Average-case analysis of algorithms using Kolmogorov complexity

Analyzing the average-case complexity of algorithms is a very practical but very difficult problem in computer science. In the past few years, we have demonstrated that Kolmogorov complexity is an important tool for analyzing the average-case complexity of algorithms. We have developed the incompres...

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Bibliographic Details
Published in:Journal of computer science and technology Vol. 15; no. 5; pp. 402 - 408
Main Authors: Jiang, Tao, Li, Ming, Vitányi, Paul M. B.
Format: Journal Article
Language:English
Published: Beijing Springer Nature B.V 01.09.2000
Department of Computing Science, University of California, Riverside, CA 92521, USA%Department of Computer Science, University of California, Santa Barbara, CA 93106, USA%CWI and University of Amsterdam, Kruislaan 413, 1098 SJ Amsterdam, The Netherlands
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ISSN:1000-9000, 1860-4749
Online Access:Get full text
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Summary:Analyzing the average-case complexity of algorithms is a very practical but very difficult problem in computer science. In the past few years, we have demonstrated that Kolmogorov complexity is an important tool for analyzing the average-case complexity of algorithms. We have developed the incompressibility method. In this paper, several simple examples are used to further demonstrate the power and simplicity of such method. We prove bounds on the average-case number of stacks (queues) required for sorting sequential or parallel Queuesort or Stacksort.
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ISSN:1000-9000
1860-4749
DOI:10.1007/BF02950402