Title :
Methods for selecting and improving software clustering algorithms
Author :
Shtern, Mark ; Tzerpos, Vassilios
Author_Institution :
York Univ., Toronto, ON
Abstract :
Several software clustering algorithms have been proposed in the literature, each with its own strengths and weaknesses. Most of these algorithms have been applied to particular software systems with considerable success. However, the question of how to select a software clustering algorithm that is best suited for a specific software system remains unanswered. In this paper, we introduce a method for the selection of a software clustering algorithm for specific needs. The proposed method is based on a newly introduced formal description template for software clustering algorithms. Using the same template, we also introduce a method for software clustering algorithm improvement.
Keywords :
formal specification; pattern clustering; formal description template; software clustering algorithm selection; software system clustering algorithm improvement; Algorithm design and analysis; Clustering algorithms; Guidelines; Heuristic algorithms; Software algorithms; Software maintenance; Software quality; Software standards; Software systems; Terminology;
Conference_Titel :
Program Comprehension, 2009. ICPC '09. IEEE 17th International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-3998-0
Electronic_ISBN :
1092-8138
DOI :
10.1109/ICPC.2009.5090051