Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (19): 58-61.DOI: 10.3778/j.issn.1002-8331.2009.19.017

• 研发、设计、测试 • Previous Articles     Next Articles

Research test case suite minimization based on genetic algorithm

QUAN Jun-lin,LU Lu   

  1. Department of Computer Science and Engineering,South China University of Technology,Guangzhou 510006,China
  • Received:2008-05-05 Revised:2008-07-31 Online:2009-07-01 Published:2009-07-01
  • Contact: QUAN Jun-lin

基于遗传算法测试用例集极小化研究

全君林,陆 璐   

  1. 华南理工大学 计算机科学与工程学院,广州 510006
  • 通讯作者: 全君林

Abstract: Algorithm for construction of software test case suite minimization based on Genetic Algorithm(GA) is proposed.The algorithm focuses on the process of regressive test.Many redundancy test cases remain in the test suite.So this paper models the relationship between test cases and test requirement as a classic set covering problem.And then utilize the Genetic algorithm’s power global search ability.Minimize the test cases and test cost expense,as well as cover the requirement of regression test.The simulation results show that this algorithm is superior in both effectiveness and efficiency.

Key words: Genetic Algorithm(GA), test case suite, set covering problem, minimize

摘要: 提出了一种应用于软件回归测试过程中的基于遗传算法的最小化测试用例集算法模型。该算法针对在软件回归测试过程中,测试套间内的测试用例间往往存在着重复覆盖测试需求的情况,因而测试套间中将存在着大量的冗余测试用例,将测试用例与测试需求之间的覆盖关系模型转化为集覆盖模型。然后利用遗传算法强大的全局搜索能力,优化在极小化的测试用例空间,较低的测试成本条件下,覆盖回归测试需求。并通过对算法的仿真结果进行分析表明,该算法较一般的优优化算法具有更高算法性能与效率。

关键词: 遗传算法, 测试用例集, 覆盖集问题, 极小化