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Empirical comparison of two class model normalization techniques: Obstacles and questions

Jean-Rémy Falleri 1 Marianne Huchard 1 Clémentine Nebut 1
1 MAREL - Models And Reuse Engineering, Languages
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Designing accurate models is a true challenge for model driven engineering approach. We are currently exploring techniques derived from Formal Concept Analysis (FCA) theory for finding possible class, association, attribute or method generalizations in models with the aim of improving their abstraction level. Using four models, we compare classical FCA approach to Relational Concept Analysis (RCA) which allows to discover more subtle generalizations. Interestingly, expected combinatorial explosion does occur in all cases when using RCA, making it a feasible solution in a special range of models. The study highlights several difficulties, including the need for costly and subjective human intervention in assessing or filtering the results.
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Submitted on : Friday, September 19, 2008 - 8:55:34 AM
Last modification on : Monday, October 11, 2021 - 1:24:04 PM
Long-term archiving on: : Monday, October 8, 2012 - 1:20:08 PM


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  • HAL Id : lirmm-00322906, version 1



Jean-Rémy Falleri, Marianne Huchard, Clémentine Nebut. Empirical comparison of two class model normalization techniques: Obstacles and questions. ESMDE'08: Workshop on Empirical Studies of Model-Driven Engineering, Sep 2008, Toulouse, France. pp.21-30. ⟨lirmm-00322906⟩



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