{"title":"A method for test case generation by improved genetic algorithm based on static structure of procedure","authors":"Wen Jing, Zhang Yikun, Zhao Ming, Chen Hao, Hei Xin-hong, Jianxiong Shen","doi":"10.1109/ICIEA.2017.8283076","DOIUrl":null,"url":null,"abstract":"Software testing is an important method to guarantee software quality. For the large-scale complex software, some mistakes or errors will easily be overlooked if programs are detected only by manual work. Therefore, a full-automatic system is necessary to rapidly cover all program logics through calculation to achieve input and output; besides, the system can assist to generate a large number of test cases before manual intervention, and can find out some software defects to assist manual detection to complete compiling work of all test cases. In this paper, a combination of the static structure of procedure and improved genetic algorithm is proposed in order to implement a fully automatic test case generating technology, enhance the generating efficiency and coverage rate of codes, and also can help to save a lot of time in manual testing.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEA.2017.8283076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Software testing is an important method to guarantee software quality. For the large-scale complex software, some mistakes or errors will easily be overlooked if programs are detected only by manual work. Therefore, a full-automatic system is necessary to rapidly cover all program logics through calculation to achieve input and output; besides, the system can assist to generate a large number of test cases before manual intervention, and can find out some software defects to assist manual detection to complete compiling work of all test cases. In this paper, a combination of the static structure of procedure and improved genetic algorithm is proposed in order to implement a fully automatic test case generating technology, enhance the generating efficiency and coverage rate of codes, and also can help to save a lot of time in manual testing.