@article{(Open Science Index):https://publications.waset.org/pdf/10001778,
	  title     = {An Automatic Model Transformation Methodology Based on Semantic and Syntactic Comparisons and the Granularity Issue Involved},
	  author    = {Tiexin Wang and  Sebastien Truptil and  Frederick Benaben},
	  country	= {},
	  institution	= {},
	  abstract     = {Model transformation, as a pivotal aspect of Modeldriven
engineering, attracts more and more attentions both from
researchers and practitioners. Many domains (enterprise engineering,
software engineering, knowledge engineering, etc.) use model
transformation principles and practices to serve to their domain
specific problems; furthermore, model transformation could also be
used to fulfill the gap between different domains: by sharing and
exchanging knowledge. Since model transformation has been widely
used, there comes new requirement on it: effectively and efficiently
define the transformation process and reduce manual effort that
involved in. This paper presents an automatic model transformation
methodology based on semantic and syntactic comparisons, and
focuses particularly on granularity issue that existed in transformation
process. Comparing to the traditional model transformation
methodologies, this methodology serves to a general purpose: crossdomain
methodology. Semantic and syntactic checking
measurements are combined into a refined transformation process,
which solves the granularity issue. Moreover, semantic and syntactic
comparisons are supported by software tool; manual effort is replaced
in this way.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {9},
	  number    = {8},
	  year      = {2015},
	  pages     = {1828 - 1838},
	  ee        = {https://publications.waset.org/pdf/10001778},
	  url   	= {https://publications.waset.org/vol/104},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 104, 2015},
	}