基于改进蚁群算法的软件测试方法

为了降低软件的测试成本,提高软件测试效率,提出一种基于改进蚁群算法的软件测试方法.将Markov决策模型应用到软件测试过程当中,采用测试用例约简技术对测试用例集进行简化,利用贪心算法求得的较优解增强蚁群算法初始时刻信息素,通过改进的蚁群算法求得最优解,并进行仿真分析.仿真结果表明:改进的测试方法比采用基本蚁群算法的测试方法求得解更优,说明改进的测试方法可以使搜索时间更短,并可降低软件的测试成本.

Research on Software Testing Strategy Based on Improved Ant Colony Algorithm

In order to reduce the cost of software testing and improve the efficiency of software testing, introduce a software testing method based on improved ant colony algorithm. Use Markov decision model in software testing process, test case unit is simplified by reduction testing case technology. Initial time pheromone of ant colony was enhanced by using the excellent solution of the greedy algorithm. The optimal solution was obtained by the improved ant colony algorithm, and simulation analysis was carried out. The simulation results show that the resolution of improved test method was better than the resolution of basic ant colony algorithm. The improved test method can make search time shorter and reduce the testing cost of the software.