DocumentCode :
1977628
Title :
Software Architecture Decomposition Using Clustering Techniques
Author :
Alkhalid, Abdulaziz ; Chung-Horng Lung ; Duo Liu ; Ajila, Samuel
Author_Institution :
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
fYear :
2013
fDate :
22-26 July 2013
Firstpage :
806
Lastpage :
811
Abstract :
While applying clustering techniques to software system decomposition, the software designer faces two practical issues: (1) determination of the number of clusters that will be mapped to software modules and (2) determination of a specific cluster or software module for some highly coupled components. This paper presents an approach for software architecture decomposition with an emphasis on finding solutions to those two issues. The approach uses fuzzy c-means clustering together with three hierarchical agglomerative clustering methods and the adaptive K-nearest neighbor algorithm. We applied the approach to real industrial software systems. The results show that our approach provides objective and insightful information to the software designer in dealing with those two issues.
Keywords :
fuzzy set theory; pattern clustering; software architecture; adaptive K-nearest neighbor algorithm; fuzzy c-means clustering; hierarchical agglomerative clustering methods; real industrial software systems; software architecture decomposition; software designer; software modules; software system decomposition; Clustering algorithms; Computer architecture; Protocols; Software algorithms; Software architecture; Software systems; A-KNN; CLINK; SLINK; Software architecture; WPGMA; clustering; fuzzy c-means; reengineering; software decomposition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Software and Applications Conference (COMPSAC), 2013 IEEE 37th Annual
Conference_Location :
Kyoto
Type :
conf
DOI :
10.1109/COMPSAC.2013.132
Filename :
6649921
Link To Document :
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