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  • 标题:Optimized Test Case Generation Using Genetic Algorithm
  • 本地全文:下载
  • 作者:Amit Kumar Sharma
  • 期刊名称:International Journal of Computing and Business Research
  • 电子版ISSN:2229-6166
  • 出版年度:2013
  • 卷号:4
  • 期号:3
  • 出版社:International Journal of Computing and Business Research
  • 摘要:Today, Automated generation of test cases to test software product is very essential as it can decrease the time and cost of testing process. While manual testing is very time consuming and costly, Software companies are now turning towards automated testing tools and techniques. In this paper we explore how Genetic Algorithm, improves the quality and reliability of the software by generating optimized test cases. A genetic algorithm (GA) is a search algorithm based on principles from natural selection and genetic reproduction, adopted by Darwin. Three basic steps responsible for GA are (1) selection of initial chromosomes from the population, (2) performing crossover by exchanging the information between selected chromosomes and (3) performing mutation operation on the selected genes. This paper also presents the automated software testing architecture. At last, we are putting some amount of light on pitfalls of automated testing technique
  • 关键词:Genetic Algorithms; Automated Testing; ;Chromosomes; Test Cases; Testing Tools
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