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  2. d-ary heap - Wikipedia

    en.wikipedia.org/wiki/D-ary_heap

    The d-ary heap or d-heap is a priority queue data structure, a generalization of the binary heap in which the nodes have d children instead of 2. [1] [2] [3] Thus, a binary heap is a 2-heap, and a ternary heap is a 3-heap. According to Tarjan [2] and Jensen et al., [4] d-ary heaps were invented by Donald B. Johnson in 1975. [1]

  3. Skew heap - Wikipedia

    en.wikipedia.org/wiki/Skew_heap

    The general heap order must be enforced; Every operation (add, remove_min, merge) on two skew heaps must be done using a special skew heap merge. A skew heap is a self-adjusting form of a leftist heap which attempts to maintain balance by unconditionally swapping all nodes in the merge path when merging two heaps. (The merge operation is also ...

  4. Heap (data structure) - Wikipedia

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

    Example of a binary max-heap with node keys being integers between 1 and 100. In computer science, a heap is a tree-based data structure that satisfies the heap property: In a max heap, for any given node C, if P is the parent node of C, then the key (the value) of P is greater than or equal to the key of C.

  5. Category:Heaps (data structures) - Wikipedia

    en.wikipedia.org/wiki/Category:Heaps_(data...

    A heap is a tree data structure with ordered nodes where the min (or max) value is the root of the tree and all children are less than (or greater than) their parent nodes. Pages in category "Heaps (data structures)"

  6. Binary heap - Wikipedia

    en.wikipedia.org/wiki/Binary_heap

    Example of a complete binary max-heap Example of a complete binary min heap. A binary heap is a heap data structure that takes the form of a binary tree.Binary heaps are a common way of implementing priority queues.

  7. Tree (abstract data type) - Wikipedia

    en.wikipedia.org/wiki/Tree_(abstract_data_type)

    The height of a node is the length of the longest downward path to a leaf from that node. The height of the root is the height of the tree. The depth of a node is the length of the path to its root (i.e., its root path). Thus the root node has depth zero, leaf nodes have height zero, and a tree with only a single node (hence both a root and ...

  8. Binary tree - Wikipedia

    en.wikipedia.org/wiki/Binary_tree

    A tree consisting of only a root node has a height of 0. The least number of nodes is obtained by adding only two children nodes per adding height so + (1 for counting the root node). The maximum number of nodes is obtained by fully filling nodes at each level, i.e., it is a perfect tree.

  9. Fibonacci heap - Wikipedia

    en.wikipedia.org/wiki/Fibonacci_heap

    A Fibonacci heap is a collection of trees satisfying the minimum-heap property, that is, the key of a child is always greater than or equal to the key of the parent. This implies that the minimum key is always at the root of one of the trees. Compared with binomial heaps, the structure of a Fibonacci heap is more flexible.

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