Jinfeng Li, Yan Zhang, Jilong Bian, Tiejun Li, Baoying Ma
{"title":"Application of Improved Fault Localization Method to Stereo Matching Software","authors":"Jinfeng Li, Yan Zhang, Jilong Bian, Tiejun Li, Baoying Ma","doi":"10.1109/QRS-C51114.2020.00071","DOIUrl":null,"url":null,"abstract":"If we execute a test case and find a failure in the program, we need to locate the location of the faults, i.e., fault localization. Fault localization is a very costly and time-consuming process. In this paper, an improved spectrum-based fault localization method IOchiai is proposed. According to the execution of passed and failed test cases, we can calculate the suspiciousness score of software element which is the probability of the element contains faults. The passed and failed test cases have different contributions to the calculation of the suspiciousness scores, we divide them into three groups according to different contribution degrees. IOchiai gives higher suspiciousness scores to the element with faults and locates faults faster. Finally, the method proposed in this paper and the traditional spectrum-based fault localization are applied to stereo matching software and found that the method proposed in this paper has stronger fault localization capability.","PeriodicalId":358174,"journal":{"name":"2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QRS-C51114.2020.00071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
If we execute a test case and find a failure in the program, we need to locate the location of the faults, i.e., fault localization. Fault localization is a very costly and time-consuming process. In this paper, an improved spectrum-based fault localization method IOchiai is proposed. According to the execution of passed and failed test cases, we can calculate the suspiciousness score of software element which is the probability of the element contains faults. The passed and failed test cases have different contributions to the calculation of the suspiciousness scores, we divide them into three groups according to different contribution degrees. IOchiai gives higher suspiciousness scores to the element with faults and locates faults faster. Finally, the method proposed in this paper and the traditional spectrum-based fault localization are applied to stereo matching software and found that the method proposed in this paper has stronger fault localization capability.