摘要
针对两两组合测试用例集的生成问题,在有效地结合了两两组合测试问题本身的特点基础上,提出了一种基于动态解空间的启发式遗传算法(HGA)。详细分析了测试用例生成过程,根据其解空间的动态变化在传统遗传算法中加入了启发算子,使得HGA算法可以快速地搜索出当前局部优化的测试用例。实验结果表明,HGA算法在完全覆盖参数两两组合的前提下有效地减少了测试用例的数量,并且具有较快的迭代速度。
Aimed at generating minimum test cases, heuristic genetic algorithm based on the dynamic solution space is presented. According the changes of the solution space, heuristic operator is added to genetic algorithm, which makes the generation of the test case with the local optimal coverage in current environment more efficient. The experimental results show that HGA not only decreases the test cases obviously but also iterates very quickly, with the full coverage of the pair-wise combinations of the parameters.
出处
《计算机工程与设计》
CSCD
北大核心
2011年第5期1722-1724,1758,共4页
Computer Engineering and Design
关键词
软件测试
组合测试
测试用例
遗传算法
启发算子
software test
combinatorial test
test case
genetic algorithm
heuristic operator
