What Makes a Good TODO Comment?

IF 6.6 2区 计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING ACM Transactions on Software Engineering and Methodology Pub Date : 2024-05-13 DOI:10.1145/3664811
Haoye Wang, Zhipeng Gao, Tingting Bi, John Grundy, Xinyu Wang, Minghui Wu, Xiaohu Yang
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Abstract

Software development is a collaborative process that involves various interactions among individuals and teams. TODO comments in source code play a critical role in managing and coordinating diverse tasks during this process. However, this study finds that a large proportion of open-source project TODO comments are left unresolved or take a long time to be resolved. About 46.7% of TODO comments in open-source repositories are of low-quality (e.g., TODOs that are ambiguous, lack information, or are useless to developers). This highlights the need for better TODO practices. In this study, we investigate four aspects regarding the quality of TODO comments in open-source projects: (1) the prevalence of low-quality TODO comments; (2) the key characteristics of high-quality TODO comments; (3) how are TODO comments of different quality managed in practice; and (4) the feasibility of automatically assessing TODO comment quality. Examining 2,863 TODO comments from Top100 GitHub Java repositories, we propose criteria to identify high-quality TODO comments and provide insights into their optimal composition. We discuss the lifecycle of TODO comments with varying quality. To assist developers, we construct deep learning-based methods that show promising performance in identifying the quality of TODO comments, potentially enhancing development efficiency and code quality.

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怎样才能写好 TODO 评论?
软件开发是一个协作过程,涉及个人和团队之间的各种互动。在这一过程中,源代码中的 TODO 注释在管理和协调各种任务方面发挥着至关重要的作用。然而,本研究发现,很大一部分开源项目的 TODO 注释都没有得到解决或需要很长时间才能解决。开源资源库中约有 46.7% 的 TODO 注释质量不高(例如,TODO 含糊不清、缺乏信息或对开发人员毫无用处)。这凸显了改善 TODO 实践的必要性。在本研究中,我们从四个方面调查了开源项目中 TODO 注释的质量:(1) 低质量 TODO 注释的普遍性;(2) 高质量 TODO 注释的主要特征;(3) 不同质量的 TODO 注释在实践中是如何管理的;(4) 自动评估 TODO 注释质量的可行性。通过研究 GitHub Java 库 Top100 中的 2,863 条 TODO 注释,我们提出了识别高质量 TODO 注释的标准,并对其最佳构成提出了见解。我们讨论了不同质量的 TODO 注释的生命周期。为了帮助开发人员,我们构建了基于深度学习的方法,这些方法在识别 TODO 注释质量方面表现出良好的性能,有望提高开发效率和代码质量。
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来源期刊
ACM Transactions on Software Engineering and Methodology
ACM Transactions on Software Engineering and Methodology 工程技术-计算机:软件工程
CiteScore
6.30
自引率
4.50%
发文量
164
审稿时长
>12 weeks
期刊介绍: Designing and building a large, complex software system is a tremendous challenge. ACM Transactions on Software Engineering and Methodology (TOSEM) publishes papers on all aspects of that challenge: specification, design, development and maintenance. It covers tools and methodologies, languages, data structures, and algorithms. TOSEM also reports on successful efforts, noting practical lessons that can be scaled and transferred to other projects, and often looks at applications of innovative technologies. The tone is scholarly but readable; the content is worthy of study; the presentation is effective.
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