A Generic Approach Simplifying Model-to-Model Transformation Chains

  • Gerd Kainz
  • Christian Buckl
  • Alois Knoll
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7590)


The model-driven architecture proposes stepwise model refinement. The resulting model-to-model (M2M) transformation chains can consist of many steps. For realizing the transformations two approaches exist: Exogenous transformations, where input and output use different metamodels, and endogenous transformations, that use the same metamodel for input and output. Due to the particularities of embedded systems, using only endogenous transformations is not appropriate. For exogenous transformations, problems arise with respect to creation and maintenance of the subsequent metamodels. Another problem of these M2M transformation chains is that for one transformation step typically large parts of the model data remain unchanged. The resulting M2M transformation does often include many copy operations that distract the developers from the “real” transformations and increase implementation overhead. This paper introduces a generic approach that solves these issues by a (semi-) automatic metamodel construction and copy operation of unchanged model data between subsequent steps.


Transformation Chain Model-to-Model Transformation Metamodel-to-Metamodel Transformation Model-driven Software Development Model-driven Architecture 


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  1. 1.
    Miller, J., Mukerji, J.: MDA Guide Version 1.0.1 (June 2003)Google Scholar
  2. 2.
    Stahl, T., Völter, M.: Model-Driven Software Development: Technology, Engineering, Management. Wiley (2006)Google Scholar
  3. 3.
    Buckl, C.: Model-Based Development of Fault-Tolerant Real-Time Systems. Dissertation, Technische Universität München, München, Germany (2008)Google Scholar
  4. 4.
    Mens, T., Van Gorp, P.: A taxonomy of model transformation. Electronic Notes in Theoretical Computer Science 152, 125–142 (2006)CrossRefGoogle Scholar
  5. 5.
    Object Management Group (OMG): Meta Object Facility (MOF) 2.0 Query/View/Transformation Specification Version 1.1 (January 2011)Google Scholar
  6. 6.
    Wachsmuth, G.: Metamodel Adaptation and Model Co-adaptation. In: Bateni, M. (ed.) ECOOP 2007. LNCS, vol. 4609, pp. 600–624. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  7. 7.
    Cicchetti, A., Ruscio, D.D., Pierantonio, A.: A metamodel independent approach to difference representation. Journal of Object Technology 6(9), 165–185 (2007)CrossRefGoogle Scholar
  8. 8.
    Schaefer, I., Bettini, L., Damiani, F., Tanzarella, N.: Delta-Oriented Programming of Software Product Lines. In: Bosch, J., Lee, J. (eds.) SPLC 2010. LNCS, vol. 6287, pp. 77–91. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Clarke, D., Helvensteijn, M., Schaefer, I.: Abstract delta modeling. In: Proceedings of the Ninth International Conference on Generative Programming and Component Engineering (GPCE 2010), pp. 13–22 (2010)Google Scholar
  10. 10.
    Object Management Group (OMG): Meta Object Facility (MOF) Core Specification Version 2.0 (January 2006)Google Scholar
  11. 11.
    Buckl, C., Sojer, D., Knoll, A.: FTOS: Model-driven development of fault-tolerant automation systems. In: 15th International Conference on Emerging Technologies and Factory Automation (ETFA 2010), Bilbao, Spain, pp. 1–8 (2010)Google Scholar
  12. 12.
    Buckl, C., Sommer, S., Scholz, A., Knoll, A., Kemper, A., Heuer, J., Schmitt, A.: Services to the field: An approach for resource constrained sensor/actor networks. In: International Conference on Advanced Information Networking and Applications Workshops (WAINA 2009), Bradford, UK, pp. 476–481 (2009)Google Scholar
  13. 13.
    Jouault, F., Kurtev, I.: Transforming Models with ATL. In: Bruel, J.-M. (ed.) MoDELS 2005. LNCS, vol. 3844, pp. 128–138. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  14. 14.
    Batory, D., Azanza, M., Saraiva, J.A.: The Objects and Arrows of Computational Design. In: Czarnecki, K., Ober, I., Bruel, J.-M., Uhl, A., Völter, M. (eds.) MODELS 2008. LNCS, vol. 5301, pp. 1–20. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    Bouzitouna, S., Gervais, M.P.: Composition rules for PIM reuse. In: 2nd European Workshop on Model Driven Architecture with Emphasis on Methodologies and Transformations (EDWMDA 2004), pp. 36–43 (2004)Google Scholar
  16. 16.
    Bouzitouna, S., Gervais, M.P., Blanc, X.: Model reuse in MDA. In: International Conference on Software Engineering Research and Practice (SERP 2005), Las Vegas, USA, pp. 354–360 (2005)Google Scholar
  17. 17.
    Kolovos, D., Rose, L., Paige, R.: The Epsilon Book (2010)Google Scholar
  18. 18.
    Rose, L.M., Kolovos, D.S., Paige, R.F., Polack, F.A.C.: Model Migration with Epsilon Flock. In: Tratt, L., Gogolla, M. (eds.) ICMT 2010. LNCS, vol. 6142, pp. 184–198. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  19. 19.
    Herrmannsdoerfer, M., Benz, S., Juergens, E.: COPE - Automating Coupled Evolution of Metamodels and Models. In: Drossopoulou, S. (ed.) ECOOP 2009. LNCS, vol. 5653, pp. 52–76. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  20. 20.
    Paternostro, M., Hussey, K.: Advanced features of the eclipse modeling framework. In: EclipseCON (March 2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Gerd Kainz
    • 1
  • Christian Buckl
    • 1
  • Alois Knoll
    • 2
  1. 1.fortiss, Cyber-Physical SystemsMunichGermany
  2. 2.Faculty of InformaticsTechnical University MunichGarchingGermany

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