Optimal Test Case Selection Using Ant Colony and Rough Sets
作者: Angelin Gladston Niranjana Devi N.
作者单位: 1Anna University, India
刊名: International Journal of Applied Evolutionary Computation (IJAEC), 2020, Vol.11 (2), pp.1-14
来源数据库: IGI Global Journal
DOI: 10.4018/IJAEC.2020040101
原始语种摘要: Test case selection helps in improving quality of test suites by removing ambiguous, redundant test cases, thereby reducing the cost of software testing. Various works carried out have chosen test cases based on single parameter and optimized the test cases using single objective employing single strategies. In this article, a parameter selection technique is combined with an optimization technique for optimizing the selection of test cases. A two-step approach has been employed. In first step, the fuzzy entropy-based filtration is used for test case fitness evaluation and selection. In second step, the improvised ant colony optimization is employed to select test cases from the previously reduced test suite. The experimental evaluation using coverage parameters namely, average percentage...
全文获取路径: IGI Global 

  • Selection 分选
  • optimization 最佳化
  • coverage 复盖
  • ambiguous 含糊的
  • fitness 适合度
  • employed 就业
  • computational 计算的
  • single 单独的
  • reducing 还原
  • fuzzy 模糊的