Bench4BL:基于ir的虫虫定位性能的可重复性研究

Jaekwon Lee, Dongsun Kim, Tegawendé F. Bissyandé, Woosung Jung, Yves Le Traon
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引用次数: 59

摘要

近年来,利用信息检索(Information Retrieval, IR)技术,在给出错误报告的情况下,自动定位错误文件,已经显示出良好的效果。然而,文献中丰富的方法与开发人员(甚至是研究社区为补充其他研究方法而采用的基于ir的错误定位(IRBL)的现实形成了鲜明对比。据推测,这种情况是由于缺乏对最先进的方法的全面评估,这些方法提供了对技术实际性能的见解。我们报告了六种最先进的IRBL技术的全面复制研究。本研究不仅将现有研究中使用的对象(旧对象)应用于IRBL技术,还将46个新对象(61431个Java文件和9459个bug报告)应用于IRBL技术。此外,该研究还比较了两种不同的版本匹配(在bug报告和源代码文件之间)策略,以突出一些与性能下降相关的观察结果。我们还改变了测试文件的包含,以研究IRBL技术对测试文件的有效性,或者它的噪声对性能的影响。最后,如果利用了重复的bug报告,我们将评估潜在的性能增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bench4BL: reproducibility study on the performance of IR-based bug localization
In recent years, the use of Information Retrieval (IR) techniques to automate the localization of buggy files, given a bug report, has shown promising results. The abundance of approaches in the literature, however, contrasts with the reality of IR-based bug localization (IRBL) adoption by developers (or even by the research community to complement other research approaches). Presumably, this situation is due to the lack of comprehensive evaluations for state-of-the-art approaches which offer insights into the actual performance of the techniques. We report on a comprehensive reproduction study of six state-of-the-art IRBL techniques. This study applies not only subjects used in existing studies (old subjects) but also 46 new subjects (61,431 Java files and 9,459 bug reports) to the IRBL techniques. In addition, the study compares two different version matching (between bug reports and source code files) strategies to highlight some observations related to performance deterioration. We also vary test file inclusion to investigate the effectiveness of IRBL techniques on test files, or its noise impact on performance. Finally, we assess potential performance gain if duplicate bug reports are leveraged.
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