title: Genetic algorithm-based test data generation for multiple paths via individual sharing.
abstract: The application of genetic algorithms in automatically generating test data has aroused broad concerns and obtained delightful achievements in recent years. However, the efficiency of genetic algorithm-based test data generation for path testing needs to be further improved. In this paper, we establish a mathematical model of generating test data for multiple paths coverage. Then, a multipopulation genetic algorithm with individual sharing is presented to solve the established model. We not only analyzed the performance of the proposed method theoretically, but also applied it to various programs under test. The experimental results show that the proposed method can improve the efficiency of generating test data for many paths' coverage significantly.
authors.affiliation: College of Science, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.
authors.forename: Xiangjuan
authors.identifier: 0000-0003-3207-703X
authors.initials: X
authors.lastname: Yao
authors.affiliation: School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.
authors.forename: Dunwei
authors.initials: D
authors.lastname: Gong
mesh_terms: D000465:Algorithms; D001330:Electronic Data Processing; D006801:Humans; D033181:Information Dissemination; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D012984:Software