Abstract
AbstractIt is a key activity in CBD to identify high-quality components which have high cohesion and low coupling. However, component clustering is carried out in manual fashion by developers, resulting excessive time consumption and generating errors. In this article, we present an implementation of a tool which automates a component clustering and identification method. We show how we realize a clustering method as a tool and explain techniques applied in the implementation. Using the tool, component identification can be automated, and one can generate and navigate multiple configurations to find the most appropriate one for the project effortlessly.
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