基于多种群遗传算法测试用例优先级技术研究  

Research Test Case Suite Minimization Based on Multiple Population Genetic Algorithm

作　　者：李龙澍[1] 李森[1] 廖敏[1] 汪小珍[1] 

机构地区：[1]安徽大学计算智能与信号处理教育部重点实验室,安徽合肥230039

出　　处：《计算机技术与发展》2011年第4期112-114,119,共4页Computer Technology and Development

基　　金：安徽省自然科学基金(090412054)

摘　　要：测试用例优先级技术是一种高效实用的回归测试技术。为提高回归测试效率,提出了一种应用于回归测试过程中基于多种群遗传算法测试用例优先级技术的方法。该方法采用三个具有不同进化规律的种群,第一个种群重视全局搜索,第二个种群重视局部搜索,第三个种群通过前两个种群的移入来均衡算法的局部搜索和全局搜索能力,使算法能在更大范围内寻优。经过实验验证,该算法是一种有效的测试用例优先排序方法,较一般的遗传算法具有更强的性能和更高的效率。Test case prioritization is an effective and practical technique applied in regression testing.In order to increase the effectiveness of test suite,algorithm for construction of software test case suite minimization based on multiple population genetic algorithm.This algorithm has there populations with different evolution pattern,and the first focus on the overall search,the second focus on the overall search,while the third can balance the search ability at both the local search and local search through the migration parter,which makes multiple population genetic algorithm search better solutions in a larger range.The experimental results show that this algorithm is a kind of effective method of test cases which is superior in both effectiveness and efficiency.

关 键 词：测试用例优先级 回归测试 多种群 遗传算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]