An Automatic Model Transformation Methodology Based on Semantic and Syntactic Comparisons and the Granularity Issue Involved

Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

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.

Keywords: Automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107339

References:

[1] DC. Schmidt, Model-Driven Engineering. IEEE Computer, February 2006 (Vol.39, No. 2) pp. 25-31.
[2] J. Touzi, JP. Lorré, F. Bénaben, Interoperability through Model-based Generation: The Case of the Collaborative Information System (CIS) (J)]. Enterprise Interoperability, 2007: 407.
[3] M.D. Del Fabro, P. Valduriez, Towards the efficient development of model transformations using model weaving and matching transformations. Software & System Modeling, July 2009, Volume 8, Issue 3, pp 305-324.
[4] T. Wang, S. Truptil, F. Bénaben, “Semantic approach to automatically defined model transformation.” International Conference on Model-Driven Engineering and Software Development (MODELSWARD 2014), pp. 340-347.
[5] F. Jouault, F. Allilaire, J. Bézivin, I. Kurtev, ATL: A model transformation tool. Science of Computer Programming. 2007, Volume 72, Issues 1–2.
[6] M.D. Del Fabro, J. Bézivin, F. Jouault, E. Breton, AMW: A Generic Model Weaver. 2005, 1ère Journées sur l'Ingénierie Dirigée par les Modèles: Paris.
[7] OMG: QVT. Meta Object Facility (MOF) 2.0 Query/View/ Transformation Specification OMG (2008) http://www.omg.org/spec/QVT/1.0/PDF
[8] D. Varr´o, A. Balogh, The model transformation language of the viatra2 framework. Sci. Comput. Program 68(3), 214–234 (2007).
[9] D. Varr´o, A. Pataricza, VPM: A visual, precise and multilevel meta-modeling framework for describing mathematical domains and UML (the mathematics of metamodeling is metamodeling mathematics), Software. Syst. Model. 2 (3) (2003) 187–210.
[10] G. Karsai, A. Agrawal, F. Shi, J. Sprinkle, “On the use of graph transformation in the formal specification of model interpreters”, J. Univ. Comput. Sci. 9 (11) (2003) 1296–1321.
[11] D.V. Castro, E. Maros, J.M. Vara, Applying CIM-to-PIM model transformations for the service-oriented development of information systems. Information and Software Technology, 2011, Volume 53, Issue 1, Pages 87–105.
[12] R. Grangel, M. Bigand, J.P. Bourey, “Transformation of decisional models into UML: application to GRAI grids”. International Journal of Computer Integrated Manufacturing, 2010, Volume 23, Issue 7.
[13] VA. Bollati, JM. Vara, A. Jiménez, E. Marcos, Applying MDE to the (semi-)automatic development of model transformations. Information and Software Technology 2013; 55(4):699–718.
[14] K. Czarnecki, S. Helsen, Classification of Model Transformation Approaches. OOPSLA’03, 2003, Workshop on Generative Techniques in the Context of Model-Driven Architecture.
[15] M. Herrmannsdoerfer, S. Benz, E. Juergens, COPE - automating coupled evolution of metamodels and models. In: Drossopoulou, S. (ed.) ECOOP 2009 – Object-Oriented Programming. LNCS, vol. 5653, pp. 52–76. Springer, Heidelberg.
[16] F. Bénaben, W. Mu, S. Truptil, H. Pingaud, “Information Systems design for emerging ecosystems.” 2010, 4th IEEE International Conference on Digital Ecosystems and Technologies (DEST).
[17] J. Bezivin, “Model driven engineering: An emerging technical space,” in Generative and Transformational Techniques in Software Engineering, International Summer School -GTTSE, 2006, pp. 36–64.
[18] W. C. William, R. Pradeep, E. F. Stephen, “A Comparison of String Metrics for Matching Names and Records.” KDD Workshop on Data Cleaning and Object Consolidation, 2003, Vol. 3.
[19] H. Wilbert, “Measuring Dialect Pronunciation Differences using Levenshtein Distance.” Ph.D. thesis, 2004, Rijksuniversiteit Groningen.
[20] X. Huang, C. Zhou, “An OWL-based WordNet lexical ontology.” Journal of Zhejiang University, 2007, pp. 864-870.
[21] D. Abril, G. Navarro-Arribas, V. Torra, Choquet integral for record linkage Ann. Oper. Res., 195 (1) (2012), pp. 97–110.