The Emotional Side of Software Developers in JIRA

2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR) Pub Date : 2016-05-14 DOI:10.1145/2901739.2903505

Marco Ortu, Alessandro Murgia, Giuseppe Destefanis, Parastou Tourani, R. Tonelli, M. Marchesi, Bram Adams

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引用次数: 98

Abstract

ABSTRACTIssue tracking systems store valuable data for testing hy-potheses concerning maintenance, building statistical pre-diction models and (recently) investigating developer affec-tiveness. For the latter, issue tracking systems can be minedto explore developers emotions, sentiments and politeness, affects for short. However, research on affect detection insoftware artefacts is still in its early stage due to the lack ofmanually validated data and tools.In this paper, we contribute to the research of affectson software artefacts by providing a labeling of emotionspresent on issue comments.We manually labeled 2,000 issue comments and 4,000 sen-tences written by developers with emotions such as love,joy, surprise, anger, sadness and fear. Labeled commentsand sentences are linked to software artefacts reported inour previously published dataset (containing more than 1Kprojects, more than 700K issue reports and more than 2million issue comments). The enriched dataset presented inthis paper allows the investigation of the role of affects insoftware development.

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JIRA中软件开发人员的情感面

问题跟踪系统存储有价值的数据，用于测试有关维护的假设，建立统计预测模型和(最近)调查开发人员的影响。对于后者，可以挖掘问题跟踪系统来探索开发人员的情绪、情绪和礼貌，简称影响。然而，由于缺乏人工验证的数据和工具，软件工件的影响检测研究仍处于早期阶段。在本文中，我们通过提供问题评论中存在的情感标签，为影响软件工件的研究做出了贡献。我们手动标记了2000条问题评论和4000个由开发者写的带有爱、喜悦、惊讶、愤怒、悲伤和恐惧等情绪的句子。标记的评论和句子链接到我们之前发布的数据集中报告的软件工件(包含超过1k个项目，超过700K个问题报告和超过200万个问题评论)。本文提供的丰富数据集允许调查影响在软件开发中的作用。

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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2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR)

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