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Queue overflow results from trying to add an element onto a full queue and queue underflow happens when trying to remove an element from an empty queue. A bounded queue is a queue limited to a fixed number of items. [1] There are several efficient implementations of FIFO queues.
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.
For queue, because enqueuing and dequeuing occur at opposite ends, peek cannot be implemented in terms of basic operations, and thus is often implemented separately. One case in which peek is not trivial is in an ordered list type (i.e., elements accessible in order) implemented by a self-balancing binary search tree.
A priority queue must at least support the following operations: is_empty: check whether the queue has no elements. insert_with_priority: add an element to the queue with an associated priority. pull_highest_priority_element: remove the element from the queue that has the highest priority, and return it.
the producer must wait for the consumer to consume something if the queue is full. The semaphore solution to the producer–consumer problem tracks the state of the queue with two semaphores: emptyCount, the number of empty places in the queue, and fullCount, the number of elements in the queue.
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.
In computer science, a priority search tree is a tree data structure for storing points in two dimensions. It was originally introduced by Edward M. McCreight. [1] It is effectively an extension of the priority queue with the purpose of improving the search time from O(n) to O(s + log n) time, where n is the number of points in the tree and s is the number of points returned by the search.
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 ...