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International Conference on Formal Engineering Methods

ICFEM 2022: Formal Methods and Software Engineering pp 20–35Cite as

Canonical Narrowing for Variant-Based Conditional Rewrite Theories

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13478))

Abstract

Maude currently supports many symbolic reasoning features such as order-sorted equational unification and order-sorted narrowing-based symbolic reachability analysis. There have been many advances and new features added to improve narrowing in Maude but only at a theoretical level. In this paper, we provide a very elegant, transparent, and extremely pragmatic approach for conditional rewrite theories where the conditions are just equalities solved by equational unification. We show how two conditional theories, never executed before, are now executable with very good performance. We also show how real execution works better than the manually transformed version.

This work has been partially supported by the EC H2020-EU grant agreement No. 952215 (TAILOR), by the grant PID2021-122830OB-C42 funded by MCIN/AEI/10.13039/501100011033 and ERDF “A way of making Europe”, by the grant PROMETEO/2019/098 funded by Generalitat Valenciana, and by the grant PCI2020-120708-2 funded by MICIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR.

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Authors and Affiliations

  1. VRAIN, Universitat Politècnica de València, Valencia, Spain

    Raúl López-Rueda & Santiago Escobar

Authors
  1. Raúl López-Rueda
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  2. Santiago Escobar
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Correspondence to Santiago Escobar .

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Editors and Affiliations

  1. Complutense University of Madrid, Madrid, Spain

    Adrian Riesco

  2. East China University of Science and Technology, Shanghai, China

    Min Zhang

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López-Rueda, R., Escobar, S. (2022). Canonical Narrowing for Variant-Based Conditional Rewrite Theories. In: Riesco, A., Zhang, M. (eds) Formal Methods and Software Engineering. ICFEM 2022. Lecture Notes in Computer Science, vol 13478. Springer, Cham. https://doi.org/10.1007/978-3-031-17244-1_2

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  • DOI: https://doi.org/10.1007/978-3-031-17244-1_2

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