采用元启发式算法的半自动面向对象软件设计

Zeynab Javidi, R. Akbari, O. Bushehrian
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引用次数: 2

摘要

软件设计的质量对最终产品的可扩展性和可维护性有着重要的影响。自动化技术可以帮助设计师实现更好的设计。软件设计自动化有几种方法。一般基于搜索的方法,如遗传算法、蚁群算法和ICA算法,用于解决搜索空间大、难以找到最优解的问题。本文提出了一种称为ICA-TS(帝国主义竞争算法-禁忌搜索)的混合算法,用于自动生成待设计系统的类图。该方法分为三个阶段:首先,采用形式概念分析(FCA)作为方法预处理阶段的均值生成初始解;接下来,使用ICA和TS的混合来更新解决方案。类之间的关系在第三阶段确定。采用三个标准案例进行了性能评估,并将结果与遗传ICA和简单ICA的结果进行了比较。结果表明,该方法具有较好的效果,在系统的内聚性、耦合性和复杂性方面都能生成更高效的类图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semi-automatic object-oriented software design using metaheuristic algorithms
The quality of software design always has a significant impact on the extendibility and maintainability of the final product. Automatic techniques may help designers to achieve better design. There are several ways for software design automation. Generally Search-based methods such as GA, ant colony, and ICA are used for problems with large search space in which finding the optimal solution is hard. In this paper a hybrid algorithm called ICA-TS (Imperialist Competitive Algorithm-Tabu Search) is presented to generate class diagram of the under design system automatically. The method has three phases: First, formal concept analysis (FCA) for preprocessing phase of the method is used as a mean to generate initial solution. Next a hybrid of ICA and TS is used to update solutions. The relationships between classes are determined in third phase. Three standard case studies are used for performance evaluation and the results are compared with results of genetic and simple ICA. The results show that the presented method has competitive results and it can generate more efficient class diagram in terms of cohesion, coupling and complexity of system.
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