Eighth Asia-Pacific Software Engineering Conference (APSEC'01)
Identifying Candidate Objects Using Hierarchical Clustering Analysis
Macao, China
December 04-December 07
ISBN: 0-7695-1408-1
Clustering analysis has rarely been studied as a technique for object identification method, although it has long been broadly employed in data classification in a wide range of research areas. In this paper, we propose a review of clustering analysis method and a scheme for applying hierarchical clustering analysis to facilitate identification of candidate objects in procedural source code. The study shows that clustering analysis is able to correctly group functions to meaningful clusters even though functions are written in an interleaved order Clustering analysis can work well with the modular case and the tangled case without any additional support.