Unification and matching on compressed terms

Author:

Gascón Adrià1,Godoy Guillem1,Schmidt-Schauss Manfred2

Affiliation:

1. Universitat Politècnica de Catalunya, Barcelona, Spain

2. Goethe-Universität, Frankfurt, Germany

Abstract

Term unification plays an important role in many areas of computer science, especially in those related to logic. The universal mechanism of grammar-based compression for terms, in particular the so-called singleton tree grammars (STGAs) , have recently drawn considerable attention. Using STGs, terms of exponential size and height can be represented in linear space. Furthermore, the term representation by directed acyclic graphs (dags) can be efficiently simulated. The present article is the result of an investigation on term unification and matching when the terms given as input are represented using different compression mechanisms for terms such as dags and singleton tree grammars. We describe a polynomial time algorithm for context matching with dags, when the number of different context variables is fixed for the problem. For the same problem, NP-completeness is obtained when the terms are represented using the more general formalism of singleton tree grammars. For first-order unification and matching polynomial time algorithms are presented, each of them improving previous results for those problems.

Funder

LOGICTOOLS-2

Ministerio de Educación, Cultura y Deporte

Publisher

Association for Computing Machinery (ACM)

Subject

Computational Mathematics,Logic,General Computer Science,Theoretical Computer Science

Reference44 articles.

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2. Baader F. and Snyder W. 2001. Unification theory. In Handbook of Automated Reasoning J. A. Robinson and A.Voronkov Eds. Elsevier and MIT Press Amsterdam The Netherlands and Cambridge MA 445--532. Baader F. and Snyder W. 2001. Unification theory. In Handbook of Automated Reasoning J. A. Robinson and A.Voronkov Eds. Elsevier and MIT Press Amsterdam The Netherlands and Cambridge MA 445--532.

3. On the Complexity of Pattern Matching for Highly Compressed Two-Dimensional Texts

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