Zouhair Ibn  Batouta, Rachid  Dehbi, Mohammed  Talea, Omar  Hajoui, 
    Generative Automatic Matching Between
Heterogeneous Meta-Model’ Systems,
    Journal of Engineering and Applied Sciences,
    Volume 13,Issue 2,
    2018,
    Pages 493-500,
    ISSN 1816-949x,
    jeasci.2018.493.500,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2018.493.500)
    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.
    Keywords: Matching;automation;different matching approaches;generative automatic matching;meta-model;SWOT analysis