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The heapsort algorithm can be divided into two phases: heap construction, and heap extraction. The heap is an implicit data structure which takes no space beyond the array of objects to be sorted; the array is interpreted as a complete binary tree where each array element is a node and each node's parent and child links are defined by simple arithmetic on the array indexes.
In computer science, adaptive heap sort is a comparison-based sorting algorithm of the adaptive sort family. It is a variant of heap sort that performs better when the data contains existing order. Published by Christos Levcopoulos and Ola Petersson in 1992, the algorithm utilizes a new measure of presortedness, Osc, as the number of ...
[6] [7] The heap array is assumed to have its first element at index 1. // Push a new item to a (max) heap and then extract the root of the resulting heap. // heap: an array representing the heap, indexed at 1 // item: an element to insert // Returns the greater of the two between item and the root of heap.
Using pointers, an in-place heap algorithm [2] allocates a min-heap of pointers into the input arrays. Initially these pointers point to the smallest elements of the input array. The pointers are sorted by the value that they point to. In an O(k) preprocessing step the heap is created using the standard heapify procedure.
Worst case is the function which performs the maximum number of steps on input data of size n. Average case is the function which performs an average number of steps on input data of n elements. In real-time computing , the worst-case execution time is often of particular concern since it is important to know how much time might be needed in ...
Weak heaps may be used to sort an array, in essentially the same way as a conventional heapsort. [3] First, a weak heap is built out of all of the elements of the array, and then the root is repeatedly exchanged with the last element, which is sifted down to its proper place. A weak heap of n elements can be formed in n − 1 merges. It can be ...
Dijkstra's algorithm starts with infinite distances and tries to improve them step by step: Create a set of all unvisited nodes: the unvisited set. Assign to every node a distance from start value: for the starting node, it is zero, and for all other nodes, it is infinity, since initially no path is known to these nodes.
Comparison-based sorting algorithms have traditionally dealt with achieving an optimal bound of O(n log n) when dealing with time complexity.Adaptive sort takes advantage of the existing order of the input to try to achieve better times, so that the time taken by the algorithm to sort is a smoothly growing function of the size of the sequence and the disorder in the sequence.