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Since the invention of the pairing heap by Fredman, Sedgewick, Sleator, and Tarjan, it has been an open question whether this or any other simple "self-adjusting" heap supports decrease-key operations in $O(\log\log n)$ time, where $n$ is…

Data Structures and Algorithms · Computer Science 2025-02-13 Corwin Sinnamon , Robert E. Tarjan

A lower bound is presented which shows that a class of heap algorithms in the pointer model with only heap pointers must spend Omega(log log n / log log log n) amortized time on the decrease-key operation (given O(log n) amortized-time…

Data Structures and Algorithms · Computer Science 2013-07-17 John Iacono

The smooth heap and the closely related slim heap are recently invented self-adjusting implementations of the heap (priority queue) data structure. We analyze the efficiency of these data structures. We obtain the following amortized bounds…

Data Structures and Algorithms · Computer Science 2021-11-08 Corwin Sinnamon , Robert E. Tarjan

Improving the structure and analysis in \cite{elm0}, we give a variation of the pairing heaps that has amortized zero cost per meld (compared to an $O(\log \log{n})$ in \cite{elm0}) and the same amortized bounds for all other operations.…

Data Structures and Algorithms · Computer Science 2009-04-09 Amr Elmasry

We introduce a new family of priority-queue data structures: partition-based simple heaps. The structures consist of $O(\log n)$ doubly-linked lists; order is enforced among data in different lists, but the individual lists are unordered.…

Data Structures and Algorithms · Computer Science 2026-03-03 Gerth Stølting Brodal , John Iacono , Casper Moldrup Rysgaard , Sebastian Wild

Let $n$ denote the number of elements currently in a data structure. An in-place heap is stored in the first $n$ locations of an array, uses $O(1)$ extra space, and supports the operations: minimum, insert, and extract-min. We introduce an…

Data Structures and Algorithms · Computer Science 2014-07-15 Stefan Edelkamp , Jyrki Katajainen , Amr Elmasry

The pairing heap is a classical heap data structure introduced in 1986 by Fredman, Sedgewick, Sleator, and Tarjan. It is remarkable both for its simplicity and for its excellent performance in practice. The "magic" of pairing heaps lies in…

Data Structures and Algorithms · Computer Science 2018-06-22 Dani Dorfman , Haim Kaplan , László Kozma , Uri Zwick

We give a priority queue that achieves the same amortized bounds as Fibonacci heaps. Namely, find-min requires O(1) worst-case time, insert, meld and decrease-key require O(1) amortized time, and delete-min requires $O(\log n)$ amortized…

Data Structures and Algorithms · Computer Science 2010-02-11 Amr Elmasry

We improve the lower bound on the amortized cost of the decrease-key operation in the pure heap model and show that any pure-heap-model heap (that has a \bigoh{\log n} amortized-time extract-min operation) must spend \bigom{\log\log n}…

Data Structures and Algorithms · Computer Science 2014-07-25 John Iacono , Özgür Özkan

We show the $O(\log n)$ time extract minimum function of efficient priority queues can be generalized to the extraction of the $k$ smallest elements in $O(k \log(n/k))$ time (we define $\log(x)$ as $\max(\log_2(x), 1)$.), which we prove…

Data Structures and Algorithms · Computer Science 2022-01-11 Bryce Sandlund , Lingyi Zhang

We introduce the hollow heap, a very simple data structure with the same amortized efficiency as the classical Fibonacci heap. All heap operations except delete and delete-min take $O(1)$ time, worst case as well as amortized; delete and…

Data Structures and Algorithms · Computer Science 2015-10-23 Thomas Dueholm Hansen , Haim Kaplan , Robert E. Tarjan , Uri Zwick

The binary heap of Williams (1964) is a simple priority queue characterized by only storing an array containing the elements and the number of elements $n$ - here denoted a strictly implicit priority queue. We introduce two new strictly…

Data Structures and Algorithms · Computer Science 2015-05-04 Gerth Stølting Brodal , Jesper Sindahl Nielsen , Jakob Truelsen

Chazelle [JACM00] introduced the soft heap as a building block for efficient minimum spanning tree algorithms, and recently Kaplan et al. [SOSA2019] showed how soft heaps can be applied to achieve simpler algorithms for various selection…

Data Structures and Algorithms · Computer Science 2020-08-13 Gerth Stølting Brodal

The Fibonacci heap is a classic data structure that supports deletions in logarithmic amortized time and all other heap operations in O(1) amortized time. We explore the design space of this data structure. We propose a version with the…

Data Structures and Algorithms · Computer Science 2014-07-23 Haim Kaplan , Robert E. Tarjan , Uri Zwick

The heap is a basic data structure used in a wide variety of applications, including shortest path and minimum spanning tree algorithms. In this paper we explore the design space of comparison-based, amortized-efficient heap…

Data Structures and Algorithms · Computer Science 2009-03-03 Bernhard Haeupler , Siddhartha Sen , Robert E. Tarjan

Most hash tables have an insertion time of $O(1)$, possibly qualified as expected and/or amortised. While insertions into cuckoo hash tables indeed seem to take $O(1)$ expected time in practice, only polylogarithmic guarantees are proven in…

Data Structures and Algorithms · Computer Science 2022-04-26 Stefan Walzer

We revisit multipass pairing heaps and path-balanced binary search trees (BSTs), two classical algorithms for data structure maintenance. The pairing heap is a simple and efficient "self-adjusting" heap, introduced in 1986 by Fredman,…

Data Structures and Algorithms · Computer Science 2018-06-25 Dani Dorfman , Haim Kaplan , László Kozma , Seth Pettie , Uri Zwick

The smooth heap is a recently introduced self-adjusting heap [Kozma, Saranurak, 2018] similar to the pairing heap [Fredman, Sedgewick, Sleator, Tarjan, 1986]. The smooth heap was obtained as a heap-counterpart of Greedy BST, a binary search…

Data Structures and Algorithms · Computer Science 2021-07-13 Maria Hartmann , László Kozma , Corwin Sinnamon , Robert E. Tarjan

Explorable heap selection is the problem of selecting the $n$th smallest value in a binary heap. The key values can only be accessed by traversing through the underlying infinite binary tree, and the complexity of the algorithm is measured…

Data Structures and Algorithms · Computer Science 2024-09-12 Sander Borst , Daniel Dadush , Sophie Huiberts , Danish Kashaev

We present the first potential function for pairing heaps with linear range. This implies that the runtime of a short sequence of operations is faster than previously known. It is also simpler than the only other potential function known to…

Data Structures and Algorithms · Computer Science 2016-06-28 John Iacono , Mark Yagnatinsky
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