DocumentCode
3342765
Title
MoJo: a distance metric for software clusterings
Author
Tzerpos, Vassilios ; Holt, R.C.
Author_Institution
Toronto Univ., Ont., Canada
fYear
1999
fDate
6-8 Oct 1999
Firstpage
187
Lastpage
193
Abstract
The software clustering problem has attracted much attention recently, since it is an integral part of the process of reverse engineering large software systems. A key problem in this research is the difficulty in comparing different approaches in an objective fashion. In this paper, we present a metric, called MoJo (Move-Join), that can be used in evaluating the similarity of two different decompositions of a software system. Our metric calculates a distance between two partitions of the same set of software resources. We begin by introducing the model we use. Then we present a heuristic algorithm that calculates the distance in an efficient fashion. Finally, we discuss some experiments that showcase the performance of the algorithm and the effectiveness of the metric
Keywords
heuristic programming; reverse engineering; software metrics; software performance evaluation; MoJo software metric; algorithm performance; cluster joining; cluster moving; distance metric; heuristic algorithm; large software systems; reverse engineering; software clusterings; software resource partitioning; software system dcomposition; Electrical capacitance tomography; Feedback; Hardware; Reverse engineering; Software measurement; Software systems; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Reverse Engineering, 1999. Proceedings. Sixth Working Conference on
Conference_Location
Atlanta, GA
Print_ISBN
0-7695-0303-9
Type
conf
DOI
10.1109/WCRE.1999.806959
Filename
806959
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