[期刊第一]MSeer -一种并行定位多个bug的先进技术

Ruizhi Gao, E. Wong
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引用次数: 47

摘要

实际上,一个程序可能包含多个错误。这些错误的同时存在可能会降低现有错误定位技术定位程序错误的有效性。虽然使用所有失败和成功的测试来识别只有一个错误的程序的可疑代码是可以接受的,但对于有多个错误的程序使用相同的方法是不合适的,因为失败的测试和潜在的错误之间的因果关系不容易识别。一种解决方案是通过将由相同错误引起的失败测试分组到相同的集群中来生成以故障为中心的集群。我们提出了MSeer -一种先进的故障定位技术,用于并行定位多个错误。我们的主要贡献包括使用(1)修订的Kendall tau距离来测量两个失败测试之间的距离,(2)一种创新的方法来同时估计聚类的数量并为这些聚类分配初始介质,以及(3)改进的k -介质聚类算法来更好地识别失败测试与其相应错误之间的因果关系。对7个程序的840个多错误版本的案例研究表明,MSeer在并行定位多个错误方面的有效性和效率优于其他两种技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Journal First] MSeer – An Advanced Technique for Locating Multiple Bugs in Parallel
In practice, a program may contain multiple bugs. The simultaneous presence of these bugs may deteriorate the effectiveness of existing fault-localization techniques to locate program bugs. While it is acceptable to use all failed and successful tests to identify suspicious code for programs with exactly one bug, it is not appropriate to use the same approach for programs with multiple bugs because the due-to relationship between failed tests and underlying bugs cannot be easily identified. One solution is to generate fault-focused clusters by grouping failed tests caused by the same bug into the same clusters. We propose MSeer - an advanced fault localization technique for locating multiple bugs in parallel. Our major contributions include the use of (1) a revised Kendall tau distance to measure the distance between two failed tests, (2) an innovative approach to simultaneously estimate the number of clusters and assign initial medoids to these clusters, and (3) an improved K-medoids clustering algorithm to better identify the due-to relationship between failed tests and their corresponding bugs. Case studies on 840 multiple-bug versions of seven programs suggest that MSeer performs better in terms of effectiveness and efficiency than two other techniques for locating multiple bugs in parallel.
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