Treffer: Automated higher-order complexity analysis

Title:
Automated higher-order complexity analysis
Authors:
Source:
Implicit computational complexityTheoretical computer science. 318(1-2):79-103
Publisher Information:
Amsterdam: Elsevier, 2004.
Publication Year:
2004
Physical Description:
print, 29 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science, Cornell University, Ithaca, NY 14853, United States
ISSN:
0304-3975
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.15839886
Database:
PASCAL Archive

Weitere Informationen

This paper describes the automated complexity analysis (ACA) system for automated higher-order complexity analysis of functional programs synthesized with the NUPRL 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.