Approximating Parikh Images for Generating Deterministic Graph Parsers

  • Frank Drewes
  • Berthold Hoffmann
  • Mark MinasEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9946)


The Parikh image of a word abstracts from the order of its letters. Parikh’s famous theorem states that the set of Parikh images of a context-free string language forms a semilinear set that can be effectively computed from its grammar. In this paper we study the computation of Parikh images for graph grammars defined by contextual hyperedge replacement (CHR). Our motivation is to generate efficient predictive top-down (PTD) parsers for a subclass of CHR grammars. We illustrate this by describing the subtask that identifies the nodes of the input graph that parsing starts with.


Input Graph Derivation Tree Grammar Graph Start Node Terminal Symbol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank the anonymous reviewers for the valuable comments.


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Authors and Affiliations

  1. 1.Umeå UniversitetUmeåSweden
  2. 2.Universität BremenBremenGermany
  3. 3.Universität der Bundeswehr MünchenNeubibergGermany

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