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Confluence up to Garbage

The transformation of graphs and graph-like structures is ubiquitous in computer science. When a system is described by graph-transformation rules, it is often desirable that the rules are both terminating and confluent so that rule applications in an arbitrary order produce unique resulting graphs....

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Detalles Bibliográficos
Autores principales: Campbell, Graham, Plump, Detlef
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314708/
http://dx.doi.org/10.1007/978-3-030-51372-6_2
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author Campbell, Graham
Plump, Detlef
author_facet Campbell, Graham
Plump, Detlef
author_sort Campbell, Graham
collection PubMed
description The transformation of graphs and graph-like structures is ubiquitous in computer science. When a system is described by graph-transformation rules, it is often desirable that the rules are both terminating and confluent so that rule applications in an arbitrary order produce unique resulting graphs. However, there are application scenarios where the rules are not globally confluent but confluent on a subclass of graphs that are of interest. In other words, non-resolvable conflicts can only occur on graphs that are considered as “garbage”. In this paper, we introduce the notion of confluence up to garbage and generalise Plump’s critical pair lemma for double-pushout graph transformation, providing a sufficient condition for confluence up to garbage by non-garbage critical pair analysis. We apply our results to language recognition by backtracking-free graph reduction, showing how to establish that a graph language can be decided by a system which is confluent up to garbage. We present two case studies with backtracking-free graph reduction systems which recognise a class of flow diagrams and a class of labelled series-parallel graphs, respectively. Both systems are non-confluent but confluent up to garbage.
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spelling pubmed-73147082020-06-25 Confluence up to Garbage Campbell, Graham Plump, Detlef Graph Transformation Article The transformation of graphs and graph-like structures is ubiquitous in computer science. When a system is described by graph-transformation rules, it is often desirable that the rules are both terminating and confluent so that rule applications in an arbitrary order produce unique resulting graphs. However, there are application scenarios where the rules are not globally confluent but confluent on a subclass of graphs that are of interest. In other words, non-resolvable conflicts can only occur on graphs that are considered as “garbage”. In this paper, we introduce the notion of confluence up to garbage and generalise Plump’s critical pair lemma for double-pushout graph transformation, providing a sufficient condition for confluence up to garbage by non-garbage critical pair analysis. We apply our results to language recognition by backtracking-free graph reduction, showing how to establish that a graph language can be decided by a system which is confluent up to garbage. We present two case studies with backtracking-free graph reduction systems which recognise a class of flow diagrams and a class of labelled series-parallel graphs, respectively. Both systems are non-confluent but confluent up to garbage. 2020-05-31 /pmc/articles/PMC7314708/ http://dx.doi.org/10.1007/978-3-030-51372-6_2 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Campbell, Graham
Plump, Detlef
Confluence up to Garbage
title Confluence up to Garbage
title_full Confluence up to Garbage
title_fullStr Confluence up to Garbage
title_full_unstemmed Confluence up to Garbage
title_short Confluence up to Garbage
title_sort confluence up to garbage
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314708/
http://dx.doi.org/10.1007/978-3-030-51372-6_2
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