{"title":"Lightweight Fault Localization Combining with Fault-Context","authors":"Yong Wang, Zhiqiu Huang, Yong Li, Bingwu Fang","doi":"10.1109/SATE.2016.23","DOIUrl":null,"url":null,"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.","PeriodicalId":344531,"journal":{"name":"2016 International Conference on Software Analysis, Testing and Evolution (SATE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Software Analysis, Testing and Evolution (SATE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SATE.2016.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.