Adaptive Graph Pattern Matching for Model Transformations using Model-sensitive Search Plans1

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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.

Keywords

graph transformation
adaptive graph pattern matching
search plans

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1

The first author was partially funded by the Péter Bizáki Puky Scholarship and the second author was partially funded by the János Bolyai Scholarship.

Copyright © 2006 Elsevier B.V.