{"title":"基于搜索的扩展有限状态机(EFSM)测试自动生成方法","authors":"A. Kalaji, R. Hierons, S. Swift","doi":"10.1109/TAICPART.2009.19","DOIUrl":null,"url":null,"abstract":"The extended finite state machine is a powerful model that can capture almost all the aspects of a system. However, testing from an EFSM is yet a challenging task due to two main problems: path feasibility and path test data generation. Although optimization algorithms are efficient, their applications to EFSM testing have received very little attention. The aim of this paper is to develop a novel approach that utilizes optimization algorithms to test from EFSM models.","PeriodicalId":339626,"journal":{"name":"2009 Testing: Academic and Industrial Conference - Practice and Research Techniques","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"A Search-Based Approach for Automatic Test Generation from Extended Finite State Machine (EFSM)\",\"authors\":\"A. Kalaji, R. Hierons, S. Swift\",\"doi\":\"10.1109/TAICPART.2009.19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The extended finite state machine is a powerful model that can capture almost all the aspects of a system. However, testing from an EFSM is yet a challenging task due to two main problems: path feasibility and path test data generation. Although optimization algorithms are efficient, their applications to EFSM testing have received very little attention. The aim of this paper is to develop a novel approach that utilizes optimization algorithms to test from EFSM models.\",\"PeriodicalId\":339626,\"journal\":{\"name\":\"2009 Testing: Academic and Industrial Conference - Practice and Research Techniques\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Testing: Academic and Industrial Conference - Practice and Research Techniques\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAICPART.2009.19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Testing: Academic and Industrial Conference - Practice and Research Techniques","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAICPART.2009.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Search-Based Approach for Automatic Test Generation from Extended Finite State Machine (EFSM)
The extended finite state machine is a powerful model that can capture almost all the aspects of a system. However, testing from an EFSM is yet a challenging task due to two main problems: path feasibility and path test data generation. Although optimization algorithms are efficient, their applications to EFSM testing have received very little attention. The aim of this paper is to develop a novel approach that utilizes optimization algorithms to test from EFSM models.