Abstract
Appropriate test models that can satisfy complex constraints are required for testing model management programs in order to build confidence in their correctness. Models have inherently complex structures and are often required to satisfy non-trivial constraints which makes them time consuming, labour intensive and error prone to construct manually. Automated capabilities are therefore required, however, existing fully-automated model generation tools cannot generate models that satisfy arbitrarily complex constraints. In this paper, we propose a semi-automated approach towards the generation of such models. A new framework named Epsilon Model Generator (EMG) that implements this approach is presented. The framework supports the development of model generators that can produce random and reproducible test models that satisfy complex constraints.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
- 3.
- 4.
References
Ali, S., Iqbal, M., Arcuri, A., Briand, L.: A search-based OCL constraint solver for model-based test data generation. In: 11th International Conference on Quality Software (QSIC), pp. 41–50 (2011)
Anastasakis, K., Bordbar, B., Kuster, J.M.: Analysis of model transformations via Alloy. In: 4th Modevva Workshop (2007)
Baudry, B., Ghosh, S., Fleurey, F., France, R., Le Traon, Y., Mottu, J.M.: Barriers to systematic model transformation testing. Commun. ACM 53(6), 139–143 (2010)
Brottier, E., Fleurey, F., Steel, J., Baudry, B., le Traon, Y.: Metamodel-based test generation for model transformations: an algorithm and a tool. In: 17th International Symposium on Software Reliability Engineering, ISSRE 2006, pp. 85–94 (2006)
Dimitris, K., Louis, R., Antonio, G.D., Richard, P.: The Epsilon Book. http://www.eclipse.org/epsilon/doc/book
Duchon, P., Flajolet, P., Louchard, G., Schaeffer, G.: Boltzmann samplers for the random generation of combinatorial structures. Comb. Probab. Comput. 13(4–5), 577–625 (2004)
Eclipse Graphical Modeling Framework, official website. http://www.eclipse.org/gmf-tooling
Ehrig, K., Kuster, J.M., Taentzer, G.: Generating instance models from meta models. Softw. Syst. Model. 8(4), 479–500 (2008)
Ferdjoukh, A., Baert, A.E., Chateau, A., Coletta, R., Nebut, C.: A CSP approach for metamodel instantiation. In: 2013 IEEE 25th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 1044–1051 (2013)
Ferdjoukh, A., Baert, A.E., Bourreau, E., Chateau, A., Coletta, R., Nebut, C.: Instantiation of meta-models constrained with OCL - a CSP approach. In: 2015 3rd International Conference on Model-Driven Engineering and Software Development (MODELSWARD), pp. 213–222, February 2015
Fiorentini, C., Momigliano, A., Ornaghi, M., Poernomo, I.: A constructive approach to testing model transformations. In: Tratt, L., Gogolla, M. (eds.) ICMT 2010. LNCS, vol. 6142, pp. 77–92. Springer, Heidelberg (2010)
Gonzalez, C., Buttner, F., Clariso, R., Cabot, J.: EMFtoCSP: a tool for the lightweight verification of EMF models. In: Software Engineering: Rigorous and Agile Approaches (FormSERA), pp. 44–50 (2012)
James, W., Simon, P.: Generating models using metaheuristic search. In: Proceedings of the Fourth York Doctoral Symposium on Computing, York, pp. 53–60 (2014)
Kolovos, D.S., Paige, R.F., Polack, F.A.C.: The epsilon object language (EOL). In: Rensink, A., Warmer, J. (eds.) ECMDA-FA 2006. LNCS, vol. 4066, pp. 128–142. Springer, Heidelberg (2006)
Kolovos, D.S., Paige, R.F., Polack, F.A.C.: On the evolution of OCL for capturing structural constraints in modelling languages. In: Abrial, J.-R., Glässer, U. (eds.) Rigorous Methods for Software Construction and Analysis. LNCS, vol. 5115, pp. 204–218. Springer, Heidelberg (2009)
Kolovos, D.S., Rose, L.M., Abid, S.B., Paige, R.F., Polack, F.A.C., Botterweck, G.: Taming EMF and GMF using model transformation. In: Rouquette, N., Haugen, Ø., Petriu, D.C. (eds.) MODELS 2010, Part I. LNCS, vol. 6394, pp. 211–225. Springer, Heidelberg (2010)
Martin, G., Jorn, B., Mark, R.: Validating UML and OCL models in USE by automatic snapshot generation. Software 4(4), 386–398 (2005)
Mougenot, A., Darrasse, A., Blanc, X., Soria, M.: Uniform random generation of huge metamodel instances. In: Paige, R.F., Hartman, A., Rensink, A. (eds.) ECMDA-FA 2009. LNCS, vol. 5562, pp. 130–145. Springer, Heidelberg (2009)
Paige, R.F., Kolovos, D.S., Rose, L.M., Drivalos, N., Polack, F.A.C.: The design of a conceptual framework and technical infrastructure for model management language engineering. In: Proceedings of the 14th IEEE International Conference on Engineering of Complex Computer Systems, ICECCS 2009, pp. 162–171. IEEE Computer Society (2009)
Scheidgen, M.: Generation of large random models for benchmarking. In: Proceedings of the 3rd Workshop on Scalable Model Driven Engineering, L’Aquila, Italy, pp. 1–10 (2015)
Sen, S., Baudry, B., Mottu, J.-M.: Automatic model generation strategies for model transformation testing. In: Paige, R.F. (ed.) ICMT 2009. LNCS, vol. 5563, pp. 148–164. Springer, Heidelberg (2009)
Wu, H., Monahan, R., Power, J.: Exploiting attributed type graphs to generate metamodel instances using an SMT solver. In: 2013 International Symposium on Theoretical Aspects of Software Engineering (TASE), pp. 175–182 (2013)
Xiao, H., Tian, Z., Zhiyi, M., Weizhong, S.: Randomized model generation for performance testing of model transformations. In: 38th Annual Computer Software and Applications Conference (COMPSAC), pp. 11–20 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Popoola, S., Kolovos, D.S., Rodriguez, H.H. (2016). EMG: A Domain-Specific Transformation Language for Synthetic Model Generation. In: Van Gorp, P., Engels, G. (eds) Theory and Practice of Model Transformations. ICMT 2016. Lecture Notes in Computer Science(), vol 9765. Springer, Cham. https://doi.org/10.1007/978-3-319-42064-6_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-42064-6_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42063-9
Online ISBN: 978-3-319-42064-6
eBook Packages: Computer ScienceComputer Science (R0)