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A Compiled Implementation of Normalization by Evaluation

  • Klaus Aehlig
  • Florian Haftmann
  • Tobias Nipkow
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5170)

Abstract

We present a novel compiled approach to Normalization by Evaluation (NBE) for ML-like languages. It supports efficient normalization of open λ-terms w.r.t. β-reduction and rewrite rules. We have implemented NBE and show both a detailed formal model of our implementation and its verification in Isabelle. Finally we discuss how NBE is turned into a proof rule in Isabelle.

Keywords

Pattern Match Default Rule Functional Language Partial Correctness Proof Rule 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Klaus Aehlig
    • 1
  • Florian Haftmann
    • 2
  • Tobias Nipkow
    • 2
  1. 1.Department of Computer ScienceSwansea UniversityUK
  2. 2.Institut für InformatikTechnische Universität MünchenGermany

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