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