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Theoretical Computer Science
Volume 318, Issues 1-2, 6 June 2004, Pages 79-103
Implicit Computational Complexity
 
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doi:10.1016/j.tcs.2003.10.022    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2003 Elsevier B.V. All rights reserved.

Automated higher-order complexity analysis

R.Ralph BenzingerE-mail The Corresponding Author

Department of Computer Science, Cornell University, Ithaca, NY 14853, USA

Available online 13 November 2003.

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Abstract

This paper describes the automated complexity analysis (ACA) system for automated higher-order complexity analysis of functional programs synthesized with the NImage proof development system. We introduce a general framework for defining models of computational complexity for functional programs based on an annotation of a given operational language semantics. Within this framework, we use type decomposition and polynomialization to express the complexity of higher-order terms. Symbolic interpretation of open terms automates complexity analysis, which involves generating and solving higher-order recurrence equations. Finally, the use of the ACA system is demonstrated by analyzing three different implementations of the pigeonhole principle.

Author Keywords: Computational complexity analysis; Functional programs; Higher-order complexity; Program synthesis; Feasible mathematics

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Theoretical Computer Science
Volume 318, Issues 1-2, 6 June 2004, Pages 79-103
Implicit Computational Complexity
 
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