Improving Class Cohesion Measurement: Towards a Novel Approach Using Hierarchical Clustering

作     者：Lazhar Sadaoui Mourad Badri Linda Badri 

作者机构：Software Engineering Research Laboratory Department of Mathematics and Computer Science University of Quebec Trois-Rivières Canada 

出 版 物：《Journal of Software Engineering and Applications》 (软件工程与应用（英文）)

年 卷 期：2012年第5卷第7期

页      面：449-458页

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Object-Oriented Classes Cohesion Similarity Clustering Metrics and Empirical Evaluation 

摘      要：Class cohesion is considered as one of the most important object-oriented software attributes. High cohesion is, in fact, a desirable property of software. Many different metrics have been suggested in the last several years to measure the cohesion of classes in object-oriented systems. The class of structural object-oriented cohesion metrics is the most in-vestigated category of cohesion metrics. These metrics measure cohesion on structural information extracted from the source code. Empirical studies noted that these metrics fail in many situations to properly reflect cohesion of classes. This paper aims at exploring the use of hierarchical clustering techniques to improve the measurement of cohesion of classes in object-oriented systems. The proposed approach has been evaluated using three particular case studies. We also used in our study three well-known structural cohesion metrics. The achieved results show that the new approach appears to better reflect the cohesion (and structure) of classes than traditional structural cohesion metrics.