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Identifying Metamodel Inaccurate Structures During Metamodel/Constraint Co-Evolution

Elyes Cherfa 1, 2 Soraya Mesli-Kesraoui Chouki Tibermacine 3 Régis Fleurquin 1, 2 Salah Sadou 1, 2 
2 ARCHWARE - Advanced Technologies for Operated Networks
3 MAREL - Models And Reuse Engineering, Languages
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : 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.
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Submitted on : Tuesday, January 11, 2022 - 1:07:08 PM
Last modification on : Friday, August 5, 2022 - 3:03:19 PM
Long-term archiving on: : Tuesday, April 12, 2022 - 6:59:08 PM


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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⟩



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