理解开发者情绪对修复诱导变更的影响:对GitHub拉取请求的探索性研究

Syed Fatiul Huq, Ali Zafar Sadiq, K. Sakib
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引用次数: 14

摘要

在软件开发环境中,开发人员的情绪或情绪有可能影响性能,从而影响软件本身。情感分析用于分析在线协作工件,可以得出开发人员情感的影响。本研究旨在通过分析常规更改和修复诱导更改(Fix-Inducing Changes, FIC)之间的情绪差异,了解开发人员的情绪与bug之间的关系。为了做到这一点,情感是从6个著名的GitHub存储库的Pull Requests中提取出来的,其中包含代码和贡献者的讨论。情感是使用专门用于软件工程领域的工具来计算的:SentiStrength-SE。接下来,从提交中检测fic,方法是过滤修复了错误的fic,并跟踪这些错误删除的代码的来源。提交基于fic进行分类,并根据不同的先前工件(来自拉取请求的提交、评论和评论)分配单独的情感分数(-4到+4)。统计结果表明,与常规提交相比,fic包含了更多积极的Comments和Reviews。在FIC之前的提交有更多的负面消息。类似地,与常规提交相比,所有的Pull Request工件组合起来对fic更不利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding the Effect of Developer Sentiment on Fix-Inducing Changes: An Exploratory Study on GitHub Pull Requests
Developer emotion or sentiment in a software development environment has the potential to affect performance, and consequently, the software itself. Sentiment analysis, conducted to analyze online collaborative artifacts, can derive effects of developer sentiment. This study aims to understand how developer sentiment is related to bugs, by analyzing the difference of sentiment between regular and Fix-Inducing Changes (FIC) - changes to code that introduce bugs in the system. To do so, sentiment is extracted from Pull Requests of 6 well known GitHub repositories, which contain both code and contributor discussion. Sentiment is calculated using a tool specializing in the software engineering domain: SentiStrength-SE. Next, FICs are detected from Commits by filtering the ones that fix bugs and tracking the origin of the code these remove. Commits are categorized based on FICs and assigned separate sentiment scores (-4 to +4) based on different preceding artifacts - Commits, Comments and Reviews from Pull Requests. The statistical result shows that FICs, compared to regular Commits, contain more positive Comments and Reviews. Commits that precede an FIC have more negative messages. Similarly, all the Pull Request artifacts combined are more negative for FICs than regular Commits.
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