The blog post "What makes code hard to read: Visual patterns of complexity" explores how visual patterns in code impact readability, arguing that complexity isn't solely about logic but also visual structure. It identifies several patterns that hinder readability: deep nesting (excessive indentation), wide lines forcing horizontal scrolling, fragmented logic scattered across the screen, and inconsistent indentation disrupting vertical scanning. The author advocates for writing "calm" code, characterized by shallow nesting, narrow code blocks, localized logic, and consistent formatting, allowing developers to quickly grasp the overall structure and flow of the code. The post uses Python examples to illustrate these patterns and demonstrates how refactoring can significantly improve visual clarity, even without altering functionality.
The blog post, "What makes code hard to read: Visual patterns of complexity (2023)" by Felienne Hermans, explores the concept of code readability through the lens of visual patterns, arguing that the visual layout of code significantly impacts its comprehensibility. Hermans posits that while traditional code analysis often focuses on abstract syntax trees, the visual representation experienced by programmers plays a crucial role in how easily they can understand and process the code. This visual aspect, she argues, hasn't been sufficiently explored in research.
The post introduces the concept of "visual debt" – analogous to technical debt – which accumulates when code becomes visually complex and difficult to parse. This visual debt, Hermans suggests, arises from specific visual patterns that emerge in code structure. She then meticulously details several of these patterns, illustrating them with clear examples and contrasting them with cleaner alternatives.
One such pattern is the "staircase," characterized by deeply nested code blocks that create a diagonal visual flow. This diagonal movement forces the reader's eye to jump across the screen, making it difficult to follow the logic. Hermans emphasizes the importance of minimizing nesting and keeping code blocks shallow to avoid this pattern.
Another problematic pattern highlighted is the "semaphore," which occurs when multiple lines of code share similar prefixes, mimicking the visual appearance of semaphore flags. This similarity can lead to confusion and make it challenging to differentiate between individual lines. The post recommends refactoring such code to eliminate redundant prefixes, thus improving clarity.
Hermans also discusses the "cliff," referring to long lines of code that force the reader to scroll horizontally. This horizontal movement disrupts the natural vertical reading flow and can hide important details. She advocates for keeping lines within a reasonable length to avoid this visual obstacle.
The "pit" pattern describes visually dense code blocks with minimal whitespace, making it challenging to identify individual elements and understand their relationships. Hermans emphasizes the importance of strategic whitespace to separate logical units and improve visual parsing. She demonstrates how proper indentation and blank lines can dramatically increase readability.
The post concludes by suggesting that awareness of these visual patterns can help developers write more readable code. By consciously avoiding patterns like the staircase, semaphore, cliff, and pit, programmers can reduce visual debt and improve the overall maintainability and comprehensibility of their codebases. Hermans encourages further research and discussion in this area to develop more comprehensive tools and techniques for assessing and improving code readability from a visual perspective. She ultimately champions a more holistic approach to code quality that considers not just the logical structure but also the visual experience of reading and understanding code.
Summary of Comments ( 272 )
https://news.ycombinator.com/item?id=43330900
HN commenters largely agree with the article's premise that visual complexity hinders code readability. Several highlight the importance of consistency in formatting and indentation, noting how deviations create visual noise that distracts from the code's logic. Some discuss specific patterns mentioned in the article, like deep nesting and arrow anti-patterns, offering personal anecdotes and suggesting mitigation strategies like extracting functions or using guard clauses. Others expand on the article's points by mentioning the cognitive load imposed by inconsistent naming conventions and the helpfulness of visual aids like syntax highlighting and code folding. A few commenters offer alternative perspectives, arguing that while visual complexity can be a symptom of deeper issues, it isn't the root cause of hard-to-read code. They emphasize the importance of clear logic and good design over purely visual aspects. There's also discussion around the subjective nature of code readability and the challenge of defining objective metrics for it.
The Hacker News post titled "What makes code hard to read: Visual patterns of complexity (2023)" linking to an article on seeinglogic.com has generated a moderate number of comments, many of which engage thoughtfully with the article's premise.
Several commenters agree with the article's focus on visual patterns as a key factor in code readability. One commenter points out that the article effectively highlights how "jagged" code, characterized by inconsistent indentation and irregular line lengths, significantly impacts readability and can make it difficult to parse the code's structure at a glance. They emphasize that even with syntactically correct code, these visual inconsistencies can introduce cognitive overhead.
Another commenter echoes this sentiment, adding that the article resonates with their own experience. They mention struggling with codebases that lack visual consistency and appreciate the article's clear articulation of this often overlooked aspect of code quality. They further suggest that tools that help enforce consistent visual patterns, such as linters and formatters, can be invaluable in improving maintainability and reducing cognitive load.
Some commenters delve deeper into the specific visual patterns discussed in the article. One commenter discusses the concept of "arrow anti-patterns," where deeply nested conditional logic creates a visual "arrow" shape in the code, making it difficult to follow the flow of execution. They agree with the article's recommendation of refactoring such code to flatten the structure and improve readability.
Another commenter brings up the importance of vertical density and how excessively long blocks of code without sufficient whitespace can hinder readability. They concur with the article's suggestion of breaking down large blocks into smaller, more manageable chunks to enhance visual clarity. They also suggest the judicious use of comments to further guide the reader's understanding.
A few commenters offer additional perspectives beyond the scope of the article. One commenter suggests that while visual patterns are important, cognitive complexity also plays a significant role in code readability. They argue that code with complex logic, even if visually well-structured, can still be challenging to understand. Another commenter mentions the role of domain knowledge and how familiarity with the problem domain can significantly impact one's ability to comprehend the code.
While there is general agreement on the importance of visual patterns in code readability, one commenter expresses a slightly dissenting view, arguing that excessive focus on visual aesthetics can sometimes come at the expense of functionality. They suggest that prioritizing clear and concise logic should be the primary goal, with visual patterns playing a secondary role.
Overall, the comments on the Hacker News post generally endorse the article's focus on visual readability patterns and provide further insights and perspectives on the topic. The discussion highlights the importance of visual consistency, the impact of specific anti-patterns, and the relationship between visual structure and cognitive complexity. While some nuances and alternative viewpoints are presented, the overall sentiment reinforces the value of considering visual patterns when striving for readable and maintainable code.