Copyright © 2003 Elsevier B.V. All rights reserved.
Automated higher-order complexity analysis
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 N
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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