Generation of Pairwise Test Sets Using a Novel DPSO Algorithm
The pairwise test suite generation is one of key issues of combinatorial testing. This paper presents a novel discrete particle swarm optimization algorithm (DPSO) to generate pairwise test data of combinatorial testing. In the algorithm, a particle represents a test suite, fitness function is evaluated by the uncovered number of combination pair, and the position of the particle is produced by stochastic algorithm, which is randomly generated by the frequency of discrete values of all factors in test suite, then optimal test suite which covers all combination pairs is generated. Finally, the classic example is used to illustrate the performance of the proposed algorithm. Compared with the existing algorithms, this paper provides an effective pairwise test suite generation method which has nothing to do with the initial value and can generate the most effective test suit with fast convergence, less calculation and stability.
KeywordsCombinatorial testing Discrete particle swarm optimization algorithm Test case generation
This work was supported in part by project “Research on Key Problem of Combinatorial Software Testing optimization Based on Swarm Intelligence” (61050003) from National Natural Science Foundation of China, by project “Smart Combinatorial Soft Testing method “ (ZL2009-9) from Natural Science Foundation of XUPT, by project “Smart Combinatorial Embedded Soft Testing Platform” (2009K08-26) from Key Technologies R and D Programmed Foundation of Shan xi Province.
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