
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>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)].
graph rewriting, local confluence, term rewriting, graph grammars, Formal languages and automata, Abstract data types; algebraic specification, Theoretical Computer Science, Computer Science(all)
graph rewriting, local confluence, term rewriting, graph grammars, Formal languages and automata, Abstract data types; algebraic specification, Theoretical Computer Science, Computer Science(all)
| 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). | 80 | |
| 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. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
