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Weak mutation test case set generation based on dynamic set evolutionary algorithm
GUO Houqian, WANG Weiwei, SHANG Ying, ZHAO Ruilian
Journal of Computer Applications    2017, 37 (9): 2659-2664.   DOI: 10.11772/j.issn.1001-9081.2017.09.2659
Abstract507)      PDF (1113KB)(393)       Save
To solve the problem of fixed individual scale and high execution cost of weak mutation test case set generation based on Set Evolutionary Algorithm (SEA), a generation method of weak mutation test case set based on Dynamic Set Evolutionary Algorithm (DSEA) was proposed. The test case sets were used as individuals to generate some weak mutations to cover all mutant branches. In the evolutionary process, according to the minimum subset of the optimal individuals and the number of uncovered mutation branches, the minimum scale of the required test case set was calculated by the set compact operator. And the size of all individuals in the population was adjusted based on the minimum scale to generate the smallest scale of the weak mutation test case set. At the same time, a fitness function for assessing a use case set as an individual was designed. The experimental results show that when the dynamic ensemble evolution algorithm is used to guide the generation of weak mutation test cases, and the scale of the test cases was 50.15% lower than the initial size of the individuals, and the execution time is lower than that of SEA by 74.58% at most. Thus, the dynamic ensemble evolution algorithm provides a solution for generating of the weak mutation test case set with minimum scale and enhancing the algorithm speed.
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