基于遗传算法的DM-GA组合测试数据生成方法

测试数据生成是组合软件测试的重要部分,生成高质量的测试数据对于软件测试具有重要意义.针对两两组合测试数据生成问题,结合传统遗传算法,加入了精英策略和自适应变异概率,提出了DM-GA( dynamic mutation rates-genetic algorithm)算法,改善了传统遗传算法容易陷入局部最优以及收敛速度慢等不足,并取得了良好的效果.实验结果表明DM-GA算法可以作为一种较理想的两两组合测试数据生成方法.

DM-GA:A PAIRWISE TESTING DATA GENERATION APPROACH BASED ON GENETIC ALGORITHM

Test data generation is an important part of combinatorial software testing,to generate the high quality test data plays a significant role in software testing.This paper presents the DM-GA(dynamic mutation rates-genetic algorithm) in light of the pairwise testing data generation issue,which is based on traditional genetic algorithm,and the elitism and adaptive mutation probability are added to as well.The DM-GA meliorates the deficiencies of the traditional genetic algorithm in easy to fall into the local optimum and slow convergence speed,achieves preferable effect.Simulation results show that DM-GA can be used as an ideal approach for pairwise test suite generation.