Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
Building computer systems has become increasingly difficult, this is essentially due to the great number of existing solutions. The aim of this study is to propose a new approach allowing the matching between meta-models of different systems, this will allow the generation between models conforming to these connected meta-models. First, we will elaborate a taxonomy study on existing approaches, then we present the architecture of our generative matching approach named GAM (Generative Automatic Matching), after that, we will introduce a case study explaining our approach. Finally, we will conclude by a SWOT analysis between the different matching approaches.
How to cite this article:
Zouhair Ibn Batouta, Rachid Dehbi, Mohammed Talea and Omar Hajoui. Generative Automatic Matching Between
Heterogeneous Meta-Model’ Systems.
DOI: https://doi.org/10.36478/jeasci.2018.493.500
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.493.500