Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/13801
Title: A hybrid software component clustering and retrieval scheme using an entropy-based fuzzy k-modes algorithm
Authors: Andreou, Andreas S. 
Stylianou, Constantinos 
Keywords: Clustering algorithms
Category: Electrical Engineering - Electronic Engineering - Information Engineering
Field: Engineering and Technology
Issue Date: Oct-2007
Source: 19th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2007, Patras, Greece, 29 October 2007 through 31 October 2007
Conference: International Conference on Tools with Artificial Intelligence 
Abstract: Modern software development is currently seeking new paths to improve quality and meet time and cost constraints. Reuse of existing software components is considered one of these paths. However, this process experiences significant problems related to efficiently maintaining component repositories, and, moreover, providing the means to discover and retrieve the most suitable ones. This paper aims to provide a methodology to improve the component-based software development process. Specifically, its objective is to introduce an approach that reduces the time to locate suitable software components. The suggested methodology meets the requirements for the efficient searching of components in repositories and also addresses the need for adequate retrieval of the most suitable software components based on the needs of developers. To achieve this we employ a combination of partitional clustering algorithms borrowed from the field of computational intelligence and fuzzy logic thus creating a subset of the available components that are most suitable to the developers' preferences. © 2007 IEEE.
ISBN: 076953015X
978-0-7695-3015-4
ISSN: 2375-0197
DOI: 10.1109/ICTAI.2007.100
Rights: IEEE
Type: Article
Appears in Collections:Άρθρα/Articles

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