According to the particle swarm algorithm that easily falls into the local optimal solution and the problem of low search accuracy

this paper proposes reduced adaptive particle swarm optimization algorithm for generating test data automatically.First

this paper reduces the evolution equations of particle swarm and presents evolution equations without velocity.Then this paper proposes adaptive adjustment scheme based on inertia weight and inertia weight is directly acted on the particle position.According to the particle fitness and particle aggregation degree

the population will be divided into three parts.The experiments show that our approach can effectively improve the efficiency of generating test data automatically.