DocumentCode :
2726644
Title :
ACCD: an algorithm for comprehension-driven clustering
Author :
Tzerpos, Vassilios ; Holt, R.C.
Author_Institution :
Toronto Univ., Ont., Canada
fYear :
2000
fDate :
2000
Firstpage :
258
Lastpage :
267
Abstract :
The software clustering literature contains many different approaches that attempt to automatically decompose software systems. These approaches commonly utilize criteria or measures based on principles such as high cohesion and low coupling, information hiding etc. We present an algorithm that subscribes to a philosophy targeted towards program comprehension and based on subsystem patterns. We discuss the algorithm´s implementation and describe experiments that demonstrate its usefulness
Keywords :
pattern clustering; reverse engineering; software engineering; statistical analysis; ACCD; automatic software system decomposition; comprehension-driven clustering algorithm; high cohesion; information hiding; low coupling; program comprehension; software clustering; subsystem patterns; Biology; Clustering algorithms; Computer industry; Psychology; Software algorithms; Software engineering; Software performance; Software systems; Statistics; Taxonomy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Reverse Engineering, 2000. Proceedings. Seventh Working Conference on
Conference_Location :
Brisbane, Qld.
ISSN :
1095-1350
Print_ISBN :
0-7695-0881-2
Type :
conf
DOI :
10.1109/WCRE.2000.891477
Filename :
891477
Link To Document :
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