Abstract
We propose a genetic programming-based approach to automatically learn model transformation rules from prior transformation pairs of source-target models used as examples. Unlike current approaches, ours does not need fine-grained transformation traces to produce many-to-many rules. This makes it applicable to a wider spectrum of transformation problems. Since the learned rules are produced directly in an actual transformation language, they can be easily tested, improved and reused. The proposed approach was successfully evaluated on well-known transformation problems that highlight three modeling aspects: structure, time constraints, and nesting.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Balogh, Z., Varrò, D.: Model transformation by example using inductive logic programming. Soft. and Syst. Modeling 8 (2009)
Banzhaf, W.: Genetic Programming: An Introduction on the Automatic Evolution of Computer Programs and Its Applications. Morgan Kaufmann Publishers (1998)
Czarnecki, K., Helsen, S.: Feature-based survey of model transformation approaches. IBM Systems Journal 45(3) (2006)
Dolques, X., Huchard, M., Nebut, C., Reitz, P.: Learning transformation rules from transformation examples: An approach based on relational concept analysis. In: Int. Enterprise Distributed Object Computing Workshops (2010)
Faunes, M., Sahraoui, H., Boukadoum, M.: Generating model transformation rules from examples using an evolutionary algorithm. In: Aut. Soft. Engineering (ASE) (2012)
García-Magariño, I., Gómez-Sanz, J.J., Fuentes-Fernández, R.: Model transformation by-example: An algorithm for generating many-to-many transformation rules in several model transformation languages. In: Paige, R.F. (ed.) ICMT 2009. LNCS, vol. 5563, pp. 52–66. Springer, Heidelberg (2009)
Grønmo, R., Møller-Pedersen, B.: From UML 2 sequence diagrams to state machines by graph transformation. Journal of Object Technology 10 (2011)
Hill, E.F.: Jess in Action: Java Rule-Based Systems (2003)
Jouault, F., Kurtev, I.: Transforming models with ATL. In: Bruel, J.-M. (ed.) MoDELS 2005. LNCS, vol. 3844, pp. 128–138. Springer, Heidelberg (2006)
Kessentini, M., Sahraoui, H.A., Boukadoum, M.: Model transformation as an optimization problem. In: Czarnecki, K., Ober, I., Bruel, J.-M., Uhl, A., Völter, M. (eds.) MODELS 2008. LNCS, vol. 5301, pp. 159–173. Springer, Heidelberg (2008)
Kessentini, M., Sahraoui, H.A., Boukadoum, M., Omar, O.B.: Search-based model transformation by example. Soft. and Syst. Modeling 11(2) (2012)
Kessentini, M., Wimmer, M., Sahraoui, H., Boukadoum, M.: Generating transformation rules from examples for behavioral models. In: Proc. of the 2nd Int. WS on Behaviour Modelling: Foundation and Applications (2010)
Koza, J., Poli, R.: Genetic programming. In: Search Methodologies (2005)
Langer, P., Wimmer, M., Kappel, G.: Model-to-model transformations by demonstration. In: Tratt, L., Gogolla, M. (eds.) ICMT 2010. LNCS, vol. 6142, pp. 153–167. Springer, Heidelberg (2010)
Mohagheghi, P., Gilani, W., Stefanescu, A., Fernandez, M.: An empirical study of the state of the practice and acceptance of model-driven engineering in four industrial cases. In: Empirical Software Engineering
Moore, G.: Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers. HarperCollins (2002)
Pachet, F., Perrot, J.: Rule firing with metarules. In: SEKE (1994)
Ratcliff, S., White, D.R., Clark, J.A.: Searching for invariants using genetic programming and mutation testing. In: GECCO (2011)
Repenning, A., Perrone, C.: Programming by example: programming by analogous examples. Commun. ACM 43(3) (2000)
Saada, H., Dolques, X., Huchard, M., Nebut, C., Sahraoui, H.: Generation of operational transformation rules from examples of model transformations. In: France, R.B., Kazmeier, J., Breu, R., Atkinson, C. (eds.) MODELS 2012. LNCS, vol. 7590, pp. 546–561. Springer, Heidelberg (2012)
Schmidt, D.C.: Model-driven engineering. IEEE Computer 39(2) (2006)
Strommer, M., Wimmer, M.: A framework for model transformation by-example: Concepts and tool support. In: Paige, R.F., Meyer, B. (eds.) TOOLS EUROPE 2008. LNBIP, vol. 11, pp. 372–391. Springer, Heidelberg (2008)
Sun, Y., White, J., Gray, J.: Model transformation by demonstration. In: Schürr, A., Selic, B. (eds.) MODELS 2009. LNCS, vol. 5795, pp. 712–726. Springer, Heidelberg (2009)
Varró, D.: Model transformation by example. In: Wang, J., Whittle, J., Harel, D., Reggio, G. (eds.) MoDELS 2006. LNCS, vol. 4199, pp. 410–424. Springer, Heidelberg (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Faunes, M., Sahraoui, H., Boukadoum, M. (2013). Genetic-Programming Approach to Learn Model Transformation Rules from Examples. In: Duddy, K., Kappel, G. (eds) Theory and Practice of Model Transformations. ICMT 2013. Lecture Notes in Computer Science, vol 7909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38883-5_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-38883-5_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38882-8
Online ISBN: 978-3-642-38883-5
eBook Packages: Computer ScienceComputer Science (R0)