Adaptive Star Grammars for Graph Models

  • Frank Drewes
  • Berthold Hoffmann
  • Mark Minas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5214)


Adaptive star grammars generalize well-known graph grammar formalisms based on hyperedge and node replacement while retaining, e.g., parseability and the commutativity and associativity of rule application. In this paper, we study how these grammars can be put to practical use for the definition of graph models. We show how to use adaptive star grammars to specify program graphs, models of object-oriented programs that have been devised for investigating refactoring operations. For this, we introduce notational enhancements and one proper extension (application conditions). The program graphs generated by the grammar comprise not only the nested composition of entities, but also scope rules for their declarations. Such properties cannot easily be defined by meta-models like Uml class diagrams. In contrast, adaptive star grammars cover several aspects of class diagrams.


Model Transformation Graph Transformation Program Graph Graph Grammar Syntax Tree 
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.


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  1. 1.
    Amelunxen, C., Königs, A., Rötschke, T., Schürr, A.: MOFLON: A standard-compliant metamodeling framework with graph transformations. In: Rensink, A., Warmer, J. (eds.) ECMDA-FA 2006. LNCS, vol. 4066, pp. 361–375. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    Bakewell, A., Plump, D., Runciman, C.: Specifying pointer structures by graph reduction. Mathematical Structures in Computer Science (to appear, 2008)Google Scholar
  3. 3.
    Courcelle, B.: An axiomatic definition of context-free rewriting and its application to NLC rewriting. Theoretical Computer Science 55, 141–181 (1987)zbMATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Drewes, F., Hoffmann, B., Janssens, D., Minas, M.: Adaptive star grammars and their languages. Technical Report 2008-01, Departement Wiskunde-Informatica, Universiteit Antwerpen (2008)Google Scholar
  5. 5.
    Drewes, F., Hoffmann, B., Janssens, D., Minas, M., Van Eetvelde, N.: Adaptive star grammars. In: Corradini, A., Ehrig, H., Montanari, U., Ribeiro, L., Rozenberg, G. (eds.) ICGT 2006. LNCS, vol. 4178, pp. 77–91. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Drewes, F., Hoffmann, B., Janssens, D., Minas, M., Van Eetvelde, N.: Shaped generic graph transformation. In: Schürr, A., Nagl, M., Zündorf, A. (eds.) Applications of Graph Transformation with Industrial Relevance (AGTIVE 2007). LNCS. Springer, Heidelberg (to appear, 2008)Google Scholar
  7. 7.
    Ehrig, H., Ehrig, K.: An overview of formal concepts for model transformations based on typed attributes graph transformation. In: Proc. Graph and Model Transformation Workshop (GraMoT 2005). Electronic Notes in Theoretical Computer Science, vol. 152(4) (2006)Google Scholar
  8. 8.
    Ehrig, H., Ehrig, K., Prange, U., Taentzer, G.: Fundamentals of Algebraic Graph Transformation. EATCS Monographs on Theoretical Computer Science. Springer, Heidelberg (2006)zbMATHGoogle Scholar
  9. 9.
    Ehrig, K., Ermel, C., Hänsgen, S., Taentzer, G.: Generation of visual editors as eclipse plug-ins. In: ASE 2005: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering, pp. 134–143. ACM Press, New York (2005)CrossRefGoogle Scholar
  10. 10.
    EMF, Eclipse Modeling Framework web page (2006),
  11. 11.
    Engelfriet, J.: Context-free graph grammars. In: Rozenberg, G., Salomaa, A. (eds.) Handbook of Formal Languages, Beyond Words, vol. 3, pp. 125–213. Springer, Heidelberg (1999)Google Scholar
  12. 12.
    Hölscher, K., Ziemann, P., Gogolla, M.: On translating uml models into graph transformation systems. J. Vis. Lang. Comput. 17(1), 78–105 (2006)CrossRefGoogle Scholar
  13. 13.
    Kaul, M.: Syntaxanalyse von Graphen bei Präzedenz–Graph–Grammatiken. Dissertation, Univ. Passau (1985)Google Scholar
  14. 14.
    Knuth, D.E.: Semantics of context-free languages. Math. Sys. Theory 2(2), 127–145 (1968); . Correction: Math. Sys. Theory 5(1), 95-96 (1971)zbMATHCrossRefMathSciNetGoogle Scholar
  15. 15.
    Mens, T., Demeyer, S., Janssens, D.: Formalising behaviour-preserving transformation. In: Corradini, A., Ehrig, H., Kreowski, H.-J., Rozenberg, G. (eds.) ICGT 2002. LNCS, vol. 2505, pp. 286–301. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  16. 16.
    Minas, M.: Concepts and realization of a diagram editor generator based on hypergraph transformation. Science of Computer Programming 44(2), 157–180 (2002)zbMATHCrossRefGoogle Scholar
  17. 17.
    Minas, M.: Parsing of adaptive star grammars. Electronic Communications of the European Association of Software Science and Technology 4 (2006),
  18. 18.
    Object Management Group. Meta Object Facility (MOF) Core Specification, version 2.0 edn., Document - formal/06-01-01 (January 2006)Google Scholar
  19. 19.
    Schürr, A., Winter, A., Zündorf, A.: The Progres approach: Language and environment. In: Engels, G., Ehrig, H., Kreowski, H.-J., Rozenberg, G. (eds.) Handbook of Graph Grammars and Computing by Graph Transformation, Applications, Languages, and Tools, ch. 13, vol. II, pp. 487–550. World Scientific, Singapore (1999)Google Scholar
  20. 20.
    Van Eetvelde, N.: A Graph Transformation Approach to Refactoring. Doctoral thesis, Universiteit Antwerpen (May 2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Frank Drewes
    • 1
  • Berthold Hoffmann
    • 2
  • Mark Minas
    • 3
  1. 1.Umeå universitetSweden
  2. 2.Universität BremenGermany
  3. 3.Universität der Bundeswehr MünchenGermany

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