Adaptive Graph Pattern Matching for Model Transformations using Model-sensitive Search Plans

Authors:
Gergely Varró;Katalin Friedl;Dániel Varró
Affiliations:
Department of Computer Science and Information Theory, Budapest University of Technology and Economics, H-1521 Budapest, Magyar tudósok körútja 2., Hungary;Department of Computer Science and Information Theory, Budapest University of Technology and Economics, H-1521 Budapest, Magyar tudósok körútja 2., Hungary;Department of Measurement and Information Systems, Budapest University of Technology and Economics, H-1521 Budapest, Magyar tudósok körútja 2., Hungary
Venue:
Electronic Notes in Theoretical Computer Science (ENTCS)
Year:
2006

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Abstract

The current paper makes two contributions for the graph pattern matching problem of model transformation tools. First, model-sensitive search plan generation is proposed for pattern traversal (as an extension to traditional multiplicity and type considerations of existing tools) by estimating the expected performance of search plans on typical instance models that are available at transformation design time. Then, an adaptive approach for graph pattern matching is presented, where the optimal search plan can be selected from previously generated search plans at run-time based on statistical data collected from the current instance model under transformation.