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Refactoring packages of object-oriented software using genetic algorithm based community detection technique

机译:基于遗传算法的社区检测技术对面向对象软件的重构

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摘要

Refactoring is regarded as an effective way to address the software quality deterioration problem. Although many refactoring approaches have been proposed, there is little work at the package level. This paper proposes to use the community detection technique to refactor the packages of object-oriented software. It uses software class network to represent classes and their dependencies, proposes a genetic algorithm based community detection algorithm to obtain the optimised package structures, and finally provides a list of classes that should be moved by comparing the optimised package structures with the real package structures. The empirical evaluation of the proposed approach has been performed in two open source Java projects, and the benefits of our approach are illustrated in comparison with the only one software refactoring approach at the package level (viz. adaptive k-nearest neighbour algorithm), and other five community detection algorithms used in the complex networks literature.
机译:重构被认为是解决软件质量下降问题的有效方法。尽管已经提出了许多重构方法,但是在程序包级别上几乎没有任何工作。本文提出使用社区检测技术来重构面向对象软件的软件包。它使用软件类网络来表示类及其依赖关系,提出了一种基于遗传算法的社区检测算法来获取优化的包装结构,最后通过将优化的包装结构与实际包装结构进行比较来提供应移动的类的列表。在两个开源Java项目中对所提出的方法进行了实证评估,与仅在软件包级别的一种软件重构方法(即自适应k最近邻算法)相比,我们的方法的优势得到了说明。复杂网络文献中使用的其他五种社区检测算法。

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