{"title":"识别测试关键依赖项","authors":"Stefan Jungmayr","doi":"10.1109/ICSM.2002.1167797","DOIUrl":null,"url":null,"abstract":"Regression testing is a major cost driver during software maintenance. An important approach to reduce maintenance costs is therefore to improve software testability The improvement efforts should concentrate on those parts of a software system that cause the most severe problems during testing and maintenance. This paper describes a new approach to testability improvement focusing on system structure. We identify dependencies that are critical for testing, i.e. test-critical dependencies, based on a set of testability metrics. The results of four case studies show that (1) a small subset of the dependencies within a system has an exceedingly high impact on particular testability metrics, (2) conventional coupling metrics are not good predictors of these test-critical dependencies, (3) dependencies automatically identified to be test-critical are good indicators of design that needs improvement.","PeriodicalId":385190,"journal":{"name":"International Conference on Software Maintenance, 2002. Proceedings.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"64","resultStr":"{\"title\":\"Identifying test-critical dependencies\",\"authors\":\"Stefan Jungmayr\",\"doi\":\"10.1109/ICSM.2002.1167797\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Regression testing is a major cost driver during software maintenance. An important approach to reduce maintenance costs is therefore to improve software testability The improvement efforts should concentrate on those parts of a software system that cause the most severe problems during testing and maintenance. This paper describes a new approach to testability improvement focusing on system structure. We identify dependencies that are critical for testing, i.e. test-critical dependencies, based on a set of testability metrics. The results of four case studies show that (1) a small subset of the dependencies within a system has an exceedingly high impact on particular testability metrics, (2) conventional coupling metrics are not good predictors of these test-critical dependencies, (3) dependencies automatically identified to be test-critical are good indicators of design that needs improvement.\",\"PeriodicalId\":385190,\"journal\":{\"name\":\"International Conference on Software Maintenance, 2002. Proceedings.\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"64\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Software Maintenance, 2002. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSM.2002.1167797\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Software Maintenance, 2002. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSM.2002.1167797","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Regression testing is a major cost driver during software maintenance. An important approach to reduce maintenance costs is therefore to improve software testability The improvement efforts should concentrate on those parts of a software system that cause the most severe problems during testing and maintenance. This paper describes a new approach to testability improvement focusing on system structure. We identify dependencies that are critical for testing, i.e. test-critical dependencies, based on a set of testability metrics. The results of four case studies show that (1) a small subset of the dependencies within a system has an exceedingly high impact on particular testability metrics, (2) conventional coupling metrics are not good predictors of these test-critical dependencies, (3) dependencies automatically identified to be test-critical are good indicators of design that needs improvement.