Abstract: To reduce the size of test case and the cost of regression test, the paper presents an algorithm of the combination of Genetic Algorithm(GA) and Ant Colony Algorithm(ACA). It uses the GA to realize genetic operator operation, the result as ACA for initialization pheromone distribution. It uses ACA to update the ant path and pheromone transfer, and obtains the optimal solution of the problem. Experimental results show that the method can effectively reduce the test suite, shorten operating time, and improve the effectiveness of minimization.

Key words: regression test, test case minimization, coverage, running cost, Genetic Algorithm(GA), Ant Colony Algorithm(ACA), combination algorithm

摘要： 为缩减测试用例规模及降低回归测试成本，提出一种基于遗传蚁群融合算法的测试用例最小化方法。采用遗传算法进行遗传算子操作，其结果作为蚁群算法的初始信息素分布。使用蚁群算法进行蚂蚁路径转移和信息素的更新，得到最优解。实验结果证明，该方法能有效减小测试用例集规模，缩短运行时间，提高最小化效率。

关键词: 回归测试, 测试用例最小化, 覆盖度, 运行代价, 遗传算法, 蚁群算法, 融合算法

CLC Number: 

• TP311.13