Evolutionary testing (ET) is an effective test case generation technique which uses some meta-heuristic search algorithm, especially genetic algorithm, to generate test case automatically. However, the population prem...Evolutionary testing (ET) is an effective test case generation technique which uses some meta-heuristic search algorithm, especially genetic algorithm, to generate test case automatically. However, the population prematurity problem may decrease the performance of ET. In this paper, a hybrid optimization strategy is proposed based on extended cataclysm which integrates both static configuration strategies and dynamic optimization strategy. Dynamic optimization strategy included the optimization of initial population and the dynamic population optimization based on extended cataclysm, where the diversity of population was monitored during the evolution process of ET, and once the population prematurity was detected, extended cataclysm operation was used to renew the diversity of the population. Experimental results show that the hybrid optimization strategy can improve the performance of ET.展开更多
基金National Natural Science Foundation of China under Grant No. 61806068, 61672204by Visiting Scholar at Home and Aboard Funded Project of Universities of Anhui Province under Grant gxfxZD2016209+3 种基金by Key Technologies R&D Program of Anhui Province under Grant 1804a09020058by the Major Program for Scientific and Technological of Anhui Province under Grant 17030901026by Talent Research Foundation Project of Hefei University under Grant 16-17RC23by Humanities and Social Science Research Project of Universities of Anhui Province under Grant SK2018A0605.
文摘Evolutionary testing (ET) is an effective test case generation technique which uses some meta-heuristic search algorithm, especially genetic algorithm, to generate test case automatically. However, the population prematurity problem may decrease the performance of ET. In this paper, a hybrid optimization strategy is proposed based on extended cataclysm which integrates both static configuration strategies and dynamic optimization strategy. Dynamic optimization strategy included the optimization of initial population and the dynamic population optimization based on extended cataclysm, where the diversity of population was monitored during the evolution process of ET, and once the population prematurity was detected, extended cataclysm operation was used to renew the diversity of the population. Experimental results show that the hybrid optimization strategy can improve the performance of ET.
基金the National Natural Science Foundation of China(21471145)the Science and Technology Development Planning Project of Jilin Province(20170101179JC)the“Hundred Talents Program”of Chinese Academy of Sciences。
