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  2. Min-max heap - Wikipedia

    en.wikipedia.org/wiki/Min-max_heap

    The path from the new node to the root (considering only min (max) levels) should be in a descending (ascending) order as it was before the insertion. So, we need to make a binary insertion of the new node into this sequence. Technically it is simpler to swap the new node with its parent while the parent is greater (less).

  3. Binary tree - Wikipedia

    en.wikipedia.org/wiki/Binary_tree

    A labeled binary tree of size 9 (the number of nodes in the tree) and height 3 (the height of a tree defined as the number of edges or links from the top-most or root node to the farthest leaf node), with a root node whose value is 1.

  4. Tree traversal - Wikipedia

    en.wikipedia.org/wiki/Tree_traversal

    To traverse arbitrary trees (not necessarily binary trees) with depth-first search, perform the following operations at each node: If the current node is empty then return. Visit the current node for pre-order traversal. For each i from 1 to the current node's number of subtrees − 1, or from the latter to the former for reverse traversal, do:

  5. Binary heap - Wikipedia

    en.wikipedia.org/wiki/Binary_heap

    A binary heap is defined as a binary tree with two additional constraints: [3] Shape property: a binary heap is a complete binary tree; that is, all levels of the tree, except possibly the last one (deepest) are fully filled, and, if the last level of the tree is not complete, the nodes of that level are filled from left to right.

  6. Tree (abstract data type) - Wikipedia

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

    This unsorted tree has non-unique values (e.g., the value 2 existing in different nodes, not in a single node only) and is non-binary (only up to two children nodes per parent node in a binary tree). The root node at the top (with the value 2 here), has no parent as it is the highest in the tree hierarchy.

  7. Adaptive heap sort - Wikipedia

    en.wikipedia.org/wiki/Adaptive_heap_sort

    First, a Cartesian tree is built from the input in () time by putting the data into a binary tree and making each node in the tree is greater(or smaller) than all its children nodes, and the root of the Cartesian tree is inserted into an empty binary heap. Then repeatedly extract the maximum from the binary heap, retrieve the maximum in the ...

  8. Binary search tree - Wikipedia

    en.wikipedia.org/wiki/Binary_search_tree

    Fig. 1: A binary search tree of size 9 and depth 3, with 8 at the root. In computer science, a binary search tree (BST), also called an ordered or sorted binary tree, is a rooted binary tree data structure with the key of each internal node being greater than all the keys in the respective node's left subtree and less than the ones in its right subtree.

  9. Weight-balanced tree - Wikipedia

    en.wikipedia.org/wiki/Weight-balanced_tree

    A weight-balanced tree is a binary search tree that stores the sizes of subtrees in the nodes. That is, a node has fields key, of any ordered type; value (optional, only for mappings) left, right, pointer to node; size, of type integer. By definition, the size of a leaf (typically represented by a nil pointer) is zero.