研究大模型时代代码可读性，发现自动生成代码与人工编写相当。
Code Readability in the Age of Large Language Models: An Industrial Case Study from Atlassian
- 通过对比大模型生成与人工代码，评估可读性表现。
- 生成代码可读性接近人工水平，信任度高。
- 适合关注大模型开发工具落地的工程师和管理者。
软件工程师在开发过程中花费大量时间阅读代码，尤其在大语言模型（LLMs）能自动产生代码的背景下。然而，目前对大模型生成代码的可读性及其在实践者眼中的重要性仍知之甚少。本文通过调查探索了从业者对大模型时代代码可读性的看法，并通过真实场景中对比我们的基于大模型的开发代理框架HULA生成的代码与人工编写的代码，研究其可读性。总体发现表明：(1) 可读性仍是软件开发的关键因素；(2) 我们的模型生成代码的可读性与人工编写代码相当，有助于建立合理信任，推动我们大模型驱动的开发平台广泛应用。
原文摘要 · Abstract (English)
Software engineers spend a significant amount of time reading code during the software development process, especially in the age of large language models (LLMs) that can automatically generate code. However, little is known about the readability of the LLM-generated code and whether it is still important from practitioners' perspectives in this new era. In this paper, we conduct a survey to explore the practitioners' perspectives on code readability in the age of LLMs and investigate the readability of our LLM-based software development agents framework, HULA, by comparing its generated code with human-written code in real-world scenarios. Overall, the findings underscore that (1) readability remains a critical aspect of software development; (2) the readability of our LLM-generated code is comparable to human-written code, fostering the establishment of appropriate trust and driving the broad adoption of our LLM-powered software development platform.
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