基于自适应遗传算法的路径测试数据生成  

Path Test Data Generation Based on Adaptive Genetic Algorithm

作　　者：李军[1] 李艳辉[1] 彭存银[1] 

机构地区：[1]暨南大学珠海学院计算机系,珠海519070

出　　处：《计算机工程》2009年第2期203-205,共3页Computer Engineering

基　　金：暨南大学引进人才基金资助项目(04JZKY004)

摘　　要：针对简单遗传算法容易产生早熟收敛的问题,提出一种自适应遗传算法,用以自动生成测试数据。通过把程序插装法与该遗传算法相结合,实现了路径测试数据的自动生成。将三角形分类程序作为实例对其进行性能测试,实验结果表明,基于自适应遗传算法的测试数据自动生成系统能自动改变选择概率和交叉概率,提高了自动生成测试数据的效率。Aiming at the problem that the simple genetic algorithm is easy to produce premature convergence, an Adaptive Genetic Algorithm（AGA） is presented to automatically generate test data. The method of program insert is integrated with AGA to implement the automatic generating of path test data. The performance of AGA is tested by using a program of triangle classifier as an example, and experimental results show this automatic generating system of test data based on AGA can automatically change the probability of selection and probability of mutation, which promotes the efficiency of automatic generating test data.

关 键 词：软件测试 路径测试数据 自适应遗传算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]