Leveraging Incremental Pattern Matching Techniques for Model Synchronisation

  • Erhan Leblebici
  • Anthony Anjorin
  • Lars Fritsche
  • Gergely Varró
  • Andy Schürr
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10373)


Triple Graph Grammars (TGGs) are a declarative, rule-based approach to model synchronisation with numerous implementations. TGG-based approaches derive typically a set of operational graph transformations from direction-agnostic TGG rules to realise model synchronisation. In addition to these derived graph transformations, however, further runtime analyses are required to calculate the consequences of model changes in a synchronisation run. This part of TGG-based synchronisation is currently manually implemented, which not only increases implementation and tool maintenance effort, but also requires tool or at least approach-specific proofs for correctness. In this paper, therefore, we discuss how incremental graph pattern matchers can be leveraged to simplify the runtime steps of TGG-based synchronisation. We propose to outsource the task of calculating the consequences of model changes to an underlying incremental pattern matcher. As a result, a TGG-based synchroniser is reduced to a component reacting solely to appearing and disappearing matches. This abstracts high-level synchronisation goals from low-level details of handling model changes, providing a viable and unifying foundation for a new generation of TGG tools.



This work has been funded by the German Federal Ministry of Education and Research within the Software Campus project GraTraM at TU Darmstadt, funding code 01IS12054.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Erhan Leblebici
    • 1
  • Anthony Anjorin
    • 2
  • Lars Fritsche
    • 1
  • Gergely Varró
    • 1
  • Andy Schürr
    • 1
  1. 1.Technische Universität DarmstadtDarmstadtGermany
  2. 2.Universität PaderbornPaderbornGermany

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