Work

Software components capture using graph clustering

Year: 2004

Type: conference-paper

Abstract: 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 straightforward 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 by S. Mancoridis et al. (1998) 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.

Source: International Symposium on Micro-NanoMechatronics and Human Science

DOI: 10.1109/wpc.2003.1199205

Authors: Y. Chiricota, F. Jourdan, G. Melancon

Institutions: Université du Québec à Chicoutimi, Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier

Language: English

Topic: Software Engineering Research

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Natural Sciences and Engineering Research Council of Canada

OpenAlex ID: W2163090038