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This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures.
The semantics of priority queues naturally suggest a sorting method: insert all the elements to be sorted into a priority queue, and sequentially remove them; they will come out in sorted order. This is actually the procedure used by several sorting algorithms , once the layer of abstraction provided by the priority queue is removed.
Given a class of input objects, find efficient algorithms and data structures to answer a certain query about a set of input objects each time the input data is modified, i.e., objects are inserted or deleted. Problems in this class have the following measures of complexity: Space – the amount of memory space required to store the data structure;
Using a bucket queue as the priority queue in a selection sort gives a form of the pigeonhole sort algorithm. [2] Bucket queues are also called bucket priority queues [3] or bounded-height priority queues. [1] When used for quantized approximations to real number priorities, they are also called untidy priority queues [4] or pseudo priority ...
A min-priority queue is an abstract data type that provides 3 basic operations: add_with_priority(), decrease_priority() and extract_min(). As mentioned earlier, using such a data structure can lead to faster computing times than using a basic queue. Notably, Fibonacci heap [19] or Brodal queue offer optimal implementations for those 3 ...
This is optimal, because any priority queue can be used to sort a list of elements by performing insertions and delete-min operations. [2] However, strict Fibonacci heaps are simpler than Brodal queues, which make use of dynamic arrays and redundant counters, [ 3 ] whereas the strict Fibonacci heap is pointer based only.
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]
Associative containers are used in programming languages as class templates. Container abstract data types include: FIFO queues; LIFO stacks; Priority queues; Lookup tables (LUTs) Key-associated data structures. Sets, containing and indexing objects by value or by specific property; Maps, associating to each key a "value" for lookup