Examining Software Coupling and Cohesion Patterns Using Social Network Analysis

Social network analysis (SNA) is an emerging research area that has gained significant attention in recent years.Analyzing OO program through SNA can provide insights into how a program component, classes and methods interact and collaborate.In fact, an OO program is composed of a set of classes that interact with each other.Considering a class as a node and the interaction as a relationship, we can take advantage from SNA capabilities to the benefit of OO programming.Therefore, SNA is an excellent way for detecting and quantifying coupling and cohesion in an Object Oriented Programming (OOP) based on the class interaction, by analyzing the connections between classes and methods.An accurate coupling and cohesion detection helps developers to optimize codes and improve its overall performance and maintainability.In this paper, we represent four java open source projects (JUnit 5.10.2,Spring 6.1.4,Apache Commons BCEL 6.8.2 and Guava 33.0) as a social network.We also, applied SNA techniques to identify lowly cohesive classes and highly coupled classes.