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A critical evaluation of spectrum-based fault localization techniques on a large-scale software system

机译:基于频谱的故障定位技术在大型软件系统中的重要评估

摘要

In the past, spectrum-based fault localization (SBFL) techniques have been developed to pinpoint a fault location in a program given a set of failing and successful test executions. Most of the algorithms use similarity coefficients and have only been evaluated on established but small benchmark programs from the Software-artifact Infrastructure Repository (SIR). In this paper, we evaluate the feasibility of applying 33 state-of-the-art SBFL techniques to a large real-world project, namely ASPECTJ. From an initial set of 350 faulty version from the iBugs repository of ASPECTJ we manually classified 88 bugs where SBFL techniques are suitable. Notably, only 11 bugs of these bugs can be found after examining the 1000 most suspicious lines and on average 250 source code files need to be inspected per bug. Based on these results, the study showcases the limitations of current SBFL techniques on a larger program.
机译:过去,已经开发了基于频谱的故障定位(SBFL)技术,以在给定一组失败和成功的测试执行的情况下,精确定位程序中的故障位置。大多数算法使用相似系数,并且仅在软件工件基础结构存储库(SIR)中已建立但规模较小的基准程序上进行了评估。在本文中,我们评估了将33种最先进的SBFL技术应用于大型现实项目ASPECTJ的可行性。从ASPECTJ的iBugs存储库中最初的350个错误版本集中,我们手动分类了88个适合SBFL技术的错误。值得注意的是,在检查了1000条最可疑的行之后,只能发现其中11个错误,每个错误平均需要检查250个源代码文件。基于这些结果,该研究在更大的程序上展示了当前SBFL技术的局限性。

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