RAPTOR:发布意识和优先修复bug的任务分配优化

Yutaro Kashiwa
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引用次数: 3

摘要

十多年来,为了帮助开发人员阅读每天提交的大量错误报告,并分配合适的开发人员,提出了许多错误分配方法。然而,他们倾向于将任务集中在少数特定的开发人员身上。将这些方法应用于已经发布的项目将减少开发人员在下一个发布日期之前可以修复的bug的数量,因为开发人员用于修复bug的时间是有限的。在本研究中,我们提出了基于版本的bug修复任务分配方法,以减轻任务集中度,并增加开发人员在下一个发布日期之前可以修复的bug数量。这种方法使用数学编程在项目级别上找到最佳组合,而传统方法在个人级别上找到bug和开发人员的最佳组合。
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RAPTOR: Release-Aware and Prioritized Bug-Fixing Task Assignment Optimization
Over a decade, many bug assignment methods have been proposed in order to assist developers to read bug reports submitted daily and numerously, and to assign an appropriate developer. However, they tend to concentrate their assignments on a small number of particular developers. Applying the methods to the projects which have releases would reduce the number of bugs that developers can fix by the next release date because the time that developers can devote to bug-fixing is limited. In this study, we propose the release-aware bug-fixing task assignment method to mitigate the task concentration and increase the number of bugs that developers can fix by the next release date. This method employs mathematical programming to find the best combination at project level while the traditional methods find the best pair of a bug and a developer (at individual level).
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