A Feature-Based Approach for Variability Exploration and Resolution in Model Transformation Migration

  • Davide Di Ruscio
  • Juergen Etzlstorfer
  • Ludovico Iovino
  • Alfonso Pierantonio
  • Wieland Schwinger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10376)


The key to success with Model-Driven Engineering is the ability to maintain metamodels and their related artifacts consistent over time. Metamodels can evolve under evolutionary pressure that arises when clients and users express the need for enhancements. However, metamodel changes come at the price of compromising metamodel-related artifacts, including model transformations, necessitating their migration to again conform to the evolved metamodel. Restoring conformance of transformations is intrinsically difficult since a multitude of possible migration alternatives exist, which are unfeasible to be inspected manually. In this paper, we present an approach to explore variability in model transformation migration. Employing a feature-based representation of several possible transformation migrations, the approach permits modelers to explore and explicitly discover differences and conflicts among them. Once the desired migration alternatives are selected, the actual migration program is generated and executed by exploiting the EMFMigrate platform.



This work has been partly funded by the Austrian Science Fund (FWF) under grant P 28519-N31 and the OeAD under grant WTZ AR18/2013 and WTZ AR10/2015.


  1. 1.
    Bancilhon, F., Spyratos, N.: Update semantics of relational views. ACM Trans. Database Syst. (TODS) 6(4), 557–575 (1981)CrossRefzbMATHGoogle Scholar
  2. 2.
    Beuche, D., Papajewski, H., Schröder-Preikschat, W.: Variability management with feature models. Sci. Comput. Program. 53(3), 333–352 (2004)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Cicchetti, A., Di Ruscio, D., Pierantonio, A.: A metamodel independent approach to difference representation. J. Object Technol. 6(9), 165–185 (2007)CrossRefGoogle Scholar
  4. 4.
    Cicchetti, A., Ruscio, 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). doi: 10.1007/978-3-540-87875-9_23 CrossRefGoogle Scholar
  5. 5.
    Cicchetti, A., Ruscio, D.D., Eramo, R., Pierantonio, A.: Automating co-evolution in model-driven engineering. In: Proceedings of EDOC, pp. 222–231. IEEE (2008)Google Scholar
  6. 6.
    Di Ruscio, D., Iovino, L., Pierantonio, A.: Coupled evolution in model-driven engineering. IEEE Softw. 29(6), 78–84 (2012)CrossRefzbMATHGoogle Scholar
  7. 7.
    Di Ruscio, D., Iovino, L., Pierantonio, A.: Evolutionary togetherness: how to manage coupled evolution in metamodeling ecosystems. In: Ehrig, H., Engels, G., Kreowski, H.-J., Rozenberg, G. (eds.) ICGT 2012. LNCS, vol. 7562, pp. 20–37. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-33654-6_2 CrossRefGoogle Scholar
  8. 8.
    Di Ruscio, D., Iovino, L., Pierantonio, A.: A methodological approach for the coupled evolution of metamodels and ATL transformations. In: Duddy, K., Kappel, G. (eds.) ICMT 2013. LNCS, vol. 7909, pp. 60–75. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-38883-5_9 CrossRefGoogle Scholar
  9. 9.
    Garcés, K., Vara, J.M., Jouault, F., Marcos, E.: Adapting transformations to metamodel changes via external transformation composition. Softw. Syst. Model. 13, 789–806 (2013)CrossRefGoogle Scholar
  10. 10.
    García, J., Diaz, O., Azanza, M.: Model transformation co-evolution: a semi-automatic approach. In: Czarnecki, K., Hedin, G. (eds.) SLE 2012. LNCS, vol. 7745, pp. 144–163. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-36089-3_9 CrossRefGoogle Scholar
  11. 11.
    Guerra, E., de Lara, J., Kolovos, D.S., Paige, R.F., dos Santos, O.M.: Engineering model transformations with transml. Softw. Syst. Model. 12(3), 555–577 (2013)CrossRefGoogle Scholar
  12. 12.
    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). doi: 10.1007/978-3-642-03013-0_4 CrossRefGoogle Scholar
  13. 13.
    Iovino, L., Pierantonio, A., Malavolta, I.: On the impact significance of metamodel evolution in MDE. JOT 11(3), 3:1–3:33 (2012)CrossRefGoogle Scholar
  14. 14.
    Jouault, F., Allilaire, F., Bézivin, J., Kurtev, I.: ATL: a model transformation tool. Sci. Comput. Program. 72(1–2), 31–39 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Kolovos, D.S., Paige, R.F., Polack, F.A.C.: The epsilon transformation language. In: Vallecillo, A., Gray, J., Pierantonio, A. (eds.) ICMT 2008. LNCS, vol. 5063, pp. 46–60. Springer, Heidelberg (2008). doi: 10.1007/978-3-540-69927-9_4 CrossRefGoogle Scholar
  16. 16.
    Kruse, S.: On the use of operators for the co-evolution of metamodels and transformations. In: International Workshop on Models and Evolution 2011 (2011)Google Scholar
  17. 17.
    Kusel, A., Etzlstorfer, J., Kapsammer, E., Retschitzegger, W., Schwinger, W., Schönböck, J.: Consistent co-evolution of models and transformations. In: MODELS. IEEE, October 2015Google Scholar
  18. 18.
    Richters, M., Gogolla, M.: A metamodel for OCL. In: France, R., Rumpe, B. (eds.) UML 1999. LNCS, vol. 1723, pp. 156–171. Springer, Heidelberg (1999). doi: 10.1007/3-540-46852-8_12 CrossRefGoogle Scholar
  19. 19.
    Rose, L.M., Paige, R.F., Kolovos, D.S., Polack, F.A.C.: The epsilon generation language. In: Schieferdecker, I., Hartman, A. (eds.) ECMDA-FA 2008. LNCS, vol. 5095, pp. 1–16. Springer, Heidelberg (2008). doi: 10.1007/978-3-540-69100-6_1 CrossRefGoogle Scholar
  20. 20.
    Schmidt, D.C.: Guest editor’s introduction: model-driven engineering. Computer 39(2), 25–31 (2006)CrossRefGoogle Scholar
  21. 21.
    Schönböck, J., Kusel, A., Etzlstorfer, J., Kapsammer, E., Schwinger, W., Wimmer, M., Wischenbart, M.: CARE - a constraint-based approach for re-establishing conformance-relationships. In: Proceedings of the APCCM (2014)Google Scholar
  22. 22.
    Thüm, T., Kästner, C., Benduhn, F., Meinicke, J., Saake, G., Leich, T.: FeatureIDE: an extensible framework for feature-oriented software development. Sci. Comput. Program. 79, 70–85 (2014)CrossRefGoogle Scholar
  23. 23.
    Wagelaar, D., Iovino, L., Ruscio, D., Pierantonio, A.: Translational semantics of a co-evolution specific language with the EMF transformation virtual machine. In: Hu, Z., Lara, J. (eds.) ICMT 2012. LNCS, vol. 7307, pp. 192–207. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-30476-7_13 CrossRefGoogle Scholar
  24. 24.
    Wimmer, M., Kappel, G., Kusel, A., Retschitzegger, W., Schönböck, J., Schwinger, W., Kolovos, D., Paige, R., Lauder, M., Schürr, A., Wagelaar, D.: Surveying rule inheritance in model-to-model transformation languages. JOT 11(2), 3:1–3:46 (2012)Google Scholar
  25. 25.
    Wimmer, M., Kappel, G., Kusel, A., Retschitzegger, W., Schoenboeck, J., Schwinger, W.: Surviving the heterogeneity jungle with composite mapping operators. In: Tratt, L., Gogolla, M. (eds.) ICMT 2010. LNCS, vol. 6142, pp. 260–275. Springer, Heidelberg (2010). doi: 10.1007/978-3-642-13688-7_18 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University of L’AquilaL’AquilaItaly
  2. 2.Johannes Kepler University LinzLinzAustria
  3. 3.Gran Sasso Science InstituteL’AquilaItaly

Personalised recommendations