@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.} }