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Decomposing object-oriented class modules using an agglomerative clustering technique

机译:使用聚集聚类技术分解面向对象的类模块

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Software can be considered a live entity, as it undergoes many alterations throughout its lifecycle. Furthermore, developers do not usually retain a good design in favor of adding new features, comply with requirements or meet deadlines. For these reasons, code can become rather complex and difficult to understand. More particularly in object-oriented systems, classes may become very large and less cohesive. In order to identify such problematic cases, existing approaches have proposed the use of cohesion metrics. However, while metrics can identify classes with low cohesion, they cannot identify new or independent concepts. Moreover, these methods require a lot of human interpretation to identify the respective design flaws. In this paper, we propose a class decomposition method using an agglomerative clustering algorithm based on the Jaccard distance between class members. Our methodology is able to identify new concepts and rank the solutions according to their impact on the design quality of the system. Finally, our method has been evaluated by two independent designers who were asked to comment on the suggestions produced by our technique on their projects. The designers provided feedback on the ability of the method to identify new concepts and improve the design quality of the system in terms of cohesion.
机译:由于软件在其整个生命周期中都会经历许多更改,因此可以将其视为活动实体。此外,开发人员通常不会保留良好的设计来支持添加新功能,遵守要求或在截止日期之前完成。由于这些原因,代码可能变得相当复杂且难以理解。更特别地,在面向对象的系统中,类可能变得非常大且凝聚力降低。为了识别这种有问题的情况,现有方法已经提出使用内聚度量。但是,尽管度量可以识别具有低内聚性的类,但它们不能识别新的或独立的概念。而且,这些方法需要大量的人工解释才能识别相应的设计缺陷。在本文中,我们基于类成员之间的Jaccard距离,提出了一种使用聚集聚类算法的类分解方法。我们的方法论能够识别新概念,并根据解决方案对系统设计质量的影响对解决方案进行排名。最后,我们的方法已经由两名独立的设计师进行了评估,他们被要求对我们的技术在他们的项目中提出的建议进行评论。设计师提供了有关该方法识别新概念并提高系统设计质量的能力的反馈。

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