使用基于时间的Git数据的陷阱和指南
Pitfalls and Guidelines for Using Time-Based Git Data
摘要：
许多软件工程研究论文依赖于基于时间的数据（例如，提交时间戳、问题报告创建/更新/关闭日期、发布日期）。然而，像大多数真实世界的数据一样，基于时间的数据通常是脏的。到目前为止，还没有研究来量化软件工程研究社区使用这些数据的频率，或者调查这些数据的来源并量化这些数据是脏数据的频率。根据研究任务和使用的方法，包括这些脏数据可能会影响研究结果。本文介绍了一个扩展的调查论文，利用基于时间的数据，发表在采矿软件库（MSR）会议系列。在MSR 2004- 2021发表的754篇技术跟踪和数据论文中，我们看到至少有290篇（38%）论文使用了基于时间的数据。我们还观察到，研究论文中使用的大多数基于时间的数据都是以Git提交的形式出现的，通常来自GitHub。基于这些结果，我们使用Boa和Software Heritage基础设施来帮助识别和量化几个脏Git时间戳数据的来源。最后，我们为研究人员利用Git存储库中基于时间的数据提供了指导方针/最佳实践。
英文摘要：
Many software engineering research papers rely on time-based data (e.g., commit timestamps, issue report creation/update/close dates, release dates). Like most real-world data however, time-based data is often dirty. To date, there are no studies that quantify how frequently such data is used by the software engineering research community, or investigate sources of and quantify how often such data is dirty. Depending on the research task and method used, including such dirty data could affect the research results. This paper presents an extended survey of papers that utilize time-based data, published in the Mining Software Repositories (MSR) conference series. Out of the 754 technical track and data papers published in MSR 2004--2021, we saw at least 290 (38%) papers utilized time-based data. We also observed that most time-based data used in research papers comes in the form of Git commits, often from GitHub. Based on those results, we then used the Boa and Software Heritage infrastructures to help identify and quantify several sources of dirty Git timestamp data. Finally we provide guidelines/best practices for researchers utilizing time-based data from Git repositories.
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