{"title":"HOTFUZ: Cost‐effective higher‐order mutation‐based fault localization","authors":"Jong-In Jang, Duksan Ryu, Jong-Chan Baik","doi":"10.1002/stvr.1802","DOIUrl":null,"url":null,"abstract":"Fault localization techniques are used to deduce the exact source of a failure from a set of failure indications while debugging software and play a crucial role in improving software quality. Mutation‐based fault localization (MBFL) techniques are proposed to localize faults at a finer granularity and with higher accuracy than traditional fault localization techniques. Despite the technique's effectiveness, the immense cost of mutation analysis hinders MBFL's practical application in the industry. Various mutation alternative strategies are utilized to lower the cost of MBFL, but they sacrifice the accuracy of localization results. Higher‐order mutation testing was proposed to search for valuable mutants that drive testing harder and reduce the overall test effort. However, higher‐order mutants (HOMs) never have been used to address the cost problem of MBFL to the extent of our knowledge. This paper proposes a novel, cost‐effective MBFL technique called HOTFUZ, Higher‐Order muTation‐based FaUlt localiZation, that employs HOMs to reduce the cost while minimizing the accuracy degradation. HOTFUZ combines mutants of a program under test into HOMs to decrease the number of mutants by more than half, depending on the order of HOMs. An experimental study is conducted using 65 real‐world faults of CoREBench to assess the proposed approach's cost‐effectiveness. The experimental results show that HOTFUZ outperforms the extant mutation alternative strategies by localizing faults more accurately using the same number of mutants executed. HOTFUZ has three main benefits over existing mutant reduction techniques for MBFL: (a) It keeps the advantage of using the whole set of mutation operators; (b) it does not discard generated mutants randomly for the sake of efficiency; and, finally, (c) it significantly decreases the proportion of equivalent mutants.","PeriodicalId":49506,"journal":{"name":"Software Testing Verification & Reliability","volume":"70 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Testing Verification & Reliability","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1002/stvr.1802","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 3
Abstract
Fault localization techniques are used to deduce the exact source of a failure from a set of failure indications while debugging software and play a crucial role in improving software quality. Mutation‐based fault localization (MBFL) techniques are proposed to localize faults at a finer granularity and with higher accuracy than traditional fault localization techniques. Despite the technique's effectiveness, the immense cost of mutation analysis hinders MBFL's practical application in the industry. Various mutation alternative strategies are utilized to lower the cost of MBFL, but they sacrifice the accuracy of localization results. Higher‐order mutation testing was proposed to search for valuable mutants that drive testing harder and reduce the overall test effort. However, higher‐order mutants (HOMs) never have been used to address the cost problem of MBFL to the extent of our knowledge. This paper proposes a novel, cost‐effective MBFL technique called HOTFUZ, Higher‐Order muTation‐based FaUlt localiZation, that employs HOMs to reduce the cost while minimizing the accuracy degradation. HOTFUZ combines mutants of a program under test into HOMs to decrease the number of mutants by more than half, depending on the order of HOMs. An experimental study is conducted using 65 real‐world faults of CoREBench to assess the proposed approach's cost‐effectiveness. The experimental results show that HOTFUZ outperforms the extant mutation alternative strategies by localizing faults more accurately using the same number of mutants executed. HOTFUZ has three main benefits over existing mutant reduction techniques for MBFL: (a) It keeps the advantage of using the whole set of mutation operators; (b) it does not discard generated mutants randomly for the sake of efficiency; and, finally, (c) it significantly decreases the proportion of equivalent mutants.
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