首页|Study of an Improved Genetic Algorithm for Multiple Paths Automatic Software Test Case Generation
Study of an Improved Genetic Algorithm for Multiple Paths Automatic Software Test Case Generation
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NETL
Springer Nature
Automatic generation of test case is an important means to improve the efficiency of software testing。 As the theoretical and experimental base of the existing heuristic search algorithm， genetic algorithm shows great superiority in test case generation。 However， since most of the present fitness functions are designed by a single target path， the efficiency of the generating test case is relatively low。 In order to cope with this problem， this paper proposes an efficiency genetic algorithm by using a novel fitness function。 By generating multiple test cases to cover multiple target paths， this algorithm needs less iterations hence exhibits higher efficiency comparing to the existing algorithms。 The simulation results have also shown that the proposed algorithm is high path coverage and high efficiency。
Software testingTest case generationGenetic algorithmMultiple paths coverage
Erzhou Zhu、Chenglong Yao、Zhujuan Ma、Feng Liu
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School of Computer Science and Technology, Anhui University, Hefei 230601, China
School of Economic and Technical, Anhui Agricultural University, Hefei 230011, China
NETL
Springer Nature
