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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.
Examples of FIFO status flags include: full, empty, almost full, and almost empty. A FIFO is empty when the read address register reaches the write address register. A FIFO is full when the write address register reaches the read address register. Read and write addresses are initially both at the first memory location and the FIFO queue is empty.
Behavior when the collection is empty varies – most often this yields an underflow error, identically to a pop on an empty collection, but some implementations provide a function which instead simply returns (without error), essentially implementing if isempty then return, else peek. This behavior can be axiomatized in various ways.
Its amortized time is O(1) if the persistency is not used; but the worst-time complexity of an operation is O(n) where n is the number of elements in the double-ended queue. Let us recall that, for a list l, |l| denotes its length, that NIL represents an empty list and CONS(h, t) represents the list whose head is h and whose tail is t.
function insertAfter(Node node, Node newNode) if node = null // assume list is empty newNode.next := newNode else newNode.next := node.next node.next := newNode update lastNode variable if necessary Suppose that "L" is a variable pointing to the last node of a circular linked list (or null if the list is empty).
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.
In addition we assume that for each condition variable c, there is a queue c.q, which is a queue for threads waiting on condition variable c; All queues are typically guaranteed to be fair and, in some implementations, may be guaranteed to be first in first out. The implementation of each operation is as follows.
create-queue(q): create an empty kinetic priority queue q; find-max(q, t) (or find-min): - return the max (or min for a min-queue) value stored in the queue q at the current virtual time t. insert(X, f X, t): - insert a key X into the kinetic queue at the current virtual time t, whose value changes as a continuous function f X (t) of time t.