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A Benchmark Evaluation of Incremental Pattern Matching in Graph Transformation

by: Gábor Bergmann, Ákos Horváth, István Ráth, and Dániel Varró

In: 4th International Conference on Graph Transformation ICGT'08Springer (2008) , p. 396-410.

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URL:	http://dx.doi.org/10.1007/978-3-540-87405-8_27

In graph transformation, the most cost-intensive phase of a transformation execution is pattern matching, where those subgraphs of a model graph are identified and matched which satisfy constraints prescribed by graph patterns. Incremental pattern matchingaims to improve the efficiency of this critical step by storing the set of matches of a graph transformation rule and incrementallymaintaining it as the model changes, thus eliminating the need of recalculating existing matches of a pattern. In this paper,we propose benchmark examples where incremental pattern matching is expected to have advantageous effect in the applicationdomain of model simulation and model synchronization. Moreover, we compare the incremental graph pattern matching approachof Viatra2 with advanced non-incremental local-search based graph pattern matching approaches as available in Viatra2 and GrGen.

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SpringerLink - Buchkapitel

BibTeX record

@inproceedings{bergmann-etal:08,
  abstract = {In graph transformation, the most cost-intensive phase of a transformation execution is pattern matching, where those subgraphs
of a model graph are identified and matched which satisfy constraints prescribed by graph patterns. Incremental pattern matchingaims to improve the efficiency of this critical step by storing the set of matches of a graph transformation rule and incrementallymaintaining it as the model changes, thus eliminating the need of recalculating existing matches of a pattern. In this paper,we propose benchmark examples where incremental pattern matching is expected to have advantageous effect in the applicationdomain of model simulation and model synchronization. Moreover, we compare the incremental graph pattern matching approachof Viatra2 with advanced non-incremental local-search based graph pattern matching approaches (as available in Viatra2 and GrGen).},
  added-at = {2009-10-24T00:47:43.000+0200},
  author = {Bergmann, Gábor and Horváth, Ákos and Ráth, István and Varró, Dániel},
  biburl = {http://www.bibsonomy.org/bibtex/27d73d54c3abc652a9959d7a6ec501c07/minas},
  booktitle = {4th International Conference on Graph Transformation (ICGT'08)},
  crossref = {ICGT:08},
  description = {SpringerLink - Buchkapitel},
  interhash = {dbb7e42bfa82dd27d819f9ade2adb8ae},
  intrahash = {7d73d54c3abc652a9959d7a6ec501c07},
  keywords = {2008 GraGra},
  pages = {396-410},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  timestamp = {2009-10-24T00:47:43.000+0200},
  title = {A Benchmark Evaluation of Incremental Pattern Matching in Graph Transformation},
  url = {http://dx.doi.org/10.1007/978-3-540-87405-8_27},
  year = 2008
}

Endnote record

%0 Conference Paper
%1 bergmann-etal:08
%A Bergmann, Gábor
%A Horváth, Ákos
%A Ráth, István
%A Varró, Dániel
%B 4th International Conference on Graph Transformation (ICGT'08)
%D 2008
%I Springer
%K 
%P 396-410
%T A Benchmark Evaluation of Incremental Pattern Matching in Graph Transformation
%U http://dx.doi.org/10.1007/978-3-540-87405-8_27
%X In graph transformation, the most cost-intensive phase of a transformation execution is pattern matching, where those subgraphs
of a model graph are identified and matched which satisfy constraints prescribed by graph patterns. Incremental pattern matchingaims to improve the efficiency of this critical step by storing the set of matches of a graph transformation rule and incrementallymaintaining it as the model changes, thus eliminating the need of recalculating existing matches of a pattern. In this paper,we propose benchmark examples where incremental pattern matching is expected to have advantageous effect in the applicationdomain of model simulation and model synchronization. Moreover, we compare the incremental graph pattern matching approachof Viatra2 with advanced non-incremental local-search based graph pattern matching approaches (as available in Viatra2 and GrGen).