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  2. Binary heap - Wikipedia

    en.wikipedia.org/wiki/Binary_heap

    The Build-Max-Heap function that follows, converts an array A which stores a complete binary tree with n nodes to a max-heap by repeatedly using Max-Heapify (down-heapify for a max-heap) in a bottom-up manner.

  3. Heap (data structure) - Wikipedia

    en.wikipedia.org/wiki/Heap_(data_structure)

    heapify: create a heap out of given array of elements; merge (union): joining two heaps to form a valid new heap containing all the elements of both, preserving the original heaps. meld: joining two heaps to form a valid new heap containing all the elements of both, destroying the original heaps. Inspection. size: return the number of items in ...

  4. Best, worst and average case - Wikipedia

    en.wikipedia.org/wiki/Best,_worst_and_average_case

    Heapsort has O(n) time when all elements are the same. Heapify takes O(n) time and then removing elements from the heap is O(1) time for each of the n elements. The run time grows to O(nlog(n)) if all elements must be distinct. Bogosort has O(n) time when the elements are sorted on the first iteration. In each iteration all elements are checked ...

  5. Heapsort - Wikipedia

    en.wikipedia.org/wiki/Heapsort

    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.

  6. Heap's algorithm - Wikipedia

    en.wikipedia.org/wiki/Heap's_algorithm

    A map of the 24 permutations and the 23 swaps used in Heap's algorithm permuting the four letters A (amber), B (blue), C (cyan) and D (dark red) Wheel diagram of all permutations of length = generated by Heap's algorithm, where each permutation is color-coded (1=blue, 2=green, 3=yellow, 4=red).

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  8. Min-max heap - Wikipedia

    en.wikipedia.org/wiki/Min-max_heap

    In computer science, a min-max heap is a complete binary tree data structure which combines the usefulness of both a min-heap and a max-heap, that is, it provides constant time retrieval and logarithmic time removal of both the minimum and maximum elements in it. [2]

  9. Fibonacci heap - Wikipedia

    en.wikipedia.org/wiki/Fibonacci_heap

    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.