基于贝叶斯网络的Bug报告质量与修复时间分析

Sien Reeve Ordonez Peralta, H. Washizaki, Y. Fukazawa, Yuki Noyori, Shuhei Nojiri, Hideyuki Kanuka
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引用次数: 0

摘要

大多数客户端软件采用错误跟踪系统,该系统利用用户提交的报告(错误报告),其中包含软件开发人员修复错误所需的信息。bug报告的质量差别很大。Bug报告可以包括严重性、优先级,以及通过研究所解决的Bug确定的相关问题。本文研究了bug报告质量对成功修复bug和估计修复时间的影响。我们还检查了先前研究中的说法,即由于报告者的广泛专业知识,在处理错误报告方面存在偏见和差异。我们的方法检查了bug修复周期内的质量之间的关系,并通过贝叶斯网络建模图形因果关系。带有附件的Bug报告、对另一个Bug的依赖以及频繁的讨论更有可能得到修复。此外,具有高严重性的bug报告往往修复得更快。此外,错误本身的困难程度可能会影响修复速度,因此,无论错误报告的质量如何,简单的错误都会更容易更快地修复。
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Analysis of Bug Report Qualities with Fixing Time using a Bayesian Network
Most client software employs a bug-tracking system, which utilizes user-submitted reports (bug reports) that contain information necessary for software developers to fix bugs. The quality of bug reports drastically differs. Bug reports can include severity, priority, and associated issues determined by researching the addressed bug. Herein we investigate the influence of bug report qualities on successfully fixing a bug and estimating the fixing time. We also examine the claim in previous studies that bias and differences in the treatment of bug reports exist due to broad expertness among the reporters. Our approach examines the relationship between the qualities within the bug-fixing cycle and modeling graphical causal dependencies through a Bayesian Network. Bug reports with attachments, dependencies on another bug, and frequent discussions are more likely to be fixed. In addition, bug reports with a high severity tend to be fixed faster. Moreover, the difficulty of the bug itself may influence the fixing rate such that a straightforward bug will be fixed easier and faster regardless of the bug report quality.
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