Search results
Results From The WOW.Com Content Network
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.
When a user asks to clear the browsing history for the past hour, the most recently added entries are removed. One example where a deque can be used is the work stealing algorithm. [9] This algorithm implements task scheduling for several processors. A separate deque with threads to be executed is maintained for each processor.
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 .
Circular buffering makes a good implementation strategy for a queue that has fixed maximum size. Should a maximum size be adopted for a queue, then a circular buffer is a completely ideal implementation; all queue operations are constant time. However, expanding a circular buffer requires shifting memory, which is comparatively costly.
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 bucket queue is the priority-queue analogue of pigeonhole sort (also called bucket sort), a sorting algorithm that places elements into buckets indexed by their priorities and then concatenates the buckets. Using a bucket queue as the priority queue in a selection sort gives a form of the pigeonhole sort algorithm. [2]
Input: A graph G and a starting vertex root of G. Output: Goal state.The parent links trace the shortest path back to root [9]. 1 procedure BFS(G, root) is 2 let Q be a queue 3 label root as explored 4 Q.enqueue(root) 5 while Q is not empty do 6 v := Q.dequeue() 7 if v is the goal then 8 return v 9 for all edges from v to w in G.adjacentEdges(v) do 10 if w is not labeled as explored then 11 ...
It remains to empty the other input list. while A is not empty do append head(A) to C drop the head of A while B is not empty do append head(B) to C drop the head of B return C When the inputs are linked lists, this algorithm can be implemented to use only a constant amount of working space; the pointers in the lists' nodes can be reused for ...