Graph Transformation Units – An Overview

Kreowski, Hans‐Jörg; Kuske, Sabine; Rozenberg, Grzegorz

doi:10.1007/978-3-540-68679-8_5

Cited by 21 publications

(12 citation statements)

References 26 publications

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“…This section recalls the concept of graph-transformational swarms as introduced in [1] starting with the basic components of the chosen graph-transformational approach as far as needed in this paper (for more details, see, e.g., [8,14,16,20]). …”

Section: Graph-transformational Swarmsmentioning

confidence: 99%

Modeling of decentralized processes in dynamic logistic networks by means of graph-transformational swarms

Abdenebaoui

Kreowski

2016

Logist. Res.

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In this paper, we propose to employ the framework of graph-transformational swarms for the modeling of dynamic logistic networks with decentralized processing and control. The members of a graph-transformational swarm act and interact in a common environment graph with massive parallelism of rule-based activities according to local control conditions and a global cooperation condition. This corresponds directly to the logistic hubs and their processes in a logistic network where the processes run simultaneously and autonomously with a proper way of coordination. This covers also dynamic changes on the network structures as the members of a swarm can change the environment anyhow. The approach is illustrated by the modeling of automated guided vehicles.

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Section: Graph-transformational Swarmsmentioning

confidence: 99%

Modeling of decentralized processes in dynamic logistic networks by means of graph-transformational swarms

Abdenebaoui

Kreowski

2016

Logist. Res.

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“…These approaches rely on a host language (Java, Prolog, Xtend) for cases where users wish to additionally control GraTra rules. Approaches such as Henshin [1] are in-between, focussing primarily on patterns but still providing a relatively simple and high-level language such as transformation units [14] to program individual GraTra rules.…”

Section: Related Workmentioning

confidence: 99%

Towards a Step Semantics for Story-Driven Modelling

Kulcsár

Anjorin

2016

Electron. Proc. Theor. Comput. Sci.

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Graph Transformation (GraTra) provides a formal, declarative means of specifying model transformation. In practice, GraTra rule applications are often programmed via an additional language with which the order of rule applications can be suitably controlled.Story-Driven Modelling (SDM) is a dialect of programmed GraTra, originally developed as part of the Fujaba CASE tool suite. Using an intuitive, UML-inspired visual syntax, SDM provides usual imperative control flow constructs such as sequences, conditionals and loops that are fairly simple, but whose interaction with individual GraTra rules is nonetheless non-trivial. In this paper, we present the first results of our ongoing work towards providing a formal step semantics for SDM, which focuses on the execution of an SDM specification.

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“…The graph transformation units exemplified in [15], also provide a notion of composition. However, this work takes the form of an explicit structuring mechanism of local graph transformation systems, called Units.…”

Section: Compositional Model Transformationmentioning

confidence: 99%

“…4 for an overview. Several of these, such as borrowed contexts [6], transformation units [15] and synchronised hyperedge replacement [7] have been inspired to some degree or another by notions of composition from process algebra. In this paper we continue an investigation started in [19] based on the following initial requirements: -Composition should make it possible to construct large graphs (describing the global system in context) from smaller graphs (describing individual components).…”

Section: Introductionmentioning

confidence: 99%

Generalised Compositionality in Graph Transformation

Ghamarian

Rensink

2012

Lecture Notes in Computer Science

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Abstract. 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.

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Graph Transformation Units – An Overview

Abstract: Abstract. In this paper, we give an overview of the framework of graph transformation units which provides syntactic and semantic means for analyzing, modeling, and structuring all kinds of graph processing and graph transformation.

Cited by 21 publications

References 26 publications

Modeling of decentralized processes in dynamic logistic networks by means of graph-transformational swarms

Modeling of decentralized processes in dynamic logistic networks by means of graph-transformational swarms

Towards a Step Semantics for Story-Driven Modelling

Generalised Compositionality in Graph Transformation

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