Automatic Test Data Generation for Data Flow Testing Using Particle Swarm Optimization

Automatic test case generation is a major problem in software testing. Evolutionary structural testing is an approach to automatically generate test cases that uses a Genetic Algorithm (GA) which is guided by the data How dependencies in the program to search for test data to cover the clef-use association. The Particle Swarm Optimization (PSO) approach is a swarm intelligence technique which can be used to generate test data automatically. We have proposed an algorithm to generate test cases using PSO for data flow testing. We have simulated both the evolutionary and swarm intelligence techniques. From the experiments it has been observed that PSO outperforms GA in 100% clef-use coverage percentage.