一种基于主题模型和开发者关系的Bug自动分类的开发者排名算法

Zhang Tao, Geunseok Yang, Byungjeong Lee, E. Lua
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引用次数: 37

摘要

最近,错误解决已经成为软件维护的一个关键问题,其中推荐合适的修复程序是一项重要任务。有些方法(例如,社交网络和机器学习技术)可以实现自动错误分类(例如,开发者推荐)。本文提出了一种新的方法来推荐最合适的修复程序来解决错误。与以前的方法不同,所提出的方法结合了主题模型和开发人员关系(例如,Bug报告者和受让人)来捕捉开发人员对特定Bug报告的兴趣和经验,我们可以安排最合适的开发人员来修复新Bug。我们使用三个大型开源项目(包括Eclipse、Mozilla firefox和Net beans)来评估我们方法的性能。实验结果表明,我们的方法优于其他开发人员推荐方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Developer Ranking Algorithm for Automatic Bug Triage Using Topic Model and Developer Relations
Recently, bug resolution has become a pivotal issue for software maintenance where recommendations for appropriate fixers are an important task. Some approaches (e.g., Social network and machine learning techniques) exist that can achieve automatic bug triage (i.e., Developer recommendation). This paper proposes a new method to recommend the most suitable fixer for bug resolution. Different from previous approaches, the proposed approaches combine topic model and developer relations (e.g., Bug reporter and assignee) to capture developers' interest and experience on specific bug reports, we can arrange for the most appropriate developer to fix a new bug when it comes in. We evaluate the performance of our method using three large-scale open-source projects, including Eclipse, Mozilla Fire fox, and Net beans. The experimental results reveal that our approach outperforms other recommendation methods for developers.
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