【摘要】 在软件测试实践中,由于受到测试投入时间、投入资金和人力成本的约束,软件测试不可能以无限制投入来获取理想的软件质量。针对测试成本约束下条件下在测试用例集中如何选择测试用例以获取最优软件测试覆盖这样一个具有理论价值和现实意义的问题,提出了综合考虑测试成本、测试用例权重和测试用例相距度三要素的测试用例选择寻优新思路,给出了测试成本约束下测试用例选择寻优问题的形式化描述,提出了基于遗传算法和测试成本约束的测试用例选择寻优算法的两种基本算法,即测试用例权重优先的测试用例选择寻优算法以及集群测试用例优先的测试用例选择寻优算法,并以一个模拟测试用例集合对算法有效性进行了检验,实验结果表明两种测试用例选择寻优算法在测试覆盖效果上均显著优于随机选择算法。更多还原

【Abstract】 In practice of software testing, due to the limited cost in time, money and manpower, it is impossible to invest unlimited input into a software testing to obtain an ideal software quality. To resolve the valued issue that under a limited test cost, how to select test cases in a test-case set for obtaining an optimal software testing coverage, a new idea of test-case selection optimization with an overall consideration on test cost, test-case weight and test-case distance, was proposed based on the definition of test-case distance with Euclidean space distance, then a formal description of the issue, the test-case selection optimization under a limited test cost, was given. Two basic test-case selection optimization algorithms under a limited test cost were proposed, which are weight prior test-case selection optimization algorithm and cluster prior test-case selection optimization algorithm. Finally the proposed algorithms were verified with a simulated test-case set, and the results show that the proposed two algorithms are significantly better than random selection algorithm in test coverage.更多还原