AFL fuzzy test method based on particle swarm optimization

The invention relates to an AFL fuzzy testing method based on a particle swarm algorithm, and belongs to the technical field of fuzzy testing. According to the AFL fuzzy test method based on the particle swarm algorithm, the problem that edge coverage is missing in the existing fuzzy test technology is solved, the particle swarm algorithm is applied to a fuzzy test tool AFL, selection of mutation operators in seed mutation is optimized, and the edge coverage rate is increased. Wherein each mutation operator is used as a particle, the selected probability of each mutation operator is used as a weight, a plurality of probabilities are distributed to each mutation operator in one iteration, a plurality of particle swarms are formed, iteration is carried out on the plurality of swarms, and a local optimal solution and a global optimal solution are found. According to the method, the research center of gravity is put in the mutation stage of the seeds, the probability distribution of each mutation operator is opti