Automated test data generation using computational intelligence

This paper evaluates performance of Genetic Algorithm (GA) & Particle Swarm Optimization (PSO) and henceforth derive an algorithm Genetic Particle Swarm Hybrid Algorithm (GPSHA) which is combination of these techniques. The comparison of the algorithms' performance is done, to prove the efficiency of the GPSHA over GA and PSO, based on the number of generations and uniqueness of the test cases that are generated.