Effectiveness of code contribution: from patch-based to pull-request-based tools

Jiaxin Zhu, Minghui Zhou, A. Mockus
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引用次数: 46

Abstract

Code contributions in Free/Libre and Open Source Software projects are controlled to maintain high-quality of software. Alternatives to patch-based code contribution tools such as mailing lists and issue trackers have been developed with the pull request systems being the most visible and widely available on GitHub. Is the code contribution process more effective with pull request systems? To answer that, we quantify the effectiveness via the rates contributions are accepted and ignored, via the time until the first response and final resolution and via the numbers of contributions. To control for the latent variables, our study includes a project that migrated from an issue tracker to the GitHub pull request system and a comparison between projects using mailing lists and pull request systems. Our results show pull request systems to be associated with reduced review times and larger numbers of contributions. However, not all the comparisons indicate substantially better accept or ignore rates in pull request systems. These variations may be most simply explained by the differences in contribution practices the projects employ and may be less affected by the type of tool. Our results clarify the importance of understanding the role of tools in effective management of the broad network of potential contributors and may lead to strategies and practices making the code contribution more satisfying and efficient from both contributors' and maintainers' perspectives.
代码贡献的有效性:从基于补丁的工具到基于拉取请求的工具
免费/自由和开源软件项目中的代码贡献受到控制,以保持软件的高质量。基于补丁的代码贡献工具(如邮件列表和问题跟踪器)的替代方案已经开发出来,其中拉请求系统是GitHub上最可见和最广泛可用的。使用拉取请求系统,代码贡献过程是否更有效?为了回答这个问题,我们通过贡献被接受和忽略的比率、通过第一次响应和最终解决的时间以及通过贡献的数量来量化有效性。为了控制潜在变量,我们的研究包括一个从问题跟踪器迁移到GitHub拉请求系统的项目,以及使用邮件列表和拉请求系统的项目之间的比较。我们的结果显示,拉取请求系统与减少的审查时间和更多的贡献相关联。然而,并不是所有的比较都表明在拉取请求系统中接受或忽略率更好。这些变化可能最简单地解释为项目所采用的贡献实践的差异,并且可能受工具类型的影响较小。我们的结果阐明了理解工具在有效管理潜在贡献者的广泛网络中的作用的重要性,并且可能导致从贡献者和维护者的角度来看,使代码贡献更令人满意和有效的策略和实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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