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In computer science, a priority queue is an abstract data type similar to a regular queue or stack abstract data type. Each element in a priority queue has an associated priority. In a priority queue, elements with high priority are served before elements with low priority. In some implementations, if two elements have the same priority, they ...
In computer science, a Fibonacci heap is a data structure for priority queue operations, consisting of a collection of heap-ordered trees. It has a better amortized running time than many other priority queue data structures including the binary heap and binomial heap. Michael L. Fredman and Robert E. Tarjan developed Fibonacci heaps in 1984 ...
In computer science, a double-ended priority queue (DEPQ)[1] or double-ended heap[2] is a data structure similar to a priority queue or heap, but allows for efficient removal of both the maximum and minimum, according to some ordering on the keys (items) stored in the structure. Every element in a DEPQ has a priority or value.
A van Emde Boas tree (Dutch pronunciation: [vɑn ˈɛmdə ˈboːɑs]), also known as a vEB tree or van Emde Boas priority queue, is a tree data structure which implements an associative array with m -bit integer keys. It was invented by a team led by Dutch computer scientist Peter van Emde Boas in 1975. [ 1 ] It performs all operations in O ...
Decrease-key. Θ (log n) O (log n) Merge. Θ (log n) O (log n) In computer science, a binomial heap is a data structure that acts as a priority queue. It is an example of a mergeable heap (also called meldable heap), as it supports merging two heaps in logarithmic time. It is implemented as a heap similar to a binary heap but using a special ...
Fig. 1: A binary search tree of size 9 and depth 3, with 8 at the root. In computer science, a binary search tree (BST), also called an ordered or sorted binary tree, is a rooted binary tree data structure with the key of each internal node being greater than all the keys in the respective node's left subtree and less than the ones in its right subtree.
This makes the min-max heap a very useful data structure to implement a double-ended priority queue. Like binary min-heaps and max-heaps, min-max heaps support logarithmic insertion and deletion and can be built in linear time. [3] Min-max heaps are often represented implicitly in an array; [4] hence it's referred to as an implicit data structure.
A queue is an example of a linear data structure, or more abstractly a sequential collection. Queues are common in computer programs, where they are implemented as data structures coupled with access routines, as an abstract data structure or in object-oriented languages as classes. A queue has two ends, the top, which is the only position at ...