Graph Passing in Graph Transformation

Graph transformation works under the whole world assumption. Therefore, in realistic systems, both the individual graphs and the set of all such graphs can grow very large. In reactive formalisms such as process algebra, on the other hand, each system is split into smaller components which continually interact; the interactions pass information such as names or locations between components. The state spaces for the separate components are typically much smaller, and much efficiency can be gained by analysing system behaviour on this level.In this paper we present a framework for  compositional graph transformation inspired by name-passing calculi, in which (knowledge about) subgraphs can be passed between components. Essentially, we define graph-passing (reactive) component rules and their composition into traditional (reductive) whole-world rules. This extends previous work in which a simpler form of composition was proposed. The main result is a soundness and completeness result for the composition, showing that the transformations induced by the component rules and their whole-world counterparts are equivalent

Generalised compositionality in graph transformation

We present a notion of composition applying both to graphs and to rules, based on graph and rule interfaces along which they are glued. The current paper generalises a previous result in two different ways. Firstly, rules do not have to form pullbacks with their interfaces; this enables graph passing between components, meaning that components may “learn” and “forget” subgraphs through communication with other components. Secondly, composition is no longer binary; instead, it can be repeated for an arbitrary number of components

Graph passing in graph transformation

Graph transformation works under the whole world assumption. Therefore, in realistic systems, both the individual graphs and the set of all such graphs can grow very large. In reactive formalisms such as process algebra, on the other hand, each system is split into smaller components which continually interact; the interactions pass information such as names or locations between components. The state spaces for the separate components are typically much smaller, and much efficiency can be gained by analysing system behaviour on this level. In this paper we present a framework for compositional graph transformation inspired by name-passing calculi, in which (knowledge about) subgraphs can be passed between components. Essentially, we define graph-passing (reactive) component rules and their composition into traditional (reductive) whole-world rules. This extends previous work in which a simpler form of composition was proposed. The main result is a soundness and completeness result for the composition, showing that the transformations induced by the component rules and their whole-world counterparts are equivalent