An automatic model-to-model mapping and transformation methodology to serve model-based systems engineering

An automatic model-to-model mapping and transformation methodology to serve model-based systems... With enterprise collaboration becoming increasingly frequent, the ability of an enterprise to cooperate with others has become one of the core factors in gaining competitive advantage. This trend has led to an urgent requirement to improve cooperation ability. To this end, model-based systems engineering is being adapted so that it can be used to represent and simulate the working processes of enterprises. Model-to-model mappings and transformations, as important aspects in model-based systems engineering, have become two of the key factors in improving the cooperation capabilities of enterprises. However, the foundations for achieving automatic model-to-model transformation have not yet been built. Normally, model transformation rules are built on the basis of model mappings, and model mappings concern semantic or syntactic representations. One of the difficulties in achieving model-to-model mappings and transformations lies in detecting the semantics and semantic relations that are conveyed in different models. This paper presents an automatic model-to-model mapping and transformation methodology, which applies semantic and syntactic checking measurements to detect the meanings and relations between different models automatically. Both of the semantic and syntactic checking measurements are combined into a refined meta-model based model transformation process. To evaluate the performance of this methodology, we demonstrate its applicability with a realistic example. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Information Systems and e-Business Management Springer Journals

An automatic model-to-model mapping and transformation methodology to serve model-based systems engineering

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by Springer-Verlag Berlin Heidelberg
Subject
Business and Management; IT in Business; Information Systems Applications (incl.Internet); Management
ISSN
1617-9846
eISSN
1617-9854
D.O.I.
10.1007/s10257-016-0321-z
Publisher site
See Article on Publisher Site

Abstract

With enterprise collaboration becoming increasingly frequent, the ability of an enterprise to cooperate with others has become one of the core factors in gaining competitive advantage. This trend has led to an urgent requirement to improve cooperation ability. To this end, model-based systems engineering is being adapted so that it can be used to represent and simulate the working processes of enterprises. Model-to-model mappings and transformations, as important aspects in model-based systems engineering, have become two of the key factors in improving the cooperation capabilities of enterprises. However, the foundations for achieving automatic model-to-model transformation have not yet been built. Normally, model transformation rules are built on the basis of model mappings, and model mappings concern semantic or syntactic representations. One of the difficulties in achieving model-to-model mappings and transformations lies in detecting the semantics and semantic relations that are conveyed in different models. This paper presents an automatic model-to-model mapping and transformation methodology, which applies semantic and syntactic checking measurements to detect the meanings and relations between different models automatically. Both of the semantic and syntactic checking measurements are combined into a refined meta-model based model transformation process. To evaluate the performance of this methodology, we demonstrate its applicability with a realistic example.

Journal

Information Systems and e-Business ManagementSpringer Journals

Published: Jun 9, 2016

References

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