Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
On the Worst-Case Complexity of TimSort
by
Nicaud, Cyril
, Jugé, Vincent
, Pivoteau, Carine
, Auger, Nicolas
in
Classification
/ Complexity
/ Java
/ Run time (computers)
/ Sequences
/ Sorting algorithms
2019
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
On the Worst-Case Complexity of TimSort
by
Nicaud, Cyril
, Jugé, Vincent
, Pivoteau, Carine
, Auger, Nicolas
in
Classification
/ Complexity
/ Java
/ Run time (computers)
/ Sequences
/ Sorting algorithms
2019
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Paper
On the Worst-Case Complexity of TimSort
2019
Request Book From Autostore
and Choose the Collection Method
Overview
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 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 )\\), where \\(\\) 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.
Publisher
Cornell University Library, arXiv.org
Subject
This website uses cookies to ensure you get the best experience on our website.