Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

scholarly article

en

Auger, Nicolas; Jugé, Vincent; Nicaud, Cyril; Pivoteau, Carine

https://www.dagstuhl.de/lipics

On the Worst-Case Complexity of TimSort

Abstract TimSort is an intriguing sorting algorithm designed in 2002 for Python, whose worst-case complexity was announced, but not proved until our recent preprint. In fact, there are two slightly different versions of TimSort that are currently implemented in Python and in Java respectively. We propose a pedagogical and insightful proof that the Python version runs in O(n log n). The approach we use in the analysis also applies to the Java version, although not without very involved technical details. As a byproduct of our study, we uncover a bug in the Java implementation that can cause the sorting method to fail during the execution. We also give a proof that Python's TimSort running time is in O(n + n log rho), where rho is the number of runs (i.e. maximal monotonic sequences), which is quite a natural parameter here and part of the explanation for the good behavior of TimSort on partially sorted inputs.

BibTeX - Entry

@InProceedings{auger_et_al:LIPIcs:2018:9467, author = {Nicolas Auger and Vincent Jug{\'e} and Cyril Nicaud and Carine Pivoteau}, title = {{On the Worst-Case Complexity of TimSort}}, booktitle = {26th Annual European Symposium on Algorithms (ESA 2018)}, pages = {4:1--4:13}, 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/2018/9467}, URN = {urn:nbn:de:0030-drops-94678}, doi = {10.4230/LIPIcs.ESA.2018.4}, annote = {Keywords: Sorting algorithms, Merge sorting algorithms, TimSort, Analysis of algorithms} }