关键词: 软件模块化, 软件聚类问题, 遗传算法, 启发式策略, 产品设计

Abstract:

Considering the isolated cluster problem caused by traditional software modularization methods, a new metric named Improved Modularization Quality (IMQ) was proposed and used as the fitness function of evolutionary algorithm to eliminate isolated cluster effectively. A mathematical programming model with the goal of maximizing IMQ was developed to represent software modularization problem. In addition, an Improved Genetic Algorithm (IGA) with the crossover operator based on similarity mechanism was designed to solve this model. Firstly, a heuristic based on edge contraction was used to generate high-quality solutions. Then the solutions were implanted as seeds into the initial population. At last, an Improved Genetic Algorithm (IGA) was employed to further improve solution quality. Comparison experimental results prove that IMQ can effectively reduce the number of isolated cluster, and IGA has stronger robustness and ability of finding better solutions than Improved Hill Climbing Algorithm (IHC) and GA based on GNE.

Key words: software modularization, software clustering problem, Genetic Algorithm (GA), heuristic strategy, product design