DocumentCode :
1928623
Title :
Evaluating similarity measures for software decompositions
Author :
Wen, Zhihua ; Tzerpos, Vassilios
Author_Institution :
York Univ., Toronto, Ont., Canada
fYear :
2004
fDate :
11-14 Sept. 2004
Firstpage :
368
Lastpage :
377
Abstract :
One of the central questions that a similarity measure for software decompositions has to address is whether to consider discrepancies in terms of the nodes of a particular decomposition, or assess similarity based on differences in clustering the edges of the system´s dependency graph. We argue that considering nodes or edges in isolation is too one-sided. We outline shortcomings of previous approaches, and introduce the first dissimilarity measure that takes both nodes and edges into account. We also present experiments on real and synthetic data sets that illustrate the differences between various measures.
Keywords :
software metrics; software performance evaluation; edge clustering; similarity measure evaluation; software decomposition; system dependency graph; Benchmark testing; Clustering algorithms; Information retrieval; Particle measurements; Software algorithms; Software maintenance; Software measurement; Software systems; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Maintenance, 2004. Proceedings. 20th IEEE International Conference on
ISSN :
1063-6773
Print_ISBN :
0-7695-2213-0
Type :
conf
DOI :
10.1109/ICSM.2004.1357822
Filename :
1357822
Link To Document :
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