Comparing Approaches to Implement Feature Model Composition

Mathieu Acher 1 Philippe Collet 1 Philippe Lahire 1 Robert B. France 2
1 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS
SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
2 CSU - Colorado State University [Fort Collins]
Abstract : The use of Feature Models (FMs) to define the valid combinations of features in Software Product Lines (SPL) is becoming commonplace. To enhance the scalability of FMs, support for composing FMs describing different SPL aspects is needed. Some composition operators, with interesting property preservation capabilities, have already been defined but a comprehensive and efficient implementation is still to be proposed. In this paper, we systematically compare strengths and weaknesses of different implementation approaches. The study provides some evidence that using generic model composition frameworks are not helping much in the realization, whereas a specific solution is finally necessary and clearly stands out by its qualities.
Type de document :
Communication dans un congrès
Sixth European Conference on Modelling Foundations and Applications, Jun 2010, Paris, France. springer, pp.16, 2010, LNCS
Liste complète des métadonnées

Littérature citée [30 références]  Voir  Masquer  Télécharger
https://hal.archives-ouvertes.fr/hal-00484232
Contributeur : Philippe Lahire <>
Soumis le : mardi 18 mai 2010 - 10:54:39
Dernière modification le : mercredi 31 janvier 2018 - 10:24:05
Document(s) archivé(s) le : vendredi 19 octobre 2012 - 14:51:21

Fichier

CameraReady.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00484232, version 1

Collections

UNICE | I3S | UNIV-COTEDAZUR

Citation

Mathieu Acher, Philippe Collet, Philippe Lahire, Robert B. France. Comparing Approaches to Implement Feature Model Composition. Sixth European Conference on Modelling Foundations and Applications, Jun 2010, Paris, France. springer, pp.16, 2010, LNCS. 〈hal-00484232〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

333

Téléchargements de fichiers

576

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD