Similarity assessment of UML class diagrams using a greedy algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

21 Scopus citations

Abstract

During the early stages of software development, engineers find themselves dealing with a large collection of models. Lack of efficient management of these models results in duplicated artifacts, ineffective reuse, and an aggravated maintenance effort. Models' matching is at the core of different model management operations such as models' evolution, consolidation, and retrieval. It is a kind of a combinatorial problem. The difficulty of the problem comes in two main streams, the similarity assessment metrics and the matching algorithms. In this paper, we present a greedy-based algorithm for matching UML class diagrams based on their lexical, internal, neighborhood similarity, and a combination of them. Additionally the paper empirically compares the performance of the proposed algorithm against the simulated annealing algorithm in terms of the matching accuracy and time.

Original languageEnglish
Title of host publication2014 International Computer Science and Engineering Conference, ICSEC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages228-233
Number of pages6
ISBN (Electronic)9781479949632
DOIs
StatePublished - 2014

Publication series

Name2014 International Computer Science and Engineering Conference, ICSEC 2014

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Greedy matching algorithm
  • Model matching
  • Reuse
  • Similarity metrics

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Health Informatics
  • General Computer Science

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