A Novel Method for Behavioral Model Refinement Based on Genetic Programming

The refinement of behavioral models is a crucial issue in model driven software development. In this paper, according to the formal behavioral models for environment description and the refinement theory in formal methodology, an automatic method for the refinement of behavior models based on genetic programming is proposed. The method regards the refinement as the assembling process of some basic executable operations. In the beginning, by means of analyzing the post condition formula of the abstract behavior, the refinement based on the logic reduction is carried out, and thus the loop structures and other simple formulae are produced. The simple formulae are used to construct new abstract behaviors, and they are refined sequentially by the refinement based on genetic programming until the generated program is comprised of the basic operations finally. Since choice structures are difficult to evolve by traditional genetic programming, the authors introduce the conception of combination termination criterion. By testing this criterion, the choice structures are created as well. Finally, sorting is taken as an example to demonstrate the evolutionary process, and the result shows that the proposed method is fairly feasible. As a matter of fact, the method can be used in the problem solving areas in which the solution is composed of some basic operations.