理解开发人员社区对软件文档的情绪

Akhila Sri Manasa Venigalla, S. Chimalakonda
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引用次数: 11

摘要

开源项目的可用性促进了开发人员在广泛的项目上贡献和协作。因此,为这类开源项目做出贡献的开发人员社区也在增加。许多项目涉及频繁的更新和广泛的重用。更新良好的文档有助于更好地理解软件项目,并促进有效的贡献和重用。尽管软件文档在软件的开发和维护中起着重要的作用,但它也面临着各种问题,包括不足、不一致、可维护性差等。探索开发人员对文档的看法可以帮助理解软件文档中普遍问题背后的原因。它可以进一步帮助决定可以向开发人员社区提供的培训,以便为社会建立更可持续的项目。分析项目贡献者的情绪可以提供理解开发人员看法的见解。因此,作为迈向这个方向的第一步,我们分析特定于软件项目文档的提交消息的情绪。为此,我们考虑了来自GHTorrent数据集的998个GitHub项目的提交历史,并确定了10,996个与存储库文档对应的提交。此外,我们应用情感分析技术来深入了解所选提交的提交消息中表达的情感类型。我们观察到,大约45%的已识别的提交信息表达了信任情绪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding Emotions of Developer Community Towards Software Documentation
The availability of open-source projects facilitates developers to contribute and collaborate on a wide range of projects. As a result, the developer community contributing to such open-source projects is also increasing. Many of the projects involve frequent updates and extensive reuses. A well-updated documentation helps in a better understanding of the software project and also facilitates efficient contribution and reuse. Though software documentation plays an important role in the development and maintenance of software, it also suffers from various issues that include insufficiency, inconsistency, ill-maintainability, and so on. Exploring the perception of developers towards documentation could help in understanding the reasons behind prevalent issues in software documentation. It could further aid in deciding on training that could be given to the developer community towards building more sustainable projects for society. Analyzing sentiments of contributors to a project could provide insights on understanding developer perceptions. Hence, as the first step towards this direction, we analyze sentiments of commit messages specific to the documentation of a software project. To this end, we considered the commit history of 998 GitHub projects from the GHTorrent dataset and identified 10,996 commits that correspond to the documentation of repositories. Further, we apply sentiment analysis techniques to obtain insights on the type of sentiment being expressed in commit messages of the selected commits. We observe that around 45% of the identified commit messages express trust emotion.
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