Do Bug-Fix Types Affect Spectrum-Based Fault Localization Algorithms' Efficiency?

2020 IEEE Workshop on Validation, Analysis and Evolution of Software Tests (VST) Pub Date : 2020-02-01 DOI:10.1109/VST50071.2020.9051638

Attila Szatmári, Béla Vancsics, Árpád Beszédes

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引用次数: 4

Abstract

Finding a bug in the software is an expensive task, however, debugging is a crucial part of the software development life cycle. Spectrum-Based Fault Localization (SBFL) algorithms can reduce the time spent with debugging. Despite the fact that SBFL is a very well researched topic, there are not many tools that implement it. Many studies have dealt with the effectiveness of SBFL algorithms, although these have been evaluated on Java and C++ programming languages. We performed an empirical study on JavaScript programs (using BugsJS benchmark) to evaluate the relationship between algorithms efficiency and the bug-fix types. First we implemented three popular SBFL approaches, i.e. Tarantula, Ochiai and DStar, then examined whether there was a correlation/connection between the positions of the faulty methods in the suspiciousness ranks and bug-fix types. Results show that certain bug-fix types can be significantly differentiated from the others (in both positive and negative direction) based on the fault localization effectiveness of the investigated algorithms.

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错误修复类型会影响基于频谱的故障定位算法的效率吗?

查找软件中的错误是一项昂贵的任务，然而，调试是软件开发生命周期的关键部分。基于频谱的故障定位(SBFL)算法可以减少调试时间。尽管SBFL是一个研究得很好的主题，但实现它的工具并不多。许多研究已经处理了sffl算法的有效性，尽管这些算法已经在Java和c++编程语言上进行了评估。我们对JavaScript程序进行了实证研究(使用BugsJS基准)，以评估算法效率与bug修复类型之间的关系。首先，我们实施了三种流行的SBFL方法，即Tarantula, Ochiai和DStar，然后检验了错误方法在可疑等级中的位置与错误修复类型之间是否存在相关性/联系。结果表明，基于所研究算法的故障定位有效性，某些错误修复类型可以与其他错误修复类型(正反方向)显著区分。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2020 IEEE Workshop on Validation, Analysis and Evolution of Software Tests (VST)

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