's efficiency for rebuilding itself. One commenter pointed out the importance of separating the "parsing/checking" phase from the "code generation" phase, potentially allowing for quick rebuilds when only the latter is needed.

  A few users raised points about the video potentially being a "best-case scenario" demonstration. They questioned how well the incremental compilation would perform with larger codebases and more complex changes, suggesting real-world performance might differ. There was also some discussion about the nature of the changes made in the video and how they might be particularly suited to fast recompilation.

  One commenter discussed the importance of considering the "cold" build time (initial compilation) in addition to incremental rebuilds, while acknowledging that fast incremental compilation is still a significant advantage. Another user brought up the idea of "hot reloading," where code changes are reflected instantly without even a recompilation step, wondering about its feasibility in Zig.

  Finally, the discussion branched into comparing Zig with other languages like Rust and Go, discussing their respective build systems and compilation speeds. One comment mentioned the improvements in Rust's compilation times and another praised the "blazing fast" compilation of Go.