"Less Slow C++" offers practical advice for improving C++ build and execution speed. It covers techniques ranging from precompiled headers and unity builds (combining source files) to link-time optimization (LTO) and profile-guided optimization (PGO). It also explores build system optimizations like using Ninja and parallelizing builds, and coding practices that minimize recompilation such as avoiding unnecessary header inclusions and using forward declarations. Finally, the guide touches upon utilizing tools like compiler caches (ccache) and build analysis utilities to pinpoint bottlenecks and further accelerate the development process. The focus is on readily applicable methods that can significantly improve C++ project turnaround times.
While often derided for its verbosity and perceived outdatedness, Objective-C possesses a unique charm for some developers. Its Smalltalk-inspired message-passing paradigm, dynamic nature, and human-readable syntax foster a sense of playfulness and expressiveness that can be missing in more rigid languages. This article argues that Objective-C's idiosyncrasies, including its use of square brackets and descriptive method names, contribute to a more approachable and understandable coding experience, particularly for those coming from a less technical background. Despite its decline in popularity since Swift's arrival, Objective-C's enduring legacy and distinct character continue to resonate with a dedicated community who appreciate its subjective appeal.
HN commenters largely agree that Objective-C's verbosity, while initially appearing cumbersome, contributes to its readability and maintainability. Several users appreciate the explicit nature of message passing and how it clarifies code intention. Some argue that modern Objective-C, with features like literals and blocks, addresses many of the verbosity complaints. The dynamic nature of the language and the power of its runtime are also highlighted as benefits. A few commenters express nostalgia for Objective-C, contrasting it with Swift, which they perceive as less enjoyable or flexible, despite its modern syntax. There's also a discussion around the challenges of learning Objective-C and the impact of Apple's transition to Swift.
The Go Optimization Guide at goperf.dev provides a practical, structured approach to optimizing Go programs. It covers the entire optimization process, from benchmarking and profiling to understanding performance characteristics and applying targeted optimizations. The guide emphasizes data-driven decisions using benchmarks and profiling tools like pprof and highlights common performance bottlenecks in areas like memory allocation, garbage collection, and inefficient algorithms. It also delves into specific techniques like using optimized data structures, minimizing allocations, and leveraging concurrency effectively. The guide isn't a simple list of tips, but rather a comprehensive resource that equips developers with the methodology and knowledge to systematically improve the performance of their Go code.
Hacker News users generally praised the Go Optimization Guide linked in the post, calling it "excellent," "well-written," and a "great resource." Several commenters highlighted the guide's practicality, appreciating the clear explanations and real-world examples demonstrating performance improvements. Some pointed out specific sections they found particularly helpful, like the advice on using sync.Pool and understanding escape analysis. A few users offered additional tips and resources related to Go performance, including links to profiling tools and blog posts. The discussion also touched on the nuances of benchmarking and the importance of considering optimization trade-offs.
This post advocates for using Ruby's built-in features like Struct and immutable data structures (via freeze) to create simple, efficient value objects. It argues against using more complex approaches like dry-struct or Virtus for basic cases, highlighting that the lightweight, idiomatic approach often provides sufficient functionality with minimal overhead. The article illustrates how Struct provides concise syntax for defining attributes and automatic equality and hashing based on those attributes, fulfilling the core requirements of value objects. Finally, it demonstrates how to enforce immutability by freezing instances, ensuring predictable behavior and preventing unintended side effects.
HN users largely criticized the article for misusing or misunderstanding the term "Value Object." Commenters pointed out that true Value Objects are immutable and compared by value, not identity. They argued that the article's examples, particularly using mutable hashes and relying on equal?, were not representative of Value Objects and promoted bad practices. Several users suggested alternative approaches like using Struct or creating immutable classes with custom equality methods. The discussion also touched on the performance implications of immutable objects in Ruby and the nuances of defining equality for more complex objects. Some commenters felt the title was misleading, promoting a non-idiomatic approach.
Steve Losh's "Teach, Don't Tell" advocates for a more effective approach to conveying technical information, particularly in programming tutorials. Instead of simply listing steps ("telling"), he encourages explaining the why behind each action, empowering learners to adapt and solve future problems independently. This involves revealing the author's thought process, exploring alternative approaches, and highlighting potential pitfalls. By focusing on the underlying principles and rationale, tutorials become less about rote memorization and more about fostering genuine understanding and problem-solving skills.
Hacker News users generally agreed with the "teach, don't tell" philosophy for giving feedback, particularly in programming. Several commenters shared anecdotes about its effectiveness in mentoring and code reviews, highlighting the benefits of guiding someone to a solution rather than simply providing it. Some discussed the importance of patience and understanding the learner's perspective. One compelling comment pointed out the subtle difference between explaining how to do something versus why it should be done a certain way, emphasizing the latter as key to fostering true understanding. Another cautioned against taking the principle to an extreme, noting that sometimes directly telling is the most efficient approach. A few commenters also appreciated the article's emphasis on avoiding assumptions about the learner's knowledge.
"Effective Rust (2024)" aims to be a comprehensive guide for writing robust, idiomatic, and performant Rust code. It covers a wide range of topics, from foundational concepts like ownership, borrowing, and lifetimes, to advanced techniques involving concurrency, error handling, and asynchronous programming. The book emphasizes practical application and best practices, equipping readers with the knowledge to navigate common pitfalls and write production-ready software. It's designed to benefit both newcomers seeking a solid understanding of Rust's core principles and experienced developers looking to refine their skills and deepen their understanding of the language's nuances. The book will be structured around specific problems and their solutions, focusing on practical examples and actionable advice.
HN commenters generally praise "Effective Rust" as a valuable resource, particularly for those already familiar with Rust's basics. Several highlight its focus on practical advice and idioms, contrasting it favorably with the more theoretical "Rust for Rustaceans." Some suggest it bridges the gap between introductory and advanced resources, offering actionable guidance for writing idiomatic, production-ready code. A few comments mention specific chapters they found particularly helpful, such as those covering error handling and unsafe code. One commenter notes the importance of reading the book alongside the official Rust documentation. The free availability of the book online is also lauded.
Summary of Comments ( 18 )
https://news.ycombinator.com/item?id=43727743
Hacker News users discussed the practicality and potential benefits of the "less_slow.cpp" guidelines. Some questioned the emphasis on micro-optimizations, arguing that focusing on algorithmic efficiency and proper data structures is generally more impactful. Others pointed out that the advice seemed tailored for very specific scenarios, like competitive programming or high-frequency trading, where every ounce of performance matters. A few commenters appreciated the compilation of optimization techniques, finding them valuable for niche situations, while some expressed concern that blindly applying these suggestions could lead to less readable and maintainable code. Several users also debated the validity of certain recommendations, like avoiding virtual functions or minimizing branching, citing potential trade-offs with code design and flexibility.
The Hacker News post titled "Less Slow C++" (https://news.ycombinator.com/item?id=43727743) sparked a discussion with a moderate number of comments, largely focusing on the practicality and nuances of the advice offered in the linked GitHub repository.
Several commenters appreciated the author's effort to collect and present performance optimization tips. One user highlighted the value in consolidating such information, especially for those newer to C++, acknowledging that while experienced developers might be familiar with many of the tips, having them readily available in one place is beneficial.
However, a recurring theme in the comments was the caution against premature optimization. Multiple users emphasized that focusing on code clarity and correctness should precede optimization efforts. They argued that optimizing without proper profiling and understanding of actual bottlenecks can be counterproductive, leading to more complex code without significant performance gains. One commenter even suggested the title should be "Faster C++," as "Less Slow" implies a focus on fixing slowness rather than writing efficient code from the start.
Some commenters delved into specific points from the GitHub document. There was discussion around the use of
std::vectorversusstd::array, pointing out thatstd::arrayis often preferable for small, fixed-size collections due to its avoidance of heap allocation. Another discussion centered on the advice to avoid exceptions, with some agreeing on their performance overhead, especially when thrown frequently, while others argued that exceptions are crucial for error handling and shouldn't be dismissed solely for performance reasons.The topic of inlining also garnered attention. While the GitHub document recommends strategic use of inlining, some commenters elaborated on the compiler's role in inlining decisions. They highlighted that modern compilers are often better at determining which functions to inline, making explicit inlining less necessary and sometimes even detrimental.
Finally, a few commenters shared their own experiences and preferred optimization techniques, adding further depth to the conversation. One mentioned the importance of considering data locality and cache efficiency for performance-critical code.
Overall, the comments section provides a balanced perspective on C++ optimization. While acknowledging the usefulness of the compiled tips, the discussion emphasizes the importance of careful profiling, prioritizing code readability, and understanding the trade-offs involved in different optimization strategies. It serves as a reminder that blindly applying performance tweaks without proper consideration can often do more harm than good.