Dynamic modeling of networked software interactive behavior

Current behavior modeling methods have its limitation, to deal with more complicated and uncontrollable networked software behavior, model definition and optimization need to be set up. The invariant constraints mining algorithm was investigated, six types of invariants are mined from the software interactive behavior log, which simplifies the model space. To improve the data set expression capacity, events was adopted to describe the states, and data value relationship was mapped into control flow, which more realistically describes the interactive behavior, meanwhile, events in the model satisfied with invariant constraint rules, which provide the basis for software behavior analysis. To ensure the certainty and compleueness of the model, the method of merging equivalent states in the divided sub-diagram was proposed. The experimental and analysis results show that the effectiveness and feasibility of the methods are validated.