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 -