Bottom-Up Meta-Modelling: An Interactive Approach

  • Jesús Sánchez-Cuadrado
  • Juan de Lara
  • Esther Guerra
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7590)


The intensive use of models in Model-Driven Engineering (MDE) raises the need to develop meta-models with different aims, like the construction of textual and visual modelling languages and the specification of source and target ends of model-to-model transformations. While domain experts have the knowledge about the concepts of the domain, they usually lack the skills to build meta-models. These should be tailored according to their future usage and specific implementation platform, which demands knowledge available only to engineers with great expertise in MDE platforms. These issues hinder a wider adoption of MDE both by domain experts and software engineers.

In order to alleviate this situation we propose an interactive, iterative approach to meta-model construction enabling the specification of model fragments by domain experts, with the possibility of using informal drawing tools like Dia. These fragments can be annotated with hints about the intention or needs for certain elements. A meta-model is automatically induced, which can be refactored in an interactive way, and then compiled into an implementation meta-model using profiles and patterns for different platforms and purposes.


Meta-Modelling Domain-Specific Modelling Languages Interactive Meta-Modelling Meta-Model Design Exploration 


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  1. 1.
    Baldwin, C.Y., Clark, K.B.: Design Rules: The Power of Modularity, vol. 1. The MIT Press (2000)Google Scholar
  2. 2.
    Cho, H., Gray, J.: Design patterns for metamodels. In: DSM 2011 (2011)Google Scholar
  3. 3.
    Cho, H., Gray, J., Syriani, E.: Creating visual domain-specific modeling languages from end-user demonstration. In: MiSE 2012 (2012)Google Scholar
  4. 4.
    Cho, H., Sun, Y., Gray, J., White, J.: Key challenges for modeling language creation by demonstration. In: ICSE 2011 Workshop on Flexible Modeling Tools (2011)Google Scholar
  5. 5.
    Cicchetti, A., Ruscio, D.D., Eramo, R., Pierantonio, A.: Automating co-evolution in model-driven engineering. In: EDOC 2008, pp. 222–231 (2008)Google Scholar
  6. 6.
    Cicchetti, A., Ruscio, D.D., Pierantonio, A.: Managing Model Conflicts in Distributed Development. In: Czarnecki, K., Ober, I., Bruel, J.-M., Uhl, A., Völter, M. (eds.) MODELS 2008. LNCS, vol. 5301, pp. 311–325. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  7. 7.
    Cicchetti, A., Ruscio, D.D., Pierantonio, A., Kolovos, D.: A test-driven approach for metamodel development. In: Emerging Technologies for the Evolution and Maintenance of Software Models, pp. 319–342. IGI Global (2012)Google Scholar
  8. 8.
    de Lara, J., Guerra, E.: Deep Meta-modelling with MetaDepth. In: Vitek, J. (ed.) TOOLS 2010. LNCS, vol. 6141, pp. 1–20. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Egyed, A.: Automatically detecting and tracking inconsistencies in software design models. IEEE TSE 37(2), 188–204 (2011)Google Scholar
  10. 10.
    Fowler, M.: Refactoring. Improving the Design of Existing Code. Addison-Wesley (1999)Google Scholar
  11. 11.
    Izquierdo, J.L.C., Cabot, J.: Community-driven language development. In: MiSE 2012 (2012)Google Scholar
  12. 12.
    Javed, F., Mernik, M., Gray, J., Bryant, B.R.: MARS: A metamodel recovery system using grammar inference. Inf. & Sof. Technology 50(9-10), 948–968 (2008)CrossRefGoogle Scholar
  13. 13.
    Karsai, G., Krahn, H., Pinkernell, C., Rumpe, B., Schneider, M., Völkel, S.: Design guidelines for domain specific languages. In: DSM 2009, pp. 7–13 (2009)Google Scholar
  14. 14.
    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: Petriu, D.C., Rouquette, N., Haugen, Ø. (eds.) MODELS 2010, Part I. LNCS, vol. 6394, pp. 211–225. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  15. 15.
    Liquiere, M., Sallantin, J.: Structural machine learning with galois lattice and graphs. In: ICML 1998, pp. 305–313. Morgan Kaufmann (1998)Google Scholar
  16. 16.
    Maoz, S., Ringert, J.O., Rumpe, B.: Modal Object Diagrams. In: Mezini, M. (ed.) ECOOP 2011. LNCS, vol. 6813, pp. 281–305. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  17. 17.
    Mens, T.: A state-of-the-art survey on software merging. IEEE TSE 28(5), 449–462 (2002)Google Scholar
  18. 18.
    Metamodel refactorings,
  19. 19.
    Nierstrasz, O.: Ten things I hate about object-oriented programming. Journal of Object Technology 9(5) (2010)Google Scholar
  20. 20.
    Paige, R.F., Brooke, P.J., Ostroff, J.S.: Specification-driven development of an executable metamodel in Eiffel. In: WISME 2004 (2004)Google Scholar
  21. 21.
    Perera, R.: First-Order Interactive Programming. In: Carro, M., Peña, R. (eds.) PADL 2010. LNCS, vol. 5937, pp. 186–200. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  22. 22.
    Sadilek, D.A., Weißleder, S.: Towards automated testing of abstract syntax specifications of domain-specific modeling languages. In: CEUR Workshop Proceedings,, vol. 324, pp. 21–29 (2008)Google Scholar
  23. 23.
    Schäfer, C., Kuhn, T., Trapp, M.: A pattern-based approach to DSL development. In: DSM 2011, pp. 39–46 (2011)Google Scholar
  24. 24.
    Steinberg, D., Budinsky, F., Paternostro, M., Merks, E.: EMF: Eclipse Modeling Framework, 2nd edn. Addison-Wesley Professional (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jesús Sánchez-Cuadrado
    • 1
  • Juan de Lara
    • 1
  • Esther Guerra
    • 1
  1. 1.Universidad Autónoma de MadridSpain

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