Well-Typed's blog post introduces Falsify, a new property-based testing tool for Haskell. Falsify shrinks failing test cases by intelligently navigating the type space, aiming for minimal, reproducible examples. Unlike traditional shrinking approaches that operate on the serialized form of a value, Falsify leverages type information to generate simpler values directly within Haskell, often resulting in dramatically smaller and more understandable counterexamples. This type-directed approach allows Falsify to effectively handle complex data structures and custom types, significantly improving the debugging experience for Haskell developers. Furthermore, Falsify's design promotes composability and integration with existing Haskell testing libraries.
Inko is a programming language designed for building reliable and efficient concurrent software. It features a static type system with algebraic data types and pattern matching, aiding in catching errors at compile time. Inko's concurrency model leverages actors and message passing to avoid shared memory and the associated complexities of mutexes and locks. This actor-based approach, coupled with automatic memory management via garbage collection, aims to simplify the development of concurrent programs and reduce the risk of data races and other concurrency bugs. Furthermore, Inko prioritizes performance and offers efficient compilation to native code. The language seeks to provide a practical and robust solution for modern concurrent programming challenges.
Hacker News users discussed Inko's features, drawing comparisons to Rust and Pony. Several commenters expressed interest in the actor model and ownership/borrowing system for concurrency. Some questioned Inko's practicality and adoption potential given the existing competition, while others were curious about its performance characteristics and real-world applications. The garbage collection aspect was a point of contention, with some viewing it as a drawback for performance-critical applications. A few users also mentioned their previous experiences with the language, highlighting both positive and negative aspects. There was general curiosity about the language's maturity and the size of its community.
The blog post "You Need Subtyping" argues that subtyping, despite sometimes being viewed as complex or unnecessary, is a crucial tool for writing flexible and maintainable code. It emphasizes that subtyping allows for writing generic algorithms that operate on a range of related types without needing modification for each specific type. The author illustrates this through examples using shapes and animal sounds, demonstrating how subtyping enables reusable functions that handle different subtypes without explicit type checks. The post further champions subtype polymorphism as a superior alternative to approaches like typeclasses or enums for handling diverse data types, highlighting its ability to gracefully accommodate future type extensions without altering existing code. Ultimately, the author advocates for embracing subtyping as a fundamental concept for building robust and adaptable software systems.
HN users generally disagreed with the premise that subtyping is needed. Several commenters argued that subtyping adds complexity, especially in larger projects, and that its benefits are often overstated. Alternatives like composition and pattern matching were suggested as potentially superior approaches. Some argued that the author conflated subtyping with polymorphism, while others pointed out that the benefits mentioned in the article, like code reuse and extensibility, could be achieved without subtyping. A few commenters discussed the specific example used in the blog post, highlighting its contrived nature and suggesting better alternatives. The overall sentiment was that subtyping is a tool, sometimes useful, but not a necessity.
Shopify developed a new type inference algorithm called interprocedural sparse conditional type propagation (ISCTP) for their Ruby codebase. ISCTP significantly improves the performance of Sorbet, their gradual type checker, by more effectively propagating type information across method boundaries and within conditional branches. This addresses the common issue of "union types" exploding in complexity when analyzing code with many branching paths. By selectively tracking only relevant type refinements within each branch, ISCTP dramatically reduces the amount of computation required, resulting in faster type checking and fewer false positives. This improvement enables Shopify to scale their type checking efforts across their large and dynamic Ruby on Rails application.
HN commenters generally expressed interest in Sorbet's type system and its performance improvements. Some questioned the practical impact of these optimizations for most users and the tradeoffs involved. One commenter highlighted the importance of constant propagation and the challenges of scaling static analysis, while another compared Sorbet's approach to similar features in other typed languages. There was also a discussion regarding the specifics of Sorbet's implementation, including its handling of runtime type checks and the implications for performance. A few users expressed curiosity about the "sparse" aspect and how it contributes to the overall efficiency of the system. Finally, one comment pointed out the potential for this optimization to significantly improve code analysis tools and IDE features.
The author explores several programming language design ideas centered around improving developer experience and code clarity. They propose a system for automatically managing borrowed references with implicit borrowing and optional explicit lifetimes, aiming to simplify memory management. Additionally, they suggest enhancing type inference and allowing for more flexible function signatures by enabling optional and named arguments with default values, along with improved error messages for type mismatches. Finally, they discuss the possibility of incorporating traits similar to Rust but with a focus on runtime behavior and reflection, potentially enabling more dynamic code generation and introspection.
Hacker News users generally reacted positively to the author's programming language ideas. Several commenters appreciated the focus on simplicity and the exploration of alternative approaches to common language features. The discussion centered on the trade-offs between conciseness, readability, and performance. Some expressed skepticism about the practicality of certain proposals, particularly the elimination of loops and reliance on recursion, citing potential performance issues. Others questioned the proposed module system's reliance on global mutable state. Despite some reservations, the overall sentiment leaned towards encouragement and interest in seeing further development of these ideas. Several commenters suggested exploring existing languages like Factor and Joy, which share some similarities with the author's vision.
This proposal introduces an effect system to C2x, aiming to enhance code modularity, optimization, and correctness by explicitly declaring and checking the side effects of functions. It defines a set of effect keywords, like reads and writes, to annotate function parameters and return values, indicating how they are accessed. These annotations are part of the function's type and are checked by the compiler, ensuring that declared effects match the function's actual behavior. The proposal also includes a mechanism for polymorphism over effects, enabling more flexible code reuse and separate compilation without sacrificing effect safety. This mechanism allows for abstracting over effects, so that functions can be written generically to operate on data structures with varying levels of mutability.
The Hacker News comments on the C2y effect system proposal express a mix of skepticism and cautious interest. Several commenters question the practicality and performance implications of implementing such a system in C, citing the language's existing complexity and the potential for significant overhead. Concerns are raised about the learning curve for developers and the possibility of introducing subtle bugs. Some find the proposal intriguing from a research perspective but doubt its widespread adoption. A few express interest in exploring the potential benefits of improved code analysis and error detection, particularly for concurrency and memory management, though acknowledge the challenges involved. Overall, the consensus leans towards viewing the proposal as an interesting academic exercise with limited real-world applicability in its current form.
Summary of Comments ( 17 )
https://news.ycombinator.com/item?id=43746017
Hacker News users discussed Falsify's approach to property-based testing, praising its clever use of type information and noting its potential advantages over traditional shrinking methods. Some commenters expressed interest in similar tools for other languages, while others questioned the performance implications of its Haskell implementation. Several pointed out the connection to Hedgehog's shrinking approach, highlighting Falsify's type-driven refinements. The overall sentiment was positive, with many expressing excitement about the potential improvements Falsify could bring to property-based testing workflows. A few commenters also discussed specific examples and potential use cases, showcasing practical applications of the library.
The Hacker News post about Falsify, a hypothesis-inspired shrinking for Haskell, has generated a moderate amount of discussion with several interesting comments.
Several users expressed interest and appreciation for the approach Falsify takes. One user highlighted the benefits of property-based testing and how Falsify improves upon existing shrinking methods by targeting smaller, simpler counterexamples. They pointed out how this can significantly reduce debugging time and improve overall testing efficiency.
Another commenter drew a parallel to property-based testing in other languages, mentioning Hypothesis for Python. They discussed how effective these techniques are for uncovering subtle bugs that would be difficult to find through traditional testing methods. They also expressed excitement for the potential of Falsify to advance property-based testing within the Haskell ecosystem.
One user focused on the explanation of "rose trees" in the context of shrinking. They appreciated the clear explanation provided in the blog post and linked Falsify's approach to related concepts in QuickCheck. They suggested that this approach could have broader applications in other areas beyond property-based testing.
There was a discussion about the challenges of shrinking complex data structures, with one commenter noting the difficulties involved in shrinking recursive data types. They expressed interest in how Falsify handles these complexities and how it compares to other shrinking strategies.
A few users touched upon the importance of good generators in property-based testing. They emphasized that while shrinking is important, having well-defined generators that produce relevant test cases is equally crucial for effective testing. They inquired about Falsify's approach to generating test data and how it interacts with the shrinking process.
Finally, one commenter raised the question of how Falsify handles type-level constraints in Haskell. They wondered if the shrinking process takes these constraints into account to ensure that generated counterexamples are always valid.
Overall, the comments on the Hacker News post reflect a positive reception to Falsify and acknowledge its potential to enhance property-based testing in Haskell. The discussion highlights the importance of shrinking in finding minimal counterexamples, the challenges involved in shrinking complex data, and the crucial role of well-defined generators in the property-based testing process.