Abstract: The automatic test case generation is a key phase of software testing and an important part of software assurance. The study on the heuristic algorithms is an emerging area of the automatic test case generation in recent years. The new heuristic algorithm of PSO for the test case generation is reviewed and analyzed. Key issues on the PSO test case generation are discussed, including PSO fitness functions, PSO premature convergence and local optimum, swarm size impact, and parameter optimization. A contrastive analysis of PSO and GA in software testing is presented in detail. Finally, the future development of PSO test case generation algorithms is prospected including the test case swarm size optimization, the premature restraining, and the parameter optimization.