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A double-ended queue is represented as a sextuple (len_front, front, tail_front, len_rear, rear, tail_rear) where front is a linked list which contains the front of the queue of length len_front. Similarly, rear is a linked list which represents the reverse of the rear of the queue, of length len_rear.
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.
Queues may be implemented as a separate data type, or maybe considered a special case of a double-ended queue (deque) and not implemented separately. For example, Perl and Ruby allow pushing and popping an array from both ends, so one can use push and shift functions to enqueue and dequeue a list (or, in reverse, one can use unshift and pop ...
Queue; Priority queue (such as a heap) Double-ended queue (deque) Double-ended priority queue (DEPQ) Single-ended types, such as stack, generally only admit a single peek, at the end that is modified. Double-ended types, such as deques, admit two peeks, one at each end. Names for peek vary.
A priority queue is an abstract data type like ... Python's heapq module implements a binary min ... with a double-ended priority queue to allow removal of low ...
The data structure implementing such a collection need not be linear. For example, a priority queue is often implemented as a heap, which is a kind of tree. Notable linear collections include: list; stack; queue; priority queue; double-ended queue; double-ended priority queue
The first version combines the properties of the double-ended queue (deque) and a priority queue and may be described as an ordered deque.. An item may be added to the head of the list if the new item is valued less than or equal to the current head or to the tail of the list if the new item is greater than or equal to the current tail.
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.