A Combination of GA and PSO for Automatic Test Data Generation using Data Flow Coverage

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Sanjay Singla
H M Rai, Priti Singla

Abstract

Software testing plays an important role for software’s quality and reducing the cost. In this paper we introduce a new algorithm that
combine the power of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) called Genetic-Particle Swarm Combined Algorithm
(GPSCA) which is used to generate automatic test data that satisfy data-flow coverage criteria. Finally, the paper presents the results of the
experiments that have been carried out to evaluate the effectiveness of the proposed GPSCA with new fitness function compared to the Genetic
Algorithm and PSO algorithms.

 

Keywords: Genetic Algorithms, Automatic test data generation, data flow testing, Particle Swarm Optimization.

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