Identifying Metamodel Inaccurate Structures During Metamodel/Constraint Co-Evolution - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier
Communication Dans Un Congrès Année : 2021

Identifying Metamodel Inaccurate Structures During Metamodel/Constraint Co-Evolution

Résumé

Metamodels are subject to evolution over their lifetime. UML metamodel for instance evolved through different versions, ranging from 0.8 to 2.5 minors. These metamodels are sometimes accompanied with constraints defined using OCL (Object Constraint Language). Many works in the literature developed methods for managing and assisting the co-evolution of metamodels and their constraints. These methods enable a developer to update, in an automated (or semi-automated) way, the constraints associated to a metamodel starting from the deltas identified between versions of this metamodel. In this work we complement this assistance by notifying the developer with potential inaccurate structures in the metamodel that may be introduced during evolution. We introduce in this paper an original evolution assistance method which focuses rather on the problem (notifying metamodel inaccurate structures) than on the solution (generating OCL constraints using patterns of them). The ultimate goal of this assistance is not only to enable the developer to complete existing/updated constraints with new ones, but also to accompany her/him to further check existing constraints and to test whether they still hold. A case study is presented to show the relevance of the method.
Fichier principal
Vignette du fichier
ECetAl_MODELS_2021.pdf (425.74 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

lirmm-03521022 , version 1 (11-01-2022)

Identifiants

Citer

Elyes Cherfa, Soraya Mesli-Kesraoui, Chouki Tibermacine, Régis Fleurquin, Salah Sadou. Identifying Metamodel Inaccurate Structures During Metamodel/Constraint Co-Evolution. MODELS 2021 - ACM/IEEE 24th International Conference on Model Driven Engineering Languages and Systems, Oct 2021, Fukuoka, Japan. pp.24-34, ⟨10.1109/MODELS50736.2021.00012⟩. ⟨lirmm-03521022⟩
81 Consultations
137 Téléchargements

Altmetric

Partager

More