Extract Class Refactoring Based on Cohesion and Coupling: A Greedy Approach

Abstract

A large class with many responsibilities is a design flaw that commonly occurs in real-world object-oriented systems during their lifespan. Such a class tends to be more difficult to comprehend, test, and change. Extract class refactoring (ECR) is the technique that is used to address this design flaw by trying to extract a set of smaller classes with better quality from the large class. Unfortunately, ECR is a costly process that takes great time and effort when it is conducted completely by hand. Thus, many approaches have been introduced in the literature that tried to automatically suggest the best set of classes that can be extracted from a large class. However, most of these approaches focus on improving the cohesion of the extracted classes yet neglect the coupling between them which can lead to the extraction of highly coupled classes. Therefore, this paper proposes a novel approach that considers the combination of the cohesion and coupling to identify the set of classes that can be extracted from a large class. The proposed approach was empirically evaluated based on real-world Blobs taken from two open-source object-oriented systems. The results of the empirical evaluation revealed that the proposed approach is potentially useful and leads to improvement in the overall quality.