基于镜像选择序优化的MART算法

MART Algorithm Based on Mirror Selection Order Optimization

镜像自适应随机测试(Mirror Adaptive Random Testing,MART)算法将输入空间划分为多个不相交的相等子域,源域中使用自适应随机测试(Adaptive Random Testing,ART)算法生成测试数据,剩余子域中使用镜像函数生成镜像测试数据.镜像策略的引入减少了ART算法的计算开销,但是算法的检错有效性也随之降低.通过研究MART算法的特征,分析如何提升MART算法的检错有效性.针对镜像函数将源测试数据镜像到各子域时的镜像顺序,对比分析镜像选择序与镜像函数对MART算法的影响,本文提出了基于镜像受限选择序的MART算法,通过约束镜像选择序,使镜像测试数据分布更均匀.在仿真实验与实例实验结果中均显示,针对镜像策略中镜像选择序的优化,提高了MART算法的检错有效性.

The input space is divided into several disjoint equal subdomains bymirror adaptive random testing(MART).The adaptive random testing(ART)algorithm is used to generate the test data in the source domain,and the mirror function is used to generate the mirror test data in the remaining subdomains.The introduction of mirror strategy reduces the computational cost of ART algorithm,but the effectiveness of failure detection is also reduced.By studying the characteristics of MART algorithm,this paper analyzes how to improve the effectiveness of MART algorithm.In this paper,we compare and analyze the influence of mirror selection order and mirror function on MART algorithm,and propose an algorithm based on mirror limited selection order,which makes the test data more evenly distributed by restricting the mirror selection order.The results of simulation and empirical experiments show that the optimization of the mirror selection order in the mirror strategy improves the effectiveness of the failure detection of the MART algorithm.