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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.
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.
A sorting algorithm can also be used to implement a priority queue. Specifically, Thorup says: [ 21 ] We present a general deterministic linear space reduction from priority queues to sorting implying that if we can sort up to n keys in S ( n ) time per key, then there is a priority queue supporting delete and insert in O ( S ( n )) time and ...
In computer science, a Fibonacci heap is a data structure for priority queue operations, consisting of a collection of heap-ordered trees.It has a better amortized running time than many other priority queue data structures including the binary heap and binomial heap.
The dynamic array approach uses a variant of a dynamic array that can grow from both ends, sometimes called array deques. These array deques have all the properties of a dynamic array, such as constant-time random access , good locality of reference , and inefficient insertion/removal in the middle, with the addition of amortized constant-time ...
Another variant of bucket sort known as histogram sort or counting sort adds an initial pass that counts the number of elements that will fall into each bucket using a count array. [4] Using this information, the array values can be arranged into a sequence of buckets in-place by a sequence of exchanges, leaving no space overhead for bucket ...
A good example that highlights the pros and cons of using dynamic arrays vs. linked lists is by implementing a program that resolves the Josephus problem. The Josephus problem is an election method that works by having a group of people stand in a circle. Starting at a predetermined person, one may count around the circle n times.
Implementing a DEPQ using interval heap. Apart from the above-mentioned correspondence methods, DEPQ's can be obtained efficiently using interval heaps. [6] An interval heap is like an embedded min-max heap in which each node contains two elements. It is a complete binary tree in which: [6] The left element is less than or equal to the right ...