We present conditions under which graph transformation rules can be applied in time independent of the size of the input graph: graphs must contain a unique root label, nodes in the left-hand sides of rules must be reachable from the root, and nodes must have a bounded outdegree. We establish a constant upper bound for the time needed to construct all graphs resulting from an application of a f...

Modern software systems increasingly incorporate self-* behavior to adapt to changes in the environment at runtime. Such adaptations often involve reconfiguring the software architecture of the system. Many systems also need to manage their architecture themselves, i.e., they need a planning component to autonomously decide which reconfigurations to execute to reach a desired target configurati...

We describe a tool to create, edit, visualise and compute with interaction nets — a form of graph rewriting systems. The editor, called GraphPaper, allows users to create and edit graphs and their transformation rules using an intuitive user interface. The editor uses the functionalities of the TULIP system, which gives us access to a wealth of visualisation algorithms. Interaction nets are not...

The development of a denotational framework for graph transformation systems proved elusive so far. Despite the existence of many formalisms for modelling various notions of rewriting, the lack of an explicit, algebraic notion of “term” for describing a graph (thus different from the usual view of a graph as an algebra in itself) frustrated the efforts of the researchers. Resorting to the theor...

Graph transformation can be used to implement stochastic simulation of dynamic systems based on semi-Markov processes, extending the standard approach based on Markov chains. The result is a discrete event system, where states are graphs, and events are rule matches associated to general distributions, rather than just exponential ones. We present an extension of this model, by introducing a hi...

This document provides insight to the similarities and differences of Graph Transformation and AI Planning, two rising research fields with different publication organs and tools. While graph transformation systems can be used as a graphical knowledge engineering front-end for designing planning problems, AI planning technology (especially heuristic search) can accelerate the exploration proces...

We consider a graph with labels of edges. A label means the length of an edge. We present a method to compute the length of the shortest path between two vertices using graph transformations. We introduce graph transformation rules which preserve the length of paths. Reducing to a simple graph which contains two vertices, we finally calculate the length of the shortest path of those two vertice...

Abstract. Graph transformation provides a visual but mathematically precise way to specify arbitrary model transformations in the Model Driven Architecture. The Action Semantics for UML is a standard and platform independent way to describe the dynamic behavior of methods and executable actions in UML based system models prior to implementation allowing the development of highly automated and o...

Reactive systems perform their tasks through interaction with their users or with other systems (as parts of a bigger system). An essential requirement for modeling such systems is the ability to express this kind of interaction. Classical rule-based approaches like Petri nets and graph transformation are not suited for this purpose because they assume to have complete control about the state a...

Distributed systems with mobile components are naturally modelled by graph transformations. To formalise and predict properties such as performance or reliability of such systems, stochastic methods are required. Stochastic graph transformations allow the integrated modelling of these two concerns by associating with each rule and match a probability distribution governing the delay of its appl...