Parsing Hypergraphs using Context-Free Positional Grammars

We present a novel work-in-progress approach to the parsing of hypergraphs generated by contextfree hyperedge replacement grammars.This method is based on a new LR parsing technique for positional grammars, which is also under active development.Central to our approach is a reduction from hyperedge replacement to positional grammars with additional structural constraints, enabling the use of permutation-based operations to determine the correct ordering of hyperedges on the righthand side of productions.Preliminary results also reveal a distinction between ambiguity in graph generation and ambiguity in graph recognition.While the exact class of hyperedge replacement languages parsable under this method remains under investigation, the approach provides a promising foundation for future generalisations to more expressive grammar formalisms.Graph parsing remains a broadly relevant problem across numerous domains, and our contribution aims to advance both the theoretical and practical understanding of this challenge.

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Publication Details

Journal
Electronic Proceedings in Theoretical Computer Science
Published
2026-01-06
DOI
https://doi.org/10.4204/eptcs.440.1
Primary Topic
Model-Driven Software Engineering Techniques
Type
article
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article

Parsing Hypergraphs using Context-Free Positional Grammars

Gennaro Costagliola, Federico Vastarini
Electronic Proceedings in Theoretical Computer Science
Model-Driven Software Engineering Techniques
article

Parsing Hypergraphs using Context-Free Positional Grammars

Gennaro Costagliola, Federico Vastarini
article en

Abstract

We present a novel work-in-progress approach to the parsing of hypergraphs generated by contextfree hyperedge replacement grammars.This method is based on a new LR parsing technique for positional grammars, which is also under active development.Central to our approach is a reduction from hyperedge replacement to positional grammars with additional structural constraints, enabling the use of permutation-based operations to determine the correct ordering of hyperedges on the righthand side of productions.Preliminary results also reveal a distinction between ambiguity in graph generation and ambiguity in graph recognition.While the exact class of hyperedge replacement languages parsable under this method remains under investigation, the approach provides a promising foundation for future generalisations to more expressive grammar formalisms.Graph parsing remains a broadly relevant problem across numerous domains, and our contribution aims to advance both the theoretical and practical understanding of this challenge.

Electronic Proceedings in Theoretical Computer ScienceVol. 440
University of Salerno (IT)
Quality Education
Openalex Percentile: Top 97%
Model-Driven Software Engineering Techniques
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Parsing Hypergraphs using Context-Free Positional Grammars — Gennaro Costagliola, Federico Vastarini · Electronic Proceedings in Theoretical Computer Science (2026) | TGRS Research Map | TGRS