Abstract:

In the process of objectoriented software design and implementation, responsibility assignment problem (CRA) is one of the most important and complicated procedures, which affects the quality of software to a large extent. In order to achieve the goal of CRA automatically, we propose a CRA multiobjective optimization model which is built from the perspective of cohesion and coupling metrics. On the basis of fast nondominated sorting genetic algorithm, we introduce the agglomerate hierarchical clustering technology to ensure population diversity and to avoid premature convergence. Experiments on automatical class responsibility assignment verify the correctness of the algorithm, whose results are also compared with an existing welldesigned software system. In addition, compared with the single objective genetic algorithm and the SPEA2 algorithm, the proposed algorithm has the best CRA operation effect.

Key words: class responsibility assignment, multi-objective genetic algorithms, fast non-dominated sorting, hierarchical agglomerative clustering