Lightweight Fault Localization Combining with Fault-Context

Yong Wang, Zhiqiu Huang, Yong Li, Bingwu Fang
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引用次数: 1

Abstract

Lightweight fault localization technique is a popular class of automated approach to assist programmers in debugging, which often outputs an ordered list of program entities sorted based on their likelihood to be the root cause of a set of failures. However, the technique only focus on calculating the association between program entity and failures, and did not consider program entity's fault context may influence the result. A lightweight fault localization based on fault-context was proposed, which combine suspiciousness of program entity and suspiciousness of program entity's fault-context. We conducted an experiment in which our approach was applied to seven benchmark programs. The experimental results show that our approach combining DStar and fault-context can improve absolute ranking with effective rate of 34.8% for 132 faulty versions from the seven benchmark programs. It is worth mentioning that our approach can obtain average improvement of 65.18% for those improved program if those is effective to SFL, and root causes of failures of 7 buggy programs were improved ranking at the top in the fault ranking report.
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结合故障上下文的轻量级故障定位
轻量级故障定位技术是一种流行的自动化方法,用于帮助程序员进行调试,它通常输出一个有序的程序实体列表,该列表基于它们成为一组故障的根本原因的可能性进行排序。然而,该技术只注重计算程序实体与故障之间的关联,而没有考虑程序实体的故障上下文可能对结果的影响。提出了一种基于故障上下文的轻量级故障定位方法,该方法将程序实体的怀疑性与程序实体的故障上下文的怀疑性相结合。我们进行了一个实验,将我们的方法应用于七个基准程序。实验结果表明,将DStar与故障上下文相结合的方法对7个基准程序中的132个错误版本进行绝对排序,有效率为34.8%。值得一提的是,我们的方法在对SFL有效的情况下,改进后的程序平均改进率为65.18%,在故障排名报告中,有7个bug程序的故障根源得到了改善,排名靠前。
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