License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ESA.2018.63
URN: urn:nbn:de:0030-drops-95265
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9526/
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Munro, J. Ian ; Wild, Sebastian

Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs

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LIPIcs-ESA-2018-63.pdf (0.6 MB)

Abstract

We present two stable mergesort variants, "peeksort" and "powersort", that exploit existing runs and find nearly-optimal merging orders with negligible overhead. Previous methods either require substantial effort for determining the merging order (Takaoka 2009; Barbay & Navarro 2013) or do not have an optimal worst-case guarantee (Peters 2002; Auger, Nicaud & Pivoteau 2015; Buss & Knop 2018) . We demonstrate that our methods are competitive in terms of running time with state-of-the-art implementations of stable sorting methods.

BibTeX - Entry

@InProceedings{munro_et_al:LIPIcs:2018:9526,
  author =	{J. Ian Munro and Sebastian Wild},
  title =	{{Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs}},
  booktitle =	{26th Annual European Symposium on Algorithms (ESA 2018)},
  pages =	{63:1--63:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-081-1},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{112},
  editor =	{Yossi Azar and Hannah Bast and Grzegorz Herman},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9526},
  URN =		{urn:nbn:de:0030-drops-95265},
  doi =		{10.4230/LIPIcs.ESA.2018.63},
  annote =	{Keywords: adaptive sorting, nearly-optimal binary search trees, Timsort}
}

Keywords: adaptive sorting, nearly-optimal binary search trees, Timsort
Collection: 26th Annual European Symposium on Algorithms (ESA 2018)
Issue Date: 2018
Date of publication: 14.08.2018
Supplementary Material: https://zenodo.org/record/1241162 (code to reproduce running time study)

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