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https://doi.org/10.1007/978-1-59259-692-8r nodes or subgraphs. There have been several suggestions to hierarchical graphs that differ in terms of the underlying graph type, the elements that are structured and the way the structuring is achieved. In this contribution we aim at a more general notion of hierarchical structures for graphs. We
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https://doi.org/10.1007/978-3-319-42139-1ex, edge, face, etc.) and their embeddings (. relevant data: vertex positions, face colors, volume densities, etc.). Graph transformations with variables allow us to generically handle those operations. We use two types of variables: orbit variables to abstract topological cells and node variables t
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https://doi.org/10.1007/978-3-662-41088-2 where the corresponding language consists of all graphs that can be mapped homomorphically to a given type graph. In this context, we also study languages specified by restriction graphs and their relation to type graphs. Second, we extend this basic approach to a type graph logic and, third, to ty
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Francis C. Wells,Robert H. Andersond by the observation that many large and complex structures can be seen as compositions of a large number of small basic pieces. A fusion grammar is a hypergraph grammar that provides the small pieces as connected components of the start hypergraph. To get arbitrary large numbers of them, they can b
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https://doi.org/10.1007/978-3-658-11623-1arly if systems with many possible initial graphs and large or infinite state spaces are concerned. One approach that tries to overcome these limitations is inductive invariant checking. However, the verification of inductive invariants often requires extensive knowledge about the system in question
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