敏捷软件开发
计算机科学
人气
过程(计算)
万维网
软件
跟踪(教育)
跟踪系统
数据科学
软件工程
人工智能
卡尔曼滤波器
程序设计语言
操作系统
心理学
社会心理学
教育学
作者
Marco Ortu,Giuseppe Destefanis,Bram Adams,Alessandro Murgia,Michele Marchesi,Roberto Tonelli
标识
DOI:10.1145/2810146.2810147
摘要
Issue tracking systems store valuable data for testing hypotheses concerning maintenance, building statistical prediction models and recently investigating developers "affectiveness". In particular, the Jira Issue Tracking System is a proprietary tracking system that has gained a tremendous popularity in the last years and offers unique features like the project management system and the Jira agile kanban board. This paper presents a dataset extracted from the Jira ITS of four popular open source ecosystems (as well as the tools and infrastructure used for extraction) the Apache Software Foundation, Spring, JBoss and CodeHaus communities. Our dataset hosts more than 1K projects, containing more than 700K issue reports and more than 2 million issue comments. Using this data, we have been able to deeply study the communication process among developers, and how this aspect affects the development process. Furthermore, comments posted by developers contain not only technical information, but also valuable information about sentiments and emotions. Since sentiment analysis and human aspects in software engineering are gaining more and more importance in the last years, with this repository we would like to encourage further studies in this direction.
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