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Sentiment Analysis in monitoring software development processes: An exploratory case study on GitHub's project issues

机译:监控软件开发过程中的情感分析:关于GitHub项目问题的探索性案例研究

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摘要

Software process models, which allow us to develop software products, can be improved by using the corresponding quality model. However, current tendencies in the application of Global Software Engineering and Global Software Development, which forces geographically dispersed teams to collaborate, make the usual monitoring techniques obsolete. This situation has led to looking for new methods that can help in the decision making process, such as the case of the Social Network Analysis field. In this article we propose the introduction of Sentiment Analysis techniques in order to identify and monitor the underlying sentiments in the text written by developers in issues and tickets. Therefore, in order to check its viability we conducted an exploratory case study analysing polarity and emotional clues in development issues from nine well-known projects that are freely available. Results show that although both polarity and emotional analysis are applicable, the emotional analysis looks to be more suitable to this kind of corpus. The developers leave underlying sentiments in the text, and that information could be monitored as any other feature in the development process.
机译:通过使用相应的质量模型,可以改进允许我们开发软件产品的软件过程模型。但是,当前全球软件工程和全球软件开发的应用趋势迫使地理上分散的团队进行协作,从而使通常的监视技术过时了。这种情况导致寻找新的方法来帮助决策过程,例如“社交网络分析”领域。在本文中,我们建议引入情绪分析技术,以识别和监视开发人员在问题和故障单中编写的文本中的基本情绪。因此,为了检查其可行性,我们进行了一项探索性案例研究,分析了免费提供的九个知名项目在发展问题中的极性和情感线索。结果表明,尽管极性分析和情绪分析都适用,但情绪分析看起来更适合这种语料库。开发人员在文本中保留了潜在的情感,并且该信息可以像开发过程中的任何其他功能一样受到监视。

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