Learning transformation rules from transformation examples: An approach based on Relational Concept Analysis - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Accéder directement au contenu
Communication Dans Un Congrès Année : 2010

Learning transformation rules from transformation examples: An approach based on Relational Concept Analysis

Résumé

In Model Driven Engineering (MDE), model transformations are basic and primordial entities, thus easing their design and implementation is an important issue. A quite recently proposed way to create model transformations consists in deducing a transformation from examples of transformed models. Examples are easier to write than a transformation program and are often already available. We propose in this paper a method based on a machine learning method of the lattice domain, the Relational Concept Analysis, and an implementation of this method.
Fichier principal
Vignette du fichier
main.pdf (228.35 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

lirmm-00533375 , version 1 (05-11-2010)

Identifiants

Citer

Xavier Dolques, Marianne Huchard, Clémentine Nebut, Philippe Reitz. Learning transformation rules from transformation examples: An approach based on Relational Concept Analysis. EDOC: Enterprise Distributed Object Computing Conference, Oct 2010, Vittoria, Brazil. pp.27-32, ⟨10.1109/EDOCW.2010.32⟩. ⟨lirmm-00533375⟩
124 Consultations
673 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More