A Novel Algorithm for Multi-Path Test Data Generation

Automatically generating test data to cover multiple paths is a challenging problem. This paper presents a new niching PSO algorithm, called MNPSO, to deal with this problem. In MNPSO, all particles are dynamically divided into several sub-populations and each sub-population has its global best position. The best positions of each particle are recorded for sub-populations. Test data is generated for one target path in each sub-population and the center of each sub-population is its global best positions. The results of experiments showed that MNPSO improved the efficiency of multi-path test data generation and multi-path coverage.