Theory of higher order interpretations and application to Basic Feasible Functions

Interpretation methods and their restrictions to polynomials have been deeply used to control the termination and complexity of first-order term rewrite systems. This paper extends interpretation methods to a pure higher order functional language. We develop a theory of higher order functions that i...

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Main Authors: Emmanuel Hainry, Romain Péchoux
Format: Article
Language:English
Published: Logical Methods in Computer Science e.V. 2020-12-01
Series:Logical Methods in Computer Science
Subjects:
Online Access:https://lmcs.episciences.org/4237/pdf
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author Emmanuel Hainry
Romain Péchoux
author_facet Emmanuel Hainry
Romain Péchoux
author_sort Emmanuel Hainry
collection DOAJ
description Interpretation methods and their restrictions to polynomials have been deeply used to control the termination and complexity of first-order term rewrite systems. This paper extends interpretation methods to a pure higher order functional language. We develop a theory of higher order functions that is well-suited for the complexity analysis of this programming language. The interpretation domain is a complete lattice and, consequently, we express program interpretation in terms of a least fixpoint. As an application, by bounding interpretations by higher order polynomials, we characterize Basic Feasible Functions at any order.
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spelling doaj.art-02875a8e58dc40e4a4d4ebaa9e30ce4e2024-03-08T10:32:05ZengLogical Methods in Computer Science e.V.Logical Methods in Computer Science1860-59742020-12-01Volume 16, Issue 410.23638/LMCS-16(4:14)20204237Theory of higher order interpretations and application to Basic Feasible FunctionsEmmanuel HainryRomain PéchouxInterpretation methods and their restrictions to polynomials have been deeply used to control the termination and complexity of first-order term rewrite systems. This paper extends interpretation methods to a pure higher order functional language. We develop a theory of higher order functions that is well-suited for the complexity analysis of this programming language. The interpretation domain is a complete lattice and, consequently, we express program interpretation in terms of a least fixpoint. As an application, by bounding interpretations by higher order polynomials, we characterize Basic Feasible Functions at any order.https://lmcs.episciences.org/4237/pdfcomputer science - logic in computer sciencecomputer science - computational complexitycomputer science - programming languages
spellingShingle Emmanuel Hainry
Romain Péchoux
Theory of higher order interpretations and application to Basic Feasible Functions
Logical Methods in Computer Science
computer science - logic in computer science
computer science - computational complexity
computer science - programming languages
title Theory of higher order interpretations and application to Basic Feasible Functions
title_full Theory of higher order interpretations and application to Basic Feasible Functions
title_fullStr Theory of higher order interpretations and application to Basic Feasible Functions
title_full_unstemmed Theory of higher order interpretations and application to Basic Feasible Functions
title_short Theory of higher order interpretations and application to Basic Feasible Functions
title_sort theory of higher order interpretations and application to basic feasible functions
topic computer science - logic in computer science
computer science - computational complexity
computer science - programming languages
url https://lmcs.episciences.org/4237/pdf
work_keys_str_mv AT emmanuelhainry theoryofhigherorderinterpretationsandapplicationtobasicfeasiblefunctions
AT romainpechoux theoryofhigherorderinterpretationsandapplicationtobasicfeasiblefunctions