GA-ACO算法用于IMX系统测试数据自动生成

在综合管理X-软件系统测试数据生成中，针对遗传算法不能利用系统提供的信息，需要迭代多次才可找到测试数据，而蚁群算法在搜索初期信息素匮乏的情况下测试效率很低等问题，提出了基于混合遗传蚁群算法的测试数据自动生成方法，通过运行一定次数的遗传算法，产生优化解并作用于信息素的分布，再利用蚁群算法精确求解。在三角形程序和综合管理X-软件系统上的实验表明，该方法在保持性能不变的情况下，大幅降低了迭代次数和消耗时间，提升了测试效率。

Automatic Generation of Test Data in IMX System Based on GA-ACO

In integrated management X-software ( IMX) system, genetic algorithm and ant colony algo-rithm have been used to generate the test data automatically. However, for genetic algorithm, it cannot use the information that provided by the system, thus it will iterate many times to generate the test data. For ant colony algorithm, there is little information pheromone on the path early, so it will take a long time to make it. Accordinly, a method based on hybrid genetic algorithm was proposed. First, execute the genetic algorithm for a few times. Second, use the optimization solution to make distribution for infor-mation pheromone. Finally, use ant colony algorithm to give the precision of the solution. Experiments on IMX and triangle program show that the hybrid algorithm has the characteristics of high efficiency, high quality, also it take fewer iterations to find the test data correctly and efficiently.