{"title":"通过挖掘历史数据,提高测试套件的有效性","authors":"Jeff Anderson, Saeed Salem, Hyunsook Do","doi":"10.1145/2597073.2597084","DOIUrl":null,"url":null,"abstract":"Software regression testing is an integral part of most major software projects. As projects grow larger and the number of tests increases, performing regression testing becomes more costly. If software engineers can identify and run tests that are more likely to detect failures during regression testing, they may be able to better manage their regression testing activities. In this paper, to help identify such test cases, we developed techniques that utilizes various types of information in software repositories. To assess our techniques, we conducted an empirical study using an industrial software product, Microsoft Dynamics AX, which contains real faults. Our results show that the proposed techniques can be effective in identifying test cases that are likely to detect failures.","PeriodicalId":6621,"journal":{"name":"2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR)","volume":"93 1","pages":"142-151"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":"{\"title\":\"Improving the effectiveness of test suite through mining historical data\",\"authors\":\"Jeff Anderson, Saeed Salem, Hyunsook Do\",\"doi\":\"10.1145/2597073.2597084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software regression testing is an integral part of most major software projects. As projects grow larger and the number of tests increases, performing regression testing becomes more costly. If software engineers can identify and run tests that are more likely to detect failures during regression testing, they may be able to better manage their regression testing activities. In this paper, to help identify such test cases, we developed techniques that utilizes various types of information in software repositories. To assess our techniques, we conducted an empirical study using an industrial software product, Microsoft Dynamics AX, which contains real faults. Our results show that the proposed techniques can be effective in identifying test cases that are likely to detect failures.\",\"PeriodicalId\":6621,\"journal\":{\"name\":\"2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR)\",\"volume\":\"93 1\",\"pages\":\"142-151\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"47\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2597073.2597084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2597073.2597084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving the effectiveness of test suite through mining historical data
Software regression testing is an integral part of most major software projects. As projects grow larger and the number of tests increases, performing regression testing becomes more costly. If software engineers can identify and run tests that are more likely to detect failures during regression testing, they may be able to better manage their regression testing activities. In this paper, to help identify such test cases, we developed techniques that utilizes various types of information in software repositories. To assess our techniques, we conducted an empirical study using an industrial software product, Microsoft Dynamics AX, which contains real faults. Our results show that the proposed techniques can be effective in identifying test cases that are likely to detect failures.