Download Applications of Graph Transformations with Industrial by Zsolt Kocsis (auth.), Andy Schürr, Dániel Varró, Gergely PDF

By Zsolt Kocsis (auth.), Andy Schürr, Dániel Varró, Gergely Varró (eds.)

This e-book constitutes the completely refereed post-conference lawsuits of the 4th overseas Symposium on functions of Graph ameliorations, AGTIVE 2011, held in Budapest, Hungary, in October 2011.
The thirteen revised complete papers provided including 2 invited talks, 2 program stories and three software demonstration papers have been conscientiously chosen from 36 submissions in the course of rounds of reviewing and development. The papers are prepared in topical sections on invited speak abstracts, model-driven engineering, graph transformation functions, instrument demonstrations, graph transformation exploration strategies, graph transformation semantics and reasoning, program experiences and bidirectional transformations.

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Extra info for Applications of Graph Transformations with Industrial Relevance: 4th International Symposium, AGTIVE 2011, Budapest, Hungary, October 4-7, 2011, Revised Selected and Invited Papers

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Graph constraints generated from cardinality constraints Next we define morphisms between meta-models as a graph morphism with some extra constraints given by the inheritance hierarchy. We will use this notion later to define the binding between a concept and a meta-model. A morphism M M → M M between two meta-models (short MM-morphism) is given by a clan morphism [9] f : GMM → M M from the graph GMM of the first meta-model to the second meta-model, preserving the inheritance hierarchy. A clan morphism is similar to a standard E-Graph morphism [3], but it also takes into account the semantics of inheritance.

6(b), (c) and (d) show the specifications S1 , S2 and S3 of a deep stack corresponding to a simplified version of the one in Fig. 1(b). The figure also shows the ontological typings as dashed, grey arrows. In S1 the potency 2 on Component and datalink is specified by (1 a datalink , γ1 : 1 → Component) and (2 , γ2 : (1 − → 2) → (Component −−−−→ Component)), respectively. Similarly, the potencies 1 on id and ([mult(1, 1)], δ1 ) are specified by (2 , γ3 ) and (2 , γ4 ; δ1 ), respectively.

For example, the attribute id:String of the id clabject Component in Fig. 1(b) is represented in DPF by an edge Component − → String (see Fig. 2). 24 A. Rossini et al. The semantics of graph nodes and arrows has to be chosen in a suitable way for the corresponding modelling environment [20]. In object-oriented structural modelling, each object may be related to a set of other objects. Hence, it is appropriate to interpret f → Y as multi-valued functions f : X → ℘(Y ). nodes as sets and arrows X − The semantics of predicates of the signature Σ (see Fig 2) is described using the mathematical language of set theory.

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