Optimize SPL Test Cases with Adaptive Simulated Annealing Genetic Algorithm
In Software Product Line(SPL)testing,reduced test suite with high coverage is useful for early features interaction de-tection.sGA(simplified genetic algorithm)and SAGA(simulated annealing genetic algorithm)can generate high coverage test suite.However,small probability mutations in updating test suite may reduce search efficiency and thus miss better solu-tions.An improved test cases generation method based on ASAGA(Adaptive simulated annealing genetic algorithm)is proposed.Experiments on SPLOT(Software Product Lines Online Tools)feature models show that the proposed hybrid ASAGA method can ensure local optimization accuracy and achieve smaller-size test suite with higher coverage.
Test case software test Feature Model Similarity Measure-ment ASAGA
Liu Yan Wenxin Hu Longzhe Han
College of Computer and Software Engineering,East China Normal University Shanghai,China JiangXi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing,
国际会议
2019国图灵大会(ACM Turing Celebration conference-China 2019 )
成都
英文
917-923
2019-05-17（万方平台首次上网日期，不代表论文的发表时间）