Exploratory Analysis of Co-Change Graphs for Code Refactoring

Abstract. Version Control Systems (VCS) have always played an essential role for developing reliable software. Recently, many new ways of utilizing the information hidden in VCS have been discovered. Clustering layouts of software systems using VCS is one of them. It reveals groups of related artifacts of the software system, which can be visualized for easier exploration. In this paper we use an Expectation Maximization (EM) based probabilistic clustering algorithm and visualize the clustered modules using a compound node layout algorithm. Our experiments with repositories of two medium size software tools give promising results indicating improvements over many previous approaches. Key words: Clustering, Software artifacts, Expectation Maximization,

• Type: Conference
• Year: 2009
• Where: AI
• Authors: Hassan Khosravi, Recep Colak
• Keywords: AI 2009, Artificial Intelligence, Expectation Maximization, Probabilistic Clustering Algorithm, Software System