{"title":"Introducing a test suite similarity metric for event sequence-based test cases","authors":"Penelope A. Brooks, A. Memon","doi":"10.1109/ICSM.2009.5306305","DOIUrl":null,"url":null,"abstract":"Most of today's event driven software (EDS) systems are tested using test cases that are carefully constructed as sequences of events; they test the execution of an event in the context of its preceding events. Because sizes of these test suites can be extremely large, researchers have developed techniques, such as reduction and minimization, to obtain test suites that are “similar” to the original test suite, but smaller. Existing similarity metrics mostly use code coverage; they do not consider the contextual relationships between events. Consequently, reduction based on such metrics may eliminate desirable test cases. In this paper, we present a new parameterized metric, CONTeSSi(n) which uses the context of n preceding events in test cases to develop a new context-aware notion of test suite similarity for EDS. This metric is defined and evaluated by comparing four test suites for each of four open source applications. Our results show that CONT eSSi(n) is a better indicator of the similarity of EDS test suites than existing metrics.","PeriodicalId":247441,"journal":{"name":"2009 IEEE International Conference on Software Maintenance","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Software Maintenance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSM.2009.5306305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Most of today's event driven software (EDS) systems are tested using test cases that are carefully constructed as sequences of events; they test the execution of an event in the context of its preceding events. Because sizes of these test suites can be extremely large, researchers have developed techniques, such as reduction and minimization, to obtain test suites that are “similar” to the original test suite, but smaller. Existing similarity metrics mostly use code coverage; they do not consider the contextual relationships between events. Consequently, reduction based on such metrics may eliminate desirable test cases. In this paper, we present a new parameterized metric, CONTeSSi(n) which uses the context of n preceding events in test cases to develop a new context-aware notion of test suite similarity for EDS. This metric is defined and evaluated by comparing four test suites for each of four open source applications. Our results show that CONT eSSi(n) is a better indicator of the similarity of EDS test suites than existing metrics.