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A queue has two ends, the top, which is the only position at which the push operation may occur, and the bottom, which is the only position at which the pop operation may occur. A queue may be implemented as circular buffers and linked lists, or by using both the stack pointer and the base pointer.
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 double-ended queue can be used to store the browsing history: new websites are added to the end of the queue, while the oldest entries will be deleted when the history is too large. When a user asks to clear the browsing history for the past hour, the most recently added entries are removed.
STL also has utility functions for manipulating another random-access container as a binary max-heap. The Boost libraries also have an implementation in the library heap. Python's heapq module implements a binary min-heap on top of a list. Java's library contains a PriorityQueue class, which implements a min-priority-queue as a binary heap.
CEF 3 is a multi-process implementation based on the Chromium Content API and has performance similar to Google Chrome. [6] It uses asynchronous messaging to communicate between the main application process and one or more render processes ( Blink + V8 JavaScript engine).
Priority queue: A priority queue is an abstract concept like "a list" or "a map"; just as a list can be implemented with a linked list or an array, a priority queue can be implemented with a heap or a variety of other methods. K-way merge: A heap data structure is useful to merge many already-sorted input streams into a single sorted output ...
A standard exercise in algorithm design asks for an implementation of this algorithm that takes linear time in the input size, which is the sum of sizes of all the input sets. [19] This may be solved using a bucket queue of sets in the input family, prioritized by the number of remaining elements that they cover.
For the stack, priority queue, deque, and DEPQ types, peek can be implemented in terms of pop and push (if done at same end). For stacks and deques this is generally efficient, as these operations are O (1) in most implementations, and do not require memory allocation (as they decrease the size of the data) – the two ends of a deque each ...