An approach for test data generation using program slicing and particle swarm optimization
Heuristic search-based test data generation has a potential higher efficiency in software testing with path covering. However, these approaches are suffered in covering the long and complex path. In this paper, we propose a method for generating test data based on program slicing and particle swarm optimization. With the interest points selected from a target path, we perform a program slicing to remove the statements which are irrelevant to the interest points. Our method simplifies the target path and the actual path to get a better fitness value. After program slices obtained, the population is evolved using particle swarm optimization to improve the efficiency of test data generation.
test data generation program slicing particle swarm optimization path covering