Abstract
The use of intelligent computational techniques to improve the software engineering process is a problem of increasing interest in the literature. This paper is focused on the use of these techniques with the aim to assist in the process of software libraries matching. Most integration systems only take into account the information about the structural component of the concepts. However, many conventional data models consider both structural and behavioral knowledge. In this paper, a novel approach that uses both kinds of knowledge is presented. To do that, multiple criteria that can be taken into account to determine class matches are considered, including those that are related to this new behavioral information. These criteria are then integrated into a hierarchical fuzzy multicriteria decision making model.
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Marín, N., Árcija, C.S., Vila, M.A. (2011). A Fuzzy Framework for Software Libraries Matching. In: Lee, G., Howard, D., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2011. Communications in Computer and Information Science, vol 206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24106-2_78
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DOI: https://doi.org/10.1007/978-3-642-24106-2_78
Publisher Name: Springer, Berlin, Heidelberg
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