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Theoretical Computer Science
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Theoretical Computer Science
Article . 1984
License: Elsevier Non-Commercial
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Theoretical Computer Science
Article . 1984 . Peer-reviewed
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On graph rewritings

Authors: Jean-Claude Raoult;

On graph rewritings

Abstract

This paper deals with rewriting of directed ordered graphs over a graded alphabet G. The author shows that if graphs are represented by vertices and edges direct derivations accordin to \textit{H. Ehrig}, \textit{M. Pfender}, and \textit{H. J. Schneider} [Graph Grammars: an algebraic approach, Proc. 14th Annual Conf. Switching Automata Theory, 167-180 (1973)] can be simulated using a single push-out of partial morphisms. In the following graphs representing terms of the free G-algebra over a given set of variables are considered. Let A, B, C be graphs, \(f: A\to B\) a total function and \(g: A\to C\) be an occurrence, then the push-out of f and g yields a unique graph structure D provided that certain conditions are satisfied. If A, B, C represent terms exp(A), exp(B), exp(C) and f is associated with a term rewriting rule exp(A)\(\to \exp (B)\), then D represents a term exp(D) which one obtains by applying the rule exp(A)\(\to \exp (B)\) to exp(C). Finally the author gives a necessary and sufficient condition for local confluence of a final system of graph rewriting rules associated with term rewriting rules. In the framework of graph grammars according to the Berlin School a similar result holds using the embedding theorem [cf. \textit{H. Ehrig}, Lect. Notes Comput. Sci. 73, 1-69 (1979; Zbl 0407.68072)].

Related Organizations
Keywords

graph rewriting, local confluence, term rewriting, graph grammars, Formal languages and automata, Abstract data types; algebraic specification, Theoretical Computer Science, Computer Science(all)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
80
Top 10%
Top 1%
Top 10%
hybrid