Mining source code elements for comprehending object-oriented systems and evaluating their maintainability

Yiannis Kanellopoulos, Thimios Dimopulos, Christos Tjortjis, Christos Makris
2006 SIGKDD Explorations  
Data mining and its capacity to deal with large volumes of data and to uncover hidden patterns has been proposed as a means to support industrial scale software maintenance and comprehension. This paper presents a methodology for knowledge acquisition from source code in order to comprehend an object-oriented system and evaluate its maintainability. We employ clustering in order to support semi-automated software maintenance and comprehension. A model and associated process are provided, in
more » ... re provided, in order to extract elements from source code. K-Means clustering is then applied on these data, in order to produce system overviews and deductions. The methodology is evaluated on JBoss, a very large Open Source Application Server; results are discussed and conclusions are presented together with directions for future work.
doi:10.1145/1147234.1147240 fatcat:zk6uytpdf5cpjaukzh45ao5mqi