J4 ›› 2012, Vol. 34 ›› Issue (1): 86-89.
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SHI Guiying
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Abstract:
Software testing is an important means of software quality assurance,the automatic generation of test cases has been widely studied. By analyzing the advantages and disadvantages of the genetic algorithm, the particle swarm optimization algorithm and the ant colony algorithm,the paper proposes a new improved particle swarm algorithm in the automatic generation of test cases. The pheromone mechanism of the ant colony algorithm is introduced into the particle swarm algorithm, which can increase the diversity of particles and overcome the defect that PSO is easy to premature and stagnation. Finally the simulation experiment proves the feasibility and efficiency of the algorithm in software testing.
Key words: PSO;ACO;peromone mechanism;software testing
SHI Guiying. Application of an Improved Particle Swarm Optimization Algorithm in Software Test Data Generation[J]. J4, 2012, 34(1): 86-89.
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http://joces.nudt.edu.cn/EN/Y2012/V34/I1/86