TY  - JOUR
T1  - Generative Automatic Matching Between
Heterogeneous Meta-Model’ Systems
AU - Batouta, Zouhair Ibn AU - Dehbi, Rachid AU - Talea, Mohammed AU - Hajoui, Omar 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 2
SP  - 493
EP  - 500
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.493.500
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.493.500
KW  - Matching
KW  -automation
KW  -different matching approaches
KW  -generative automatic matching
KW  -meta-model
KW  -SWOT analysis
AB  - 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.
ER  -