Abstract: Comprehensive consideration of client and server Web application evolution test generation method can test Web applications more effectively and improve their quality and safety. However, the client-side test cases involve interaction with the browser, which slows down the test efficiency. In addition, the decline in population diversity during the evolution process is likely to lead to the problems of low test generation efficiency and poor test generation effect. Therefore, the distributed parallel strategy is introduced into the evolution generation of Web application test cases with front-end and back-end fusion, and the evolution generation process of test cases is optimized at the algorithm and execution level to improve the test generation effect and efficiency. Specifically, at the algorithm level, the parallel evolution and genetic algorithm are combined to divide the population based on individual similarity and form multiple subgroups. Parallel evolution of multiple subgroups and individual migration among subgroups can increase the population diversity in the process of test evolution generation, thus improving the effect and efficiency of test generation. At the execution level, multi-thread and multi-browser process collaboration, thread pool management and dynamic scheduling strategy are adopted to realize the parallel execution of multiple subgroups, so as to improve the execution efficiency of test generation. The experimental results show that the distributed parallel evolutionary test generation method for Web application improves the test generation effect and reduces the generation time of test cases.