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...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.展开更多
Since traditional whale optimization algorithms have slow convergence speed,low accuracy and are easy to fall into local optimal solutions,an improved whale optimization algorithm based on mirror selection(WOA-MS)is p...Since traditional whale optimization algorithms have slow convergence speed,low accuracy and are easy to fall into local optimal solutions,an improved whale optimization algorithm based on mirror selection(WOA-MS)is proposed. Specific improvements includes:(1)An adaptive nonlinear inertia weight based on Branin function was introduced to balance global search and local mining.(2) A mirror selection method is proposed to improve the individual quality and speed up the convergence. By optimizing several test functions and comparing the experimental results with other three algorithms,this study verifies that WOA-MS has an excellent optimization performance.展开更多
文摘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.
基金Supported by the National Natural Science Foundation of China(Nos.31320103907,31230070,31201905)the Special Fund of Agro-scientific Research in the Public Interest(No.201403054)+2 种基金the National High Technology Research and Development Program of China(No.2011AA10A212)the National Science&Technology Pillar Program(No.2014BAD13B02)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)~~
基金supported by the Natural Science Foundation of Jiangsu Province (No. BK20151479)the Open Foundation of Graduate Innovation Base in Nanjing University of Aeronautics and Astronautics(No. kfjj20190736)
文摘Since traditional whale optimization algorithms have slow convergence speed,low accuracy and are easy to fall into local optimal solutions,an improved whale optimization algorithm based on mirror selection(WOA-MS)is proposed. Specific improvements includes:(1)An adaptive nonlinear inertia weight based on Branin function was introduced to balance global search and local mining.(2) A mirror selection method is proposed to improve the individual quality and speed up the convergence. By optimizing several test functions and comparing the experimental results with other three algorithms,this study verifies that WOA-MS has an excellent optimization performance.