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This paper introduces a novel and efficient partitioning technique for quicksort, specifically designed for real-world data with duplicate elements (50-year-old problem). The method is referred to as "equal quicksort" or "eqsort". Based on…

Data Structures and Algorithms · Computer Science 2025-03-12 Parviz Afereidoon

We present an average case analysis of two variants of dual-pivot quicksort, one with a non-algorithmic comparison-optimal partitioning strategy, the other with a closely related algorithmic strategy. For both we calculate the expected…

This work presents a comparison for the performance of sequential sorting algorithms under four different modes of execution, the sequential processing mode, a conventional multi-threading implementation, multi-threading with OpenMP Library…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-07 Mohammad Fasha

Sorting and hashing are two completely different concepts in computer science, and appear mutually exclusive to one another. Hashing is a search method using the data as a key to map to the location within memory, and is used for rapid…

Data Structures and Algorithms · Computer Science 2007-05-23 William F. Gilreath

QuickXsort is a strategy to combine Quicksort with another sorting method X, so that the result has essentially the same comparison cost as X in isolation, but sorts in place even when X requires a linear-size buffer. We solve the…

Data Structures and Algorithms · Computer Science 2019-05-07 Sebastian Wild

We revisit the method of Kirschenhofer, Prodinger and Tichy to calculate the moments of comparisons used by the quick sort algorithm. We reemphasize that this approach helps in calculating these quantities with less computation. We also…

Data Structures and Algorithms · Computer Science 2017-04-13 Sumit Kumar Jha

We address the problem of learning a ranking by using adaptively chosen pairwise comparisons. Our goal is to recover the ranking accurately but to sample the comparisons sparingly. If all comparison outcomes are consistent with the ranking,…

Machine Learning · Statistics 2017-06-16 Lucas Maystre , Matthias Grossglauser

The Quickselect algorithm (also called FIND) is a fundamental algorithm for selecting ranks or quantiles within a set of data. Gr\"ubel and R\"osler showed that the number of key comparisons required by Quickselect considered as a process…

Probability · Mathematics 2024-12-31 Jasper Ischebeck , Ralph Neininger

In this note the precise minimum number of key comparisons any dual-pivot quickselect algorithm (without sampling) needs on average is determined. The result is in the form of exact as well as asymptotic formul\ae{} of this number of a…

Combinatorics · Mathematics 2016-10-18 Daniel Krenn

We present a new analysis for QuickHeapsort splitting it into the analysis of the partition-phases and the analysis of the heap-phases. This enables us to consider samples of non-constant size for the pivot selection and leads to better…

Data Structures and Algorithms · Computer Science 2013-07-12 Volker Diekert , Armin Weiss

Smoothed analysis is a framework for analyzing the complexity of an algorithm, acting as a bridge between average and worst-case behaviour. For example, Quicksort and the Simplex algorithm are widely used in practical applications, despite…

Machine Learning · Computer Science 2015-03-29 Bichen Shi , Michel Schellekens , Georgiana Ifrim

Modern comparison sorts like quicksort suffer from performance inconsistencies due to suboptimal pivot selection, leading to $(O(N^2))$ worst-case complexity, while in-place merge sort variants face challenges with data movement overhead.…

Data Structures and Algorithms · Computer Science 2026-01-06 Jia Xu Wei

We explore the fundamental problem of sorting through the lens of learning-augmented algorithms, where algorithms can leverage possibly erroneous predictions to improve their efficiency. We consider two different settings: In the first…

Data Structures and Algorithms · Computer Science 2023-11-03 Xingjian Bai , Christian Coester

In-place associative integer sorting technique was proposed for integer lists which requires only constant amount of additional memory replacing bucket sort, distribution counting sort and address calculation sort family of algorithms. The…

Data Structures and Algorithms · Computer Science 2012-09-18 A. Emre Cetin

Semisort is a fundamental algorithmic primitive widely used in the design and analysis of efficient parallel algorithms. It takes input as an array of records and a function extracting a \emph{key} per record, and reorders them so that…

Data Structures and Algorithms · Computer Science 2023-04-21 Xiaojun Dong , Yunshu Wu , Zhongqi Wang , Laxman Dhulipala , Yan Gu , Yihan Sun

When the search algorithm QuickSelect compares keys during its execution in order to find a key of target rank, it must operate on the keys' representations or internal structures, which were ignored by the previous studies that quantified…

Probability · Mathematics 2012-09-24 James Allen Fill , Takehiko Nakama

This paper discusses about a sorting algorithm which uses the concept of buckets where each bucket represents a certain number of digits. A two dimensional data structure is used where one dimension represents buckets i. e; number of digits…

Data Structures and Algorithms · Computer Science 2014-06-10 Ankit Chadha , Rishikesh Misal , Tanaya Mokashi , Aman Chadha

This paper studies the average complexity on the number of comparisons for sorting algorithms. Its information-theoretic lower bound is $n \lg n - 1.4427n + O(\log n)$. For many efficient algorithms, the first $n\lg n$ term is easy to…

Data Structures and Algorithms · Computer Science 2017-05-03 Kazuo Iwama , Junichi Teruyama

Quicksort is a classical divide-and-conquer sorting algorithm. It is a comparison sort that makes an average of $2(n+1)H_n - 4n$ comparisons on an array of size $n$ ordered uniformly at random, where $H_n = \sum_{i=1}^n\frac{1}{i}$ is the…

Combinatorics · Mathematics 2023-06-23 Pamela E. Harris , Jan Kretschmann , J. Carlos Martínez Mori

A common problem in machine learning is to rank a set of n items based on pairwise comparisons. Here ranking refers to partitioning the items into sets of pre-specified sizes according to their scores, which includes identification of the…

Machine Learning · Computer Science 2018-01-08 Reinhard Heckel , Max Simchowitz , Kannan Ramchandran , Martin J. Wainwright