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A hybrid approach for test case prioritization and optimization using meta-heuristics techniques

Software testing is a very crucial and important phase for (SDLC) software development life cycle. Software is being tested on its effectiveness for generating good quality software. Regression testing is done by considering the constraints of resources and in this phase optimization of test suite is very important and crucial. This paper mainly aims to make use of hybrid approach of meta-heuristics, It comprises of two algorithms first is genetic algorithm and second is particle swarm optimization. In addition to algorithm the comparison of proposed algorithm hybrid GA_PSO with other optimization algorithms are been done. To validate the research Average Percentage Fault Detection (APFD) metric is used for comparison and fitness evaluation of the proposed algorithm.