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Triple Graph Gammares: Concepts, Extensions, Implementations, and Application Scenarios

Triple Graph Gammares: Concepts, Extensions, Implementations, and Application Scenarios Ekkart Kindler and Robert Wagner 2007. TGG Application Scenarios:. Triple Graph Grammars (TGGs).

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Triple Graph Gammares: Concepts, Extensions, Implementations, and Application Scenarios

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  1. Triple Graph Gammares: Concepts, Extensions, Implementations, and Application Scenarios EkkartKindler and Robert Wagner 2007

  2. TGG Application Scenarios: Triple Graph Grammars (TGGs) “Are a technique for defining the correspondence between two different types of models in a declarative way.” Model Transformation TGG Model Synchronisation Model Integration

  3. A construction plan for a toy train

  4. Triple Graph Grammars (TGGs) Figure 17: Meta-model for the correspondence objects

  5. Model Transformation Assumption and Goal: • One of the two models at either side already exists • Generate a corresponding model at the other side Solution: • Matching the source domain of the rules of the TGG to the given project model. • Adding the missing correspondence nodes and nodes (belonging to the other model) of that rule. Challenges: Transformation from PN to a project model: No corresponding project for the PN and vice versa. The transformation is not deterministic. The matching process might need backtracking

  6. Model Integration Assumption and Goal: • Two models are given, the correspondences between them needs to be established. Solution: • Introduce the correspondence node between the root elements of the models. • Matching (the both model side of) the TGG rules on the existing models. • Introduce the correspondence nodes of the matching TGG rule. Challenge: • May not be able to fully match both models

  7. Model Synchronisation Assumption and Goal: • For each side there is a model. • The correspondences between two models already exist • The models are not in complete or correct correspondence. • Finding the best possible matching pair • With as few as possible changes on both sides Solution: • Reapplying the rules and adding the missing parts of both models. Challenge: • May not be able to fully match both models.

  8. Basic Rule Synthesis Algorithm

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