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

2018 conference paper
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Summary

Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs is a conference paper[1].

Key Facts

  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs authored Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — author (P50): Ian Munro[2].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs authored Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — author (P50): Sebastian Wild[3].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's instance of is recorded as Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — instance of (P31): conference paper[4].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's publisher is recorded as Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — publisher (P123): Dagstuhl Publishing[5].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's copyright license is recorded as Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — copyright license (P275): Creative Commons Attribution 3.0 Unported[6].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's DOI is recorded as 10.4230/LIPICS.ESA.2018.63[7].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's DOI is recorded as 10.48550/ARXIV.1805.04154[8].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's DOI is recorded as 10.5281/ZENODO.1241162[9].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's language of work or name is recorded as Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — language of work or name (P407): English[10].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's publication date is recorded as +2018-08-14T00:00:00Z[11].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's arXiv ID is recorded as 1805.04154[12].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's ADS bibcode is recorded as 2018arXiv180504154M[13].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's zbMATH Open document ID is recorded as 1524.68113[14].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's main subject is recorded as Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — main subject (P921): merge sort[15].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's main subject is recorded as Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — main subject (P921): Timsort[16].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's work available at URL is recorded as https://www.wild-inter.net/publications/munro-wild-2018.pdf[17].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's described at URL is recorded as https://www.wild-inter.net/publications/munro-wild-2018[18].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's URL is recorded as https://github.com/sebawild/nearly-optimal-mergesort-code[19].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's Semantic Scholar paper ID is recorded as 971e53e34e6cd00e2ad2a277c432a8171ab47691[20].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's Google Scholar paper ID is recorded as 3982592541900879878[21].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's ResearchGate publication ID is recorded as 325118309[22].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's maintained by WikiProject is recorded as Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — maintained by WikiProject (P6104): WikiProject Mathematics[23].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's copyright status is recorded as Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — copyright status (P6216): copyrighted[24].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's PubPeer article ID is recorded as 983D341140D40F667461EED28A6115[25].
  • Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's Semantic Scholar corpus ID is recorded as 21678081[26].

Body

Designation and Status

Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs's instance of is recorded as Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — instance of (P31): conference paper[4].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [4] ↑ . wikidata.org.
  2. [2] ↑ . wikidata.org.
  3. [3] ↑ . wikidata.org.
  4. [5] ↑ . wikidata.org.
  5. [6] ↑ . wikidata.org.
  6. [7] ↑ . wikidata.org.
  7. [8] ↑ . wikidata.org.
  8. [9] ↑ . wikidata.org.
  9. [10] ↑ . wikidata.org.
  10. [11] ↑ . wikidata.org.
  11. [12] ↑ . wikidata.org.
  12. [13] ↑ . wikidata.org.
  13. [14] ↑ . wikidata.org.
  14. [15] ↑ . wikidata.org.
  15. [16] ↑ . wikidata.org.
  16. [17] ↑ . wikidata.org.
  17. [18] ↑ . wikidata.org.
  18. [19] ↑ . wikidata.org.
  19. [20] ↑ . wikidata.org.
  20. [21] ↑ . wikidata.org.
  21. [22] ↑ . wikidata.org.
  22. [23] ↑ . wikidata.org.
  23. [24] ↑ . wikidata.org.
  24. [25] ↑ . wikidata.org.
  25. [26] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs. Retrieved October 18, 2026, from https://4ort.xyz/entity/nearly-optimal-mergesorts-fast-practical-sorting-methods-that-optimally-adapt-to-existing-runs
MLA “Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs.” 4ort.xyz Knowledge Graph, 4ort.xyz, 18 Oct. 2026, https://4ort.xyz/entity/nearly-optimal-mergesorts-fast-practical-sorting-methods-that-optimally-adapt-to-existing-runs.
BibTeX @misc{4ortxyz_nearly-optimal-mergesorts-fast-practical-sorting-methods-that-optimally-adapt-to-existing-runs_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs}}, year = {2026}, url = {https://4ort.xyz/entity/nearly-optimal-mergesorts-fast-practical-sorting-methods-that-optimally-adapt-to-existing-runs}, note = {Accessed: 2026-10-18}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs — https://4ort.xyz/entity/nearly-optimal-mergesorts-fast-practical-sorting-methods-that-optimally-adapt-to-existing-runs (retrieved 2026-10-18)

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