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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.
In the integrated management of the X-system test data generation, the genetic algorithm can not utilize the information provided by the system and need to iterate many times to find the test data. However, the ant colony algorithm is inefficient in the search of the initial pheromone lacking Problem, this paper proposes a method of automatic generation of test data based on hybrid genetic ant colony algorithm. By running a certain number of genetic algorithms, the optimal solution is generated and applied to the distribution of pheromone, and then the ant colony algorithm is used to solve the problem. In triangle program and integrated management Experiments on the X-ray software system show that this method significantly reduces the number of iterations and the time consumed while maintaining the same performance, which improves the testing efficiency.