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A survey of adaptive sorting algorithms
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Source ACM Computing Surveys (CSUR) archive
Volume 24 ,  Issue 4  (December 1992) table of contents
Pages: 441 - 476  
Year of Publication: 1992
ISSN:0360-0300
Authors
Vladmir Estivill-Castro  LANIA, Veracruz, Mexico
Derick Wood  Univ. of Western Ontario, London, Ont., Canada
Publisher
ACM  New York, NY, USA
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ABSTRACT

The design and analysis of adaptive sorting algorithms has made important contributions to both theory and practice. The main contributions from the theoretical point of view are: the description of the complexity of a sorting algorithm not only in terms of the size of a problem instance but also in terms of the disorder of the given problem instance; the establishment of new relationships among measures of disorder; the introduction of new sorting algorithms that take advantage of the existing order in the input sequence; and, the proofs that several of the new sorting algorithms achieve maximal (optimal) adaptivity with respect to several measures of disorder. The main contributions from the practical point of view are: the demonstration that several algorithms currently in use are adaptive; and, the development of new algorithms, similar to currently used algorithms that perform competitively on random sequences and are significantly faster on nearly sorted sequences. In this survey, we present the basic notions and concepts of adaptive sorting and the state of the art of adaptive sorting algorithms.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  18


REVIEW

"Linda Pagli : Reviewer"

A complete and clear survey of the theory of adaptive sorting algorithms is provided. In the first part, the basic notions and concepts of adaptive sorting are introduced: if the input sequence to be sorted is already partially sorted, then a   more...

Collaborative Colleagues:
Vladmir Estivill-Castro: colleagues
Derick Wood: colleagues