@article{MAKHILLJEAS201813215467,
    title = {Generative Automatic Matching Between
Heterogeneous Meta-Model’ Systems},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {13},
    number = {2},
    pages = {493-500},
    year = {2018},
    issn = {1816-949x},
    doi = {jeasci.2018.493.500},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2018.493.500},
    author = {Zouhair Ibn,Rachid,Mohammed and},
    keywords = {Matching,automation,different matching approaches,generative automatic matching,meta-model,SWOT analysis},
    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.}
    }