Improved Conflict Detection for Graph Transformation with Attributes

In graph transformation, a conflict describes a situation where two alternative transformations cannot be arbitrarily serialized. When enriching graphs with attributes, existing conflict detection techniques typically report a conflict whenever at least one of two transformations manipulates a share...

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Main Authors: Géza Kulcsár, Frederik Deckwerth, Malte Lochau, Gergely Varró, Andy Schürr
Format: Article
Language:English
Published: Open Publishing Association 2015-04-01
Series:Electronic Proceedings in Theoretical Computer Science
Online Access:http://arxiv.org/pdf/1504.02614v1
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spelling doaj-9685dc6dc065420d9c603a463044554d2020-11-24T22:39:56ZengOpen Publishing AssociationElectronic Proceedings in Theoretical Computer Science2075-21802015-04-01181Proc. GaM 20159711210.4204/EPTCS.181.7:14Improved Conflict Detection for Graph Transformation with AttributesGéza Kulcsár0Frederik Deckwerth1Malte Lochau2Gergely Varró3Andy Schürr4 Technische Universität Darmstadt Real-Time Systems Lab Technische Universität Darmstadt Real-Time Systems Lab Technische Universität Darmstadt Real-Time Systems Lab Technische Universität Darmstadt Real-Time Systems Lab Technische Universität Darmstadt Real-Time Systems Lab In graph transformation, a conflict describes a situation where two alternative transformations cannot be arbitrarily serialized. When enriching graphs with attributes, existing conflict detection techniques typically report a conflict whenever at least one of two transformations manipulates a shared attribute. In this paper, we propose an improved, less conservative condition for static conflict detection of graph transformation with attributes by explicitly taking the semantics of the attribute operations into account. The proposed technique is based on symbolic graphs, which extend the traditional notion of graphs by logic formulas used for attribute handling. The approach is proven complete, i.e., any potential conflict is guaranteed to be detected.http://arxiv.org/pdf/1504.02614v1
collection DOAJ
language English
format Article
sources DOAJ
author Géza Kulcsár
Frederik Deckwerth
Malte Lochau
Gergely Varró
Andy Schürr
spellingShingle Géza Kulcsár
Frederik Deckwerth
Malte Lochau
Gergely Varró
Andy Schürr
Improved Conflict Detection for Graph Transformation with Attributes
Electronic Proceedings in Theoretical Computer Science
author_facet Géza Kulcsár
Frederik Deckwerth
Malte Lochau
Gergely Varró
Andy Schürr
author_sort Géza Kulcsár
title Improved Conflict Detection for Graph Transformation with Attributes
title_short Improved Conflict Detection for Graph Transformation with Attributes
title_full Improved Conflict Detection for Graph Transformation with Attributes
title_fullStr Improved Conflict Detection for Graph Transformation with Attributes
title_full_unstemmed Improved Conflict Detection for Graph Transformation with Attributes
title_sort improved conflict detection for graph transformation with attributes
publisher Open Publishing Association
series Electronic Proceedings in Theoretical Computer Science
issn 2075-2180
publishDate 2015-04-01
description In graph transformation, a conflict describes a situation where two alternative transformations cannot be arbitrarily serialized. When enriching graphs with attributes, existing conflict detection techniques typically report a conflict whenever at least one of two transformations manipulates a shared attribute. In this paper, we propose an improved, less conservative condition for static conflict detection of graph transformation with attributes by explicitly taking the semantics of the attribute operations into account. The proposed technique is based on symbolic graphs, which extend the traditional notion of graphs by logic formulas used for attribute handling. The approach is proven complete, i.e., any potential conflict is guaranteed to be detected.
url http://arxiv.org/pdf/1504.02614v1
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AT maltelochau improvedconflictdetectionforgraphtransformationwithattributes
AT gergelyvarro improvedconflictdetectionforgraphtransformationwithattributes
AT andyschurr improvedconflictdetectionforgraphtransformationwithattributes
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