Gunel Jahangirova, D. Clark, M. Harman, P. Tonella
{"title":"OASIs: oracle assessment and improvement tool","authors":"Gunel Jahangirova, D. Clark, M. Harman, P. Tonella","doi":"10.1145/3213846.3229503","DOIUrl":null,"url":null,"abstract":"The oracle problem remains one of the key challenges in software testing, for which little automated support has been developed so far. We introduce OASIs, a search-based tool for Java that assists testers in oracle assessment and improvement. It does so by combining test case generation to reveal false positives and mutation testing to reveal false negatives. In this work, we describe how OASIs works, provide details of its implementation, and explain how it can be used in an iterative oracle improvement process with a human in the loop. Finally, we present a summary of previous empirical evaluation showing that the fault detection rate of the oracles after improvement using OASIs increases, on average, by 48.6%.","PeriodicalId":20542,"journal":{"name":"Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis","volume":"46 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3213846.3229503","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The oracle problem remains one of the key challenges in software testing, for which little automated support has been developed so far. We introduce OASIs, a search-based tool for Java that assists testers in oracle assessment and improvement. It does so by combining test case generation to reveal false positives and mutation testing to reveal false negatives. In this work, we describe how OASIs works, provide details of its implementation, and explain how it can be used in an iterative oracle improvement process with a human in the loop. Finally, we present a summary of previous empirical evaluation showing that the fault detection rate of the oracles after improvement using OASIs increases, on average, by 48.6%.