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Software Components Capture Using Graph Clustering
Portland, Oregon, USA May 10-May 11
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WPC.2003.119920511th IEEE International Workshop on P ...
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Yves Chiricota, Université du Québec à Chicoutimi
We describe a simple fast computing and easy to implement method for finding relatively good clusterings of software systems. Our method relies on the ability to compute the strength of an edge in a graph by applying a straight-forward metric defined in terms of the neighborhoods of its end vertices. The metric is used to identify the weak edges of the graph, which are momentarily deleted to break it into several components. We study the quality metric MQ introduced in [5 ] and exhibit mathematical properties that make it a good measure for clustering quality. Letting the threshold weakness of edges vary defines a path, i.e. a sequence of clusterings in the solution space (of all possible clustering of the graph). This path is described in terms of a curve linking MQ to the weakness of the edges in the graph.
Citation:
Yves Chiricota, Fabien Jourdan, Guy Melançon, "Software Components Capture Using Graph Clustering," icpc, pp.217, 11th IEEE International Workshop on Program Comprehension (IWPC'03), 2003
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