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CGT-FL: using cooperative game theory to effective fault localization in presence of coincidental correctness
Empirical Software Engineering ( IF 3.5 ) Pub Date : 2020-08-17 , DOI: 10.1007/s10664-020-09859-y
Farid Feyzi

In this article we emphasize that most of the faults, appearing in real-world programs, are complicated and there exists a high interaction between faulty and other correlated statements, that is likely to cause coincidental correctness in many cases. To effectively diminish the negative impact of coincidentally correct tests on localization effectiveness, we suggest analyzing the combinatorial effect of program statements on the failure. To this end, we develop a new framework, CGT-FL, for evaluation and ranking program statements in a manner that statements which have strong discriminatory power as a group but are weak as individuals could be identified. The framework firstly evaluates the interactivity degree of each statement according to its influence on the intricate interrelation among statements by a Shapley value-based cooperative game-theoretic method. Then, statements are selected in a forward way by considering both interactivity and relevance measures. To verify the effectiveness of CGT-FL, we provide the results of our extensive experiments with different subject programs, containing seeded and real faults. The experimental results are then compared with those provided by different fault localization techniques for both single-fault and multiple-fault programs. The results prove the outperformance of CGT-FL compared to state-of-the-art techniques.

中文翻译:

CGT-FL:在存在巧合正确性的情况下,使用合作博弈论进行有效的故障定位

在本文中,我们强调,在现实世界的程序中出现的大多数错误都是复杂的,并且错误与其他相关语句之间存在高度交互,这在许多情况下很可能导致巧合正确性。为了有效减少巧合正确测试对定位有效性的负面影响,我们建议分析程序语句对失败的组合影响。为此,我们开发了一个新的框架,CGT-FL,用于评估和排名程序语句,以便可以识别作为一个群体具有很强歧视能力但作为个体弱的陈述。该框架首先通过基于沙普利值的合作博弈论方法,根据每个语句对语句之间错综复杂的相互关系的影响来评估每个语句的交互程度。然后,通过考虑交互性和相关性度量以正向方式选择语句。为了验证 CGT-FL 的有效性,我们提供了对不同主题程序进行广泛实验的结果,其中包含种子错误和真实错误。然后将实验结果与针对单故障和多故障程序的不同故障定位技术提供的结果进行比较。结果证明,与最先进的技术相比,CGT-FL 的性能更胜一筹。为了验证 CGT-FL 的有效性,我们提供了对不同主题程序进行广泛实验的结果,其中包含种子错误和真实错误。然后将实验结果与针对单故障和多故障程序的不同故障定位技术提供的结果进行比较。结果证明,与最先进的技术相比,CGT-FL 的性能更胜一筹。为了验证 CGT-FL 的有效性,我们提供了对不同主题程序进行广泛实验的结果,其中包含种子错误和真实错误。然后将实验结果与针对单故障和多故障程序的不同故障定位技术提供的结果进行比较。结果证明,与最先进的技术相比,CGT-FL 的性能更胜一筹。
更新日期:2020-08-17
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