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稿件标题: Automated Test Data Generation Based on Particle Swarm Optimization with Convergence Speed Controller
稿件作者: Fangqing Liu,Han Huang,Xueqiang Li,Zhifeng Hao
关键字词: automated test data generation;hadoop program; particle swarm optimization;convergence speed controller
文章摘要: Automated test data generation for path coverage (ATDG-PC) plays an important role in software testing. In this paper, ATDG-PC is applied to the case of cloud computing such as Hadoop programs which are more difficult to search for high-rate path coverage than the normal programs. ATDG-PC can be modelled as an optimization problem of search. It’s a challenge because its search scale is usually enormous, while the relationship between the variables and the paths is unknown. First, a rapid meta-heuristic algorithm particle swarm optimization (PSO) was chosen to solve the problem of large-scale search. Second, the strategy of convergence speed controller was used to improve the performance of PSO by mining heuristic information from the found paths. The controller adjusts the convergence speed balance periodically by two conditions and rules. The first strategy slows the convergence speed when the algorithm is premature convergence and is trapped in a local optimum. The second strategy ac
收录刊物: 2017年2卷2期
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