{"title":"MutantBench:一个等效的突变问题比较框架","authors":"Lars van Hijfte, Ana Oprescu","doi":"10.1109/ICSTW52544.2021.00015","DOIUrl":null,"url":null,"abstract":"The Equivalent Mutant Problem is an ongoing research problem that led to the creation of multiple reusable non-standardized mutant datasets. However, cross-study evaluation is still tedious. To tackle this problem, we propose MutantBench, a novel open-source comparison framework that is designed with a focus on the FAIR data principles and adoptability by the community. With this, tools within the Equivalent Mutant Problem can be empirically evaluated using the same dataset which then allows for improved cross-study evaluation. We also combine existing datasets resulting in a mutant dataset containing 4400 mutants with 1416 equivalent mutants. This increases the previously largest mutant dataset by more than a thousand equivalent mutants.","PeriodicalId":371680,"journal":{"name":"2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"MutantBench: an Equivalent Mutant Problem Comparison Framework\",\"authors\":\"Lars van Hijfte, Ana Oprescu\",\"doi\":\"10.1109/ICSTW52544.2021.00015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Equivalent Mutant Problem is an ongoing research problem that led to the creation of multiple reusable non-standardized mutant datasets. However, cross-study evaluation is still tedious. To tackle this problem, we propose MutantBench, a novel open-source comparison framework that is designed with a focus on the FAIR data principles and adoptability by the community. With this, tools within the Equivalent Mutant Problem can be empirically evaluated using the same dataset which then allows for improved cross-study evaluation. We also combine existing datasets resulting in a mutant dataset containing 4400 mutants with 1416 equivalent mutants. This increases the previously largest mutant dataset by more than a thousand equivalent mutants.\",\"PeriodicalId\":371680,\"journal\":{\"name\":\"2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSTW52544.2021.00015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSTW52544.2021.00015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MutantBench: an Equivalent Mutant Problem Comparison Framework
The Equivalent Mutant Problem is an ongoing research problem that led to the creation of multiple reusable non-standardized mutant datasets. However, cross-study evaluation is still tedious. To tackle this problem, we propose MutantBench, a novel open-source comparison framework that is designed with a focus on the FAIR data principles and adoptability by the community. With this, tools within the Equivalent Mutant Problem can be empirically evaluated using the same dataset which then allows for improved cross-study evaluation. We also combine existing datasets resulting in a mutant dataset containing 4400 mutants with 1416 equivalent mutants. This increases the previously largest mutant dataset by more than a thousand equivalent mutants.