Abstract: Flowing the way introduced in the research of evolutionary fuzzing system (EFS), a smart fuzzing method was proposed based on the node comparison algorithm among the control flow sequences. Through mapping program execution flow sequences onto the control flow sequences, the isomorphism relationship between dada search space and program logic space was established. The analyzed results prove that the method is capable of mining a mass of information from group data effectively, and is able to fully utilize the parallelism of genetic algorithm to guide the fuzzing test.