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In addition to the heap property, leftist trees are maintained so the right descendant of each node has the lower s-value. The height-biased leftist tree was invented by Clark Allan Crane. [2] The name comes from the fact that the left subtree is usually taller than the right subtree. A leftist tree is a mergeable heap. When inserting a new ...
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 leaf) has depth and height zero.
In computer science, a binary tree is a tree data structure in which each node has at most two children, referred to as the left child and the right child. That is, it is a k -ary tree with k = 2 . A recursive definition using set theory is that a binary tree is a tuple ( L , S , R ), where L and R are binary trees or the empty set and S is a ...
6-ary tree represented as a binary tree. Every multi-way or k-ary tree structure studied in computer science admits a representation as a binary tree, which goes by various names including child-sibling representation, [1] left-child, right-sibling binary tree, [2] doubly chained tree or filial-heir chain. [3]
A simple ternary tree of size 10 and height 2. In computer science, a ternary tree is a tree data structure in which each node has at most three child nodes, usually distinguished as "left", “mid” and "right". Nodes with children are parent nodes, and child nodes may contain references to their parents.
Animation showing the insertion of several elements into an AVL tree. It includes left, right, left-right and right-left rotations. Fig. 1: AVL tree with balance factors (green) In computer science, an AVL tree (named after inventors Adelson-Velsky and Landis) is a self-balancing binary search tree.
In other words, the minimum height of a binary tree with n nodes is log 2 (n), rounded down; that is, ⌊ ⌋. [1] However, the simplest algorithms for BST item insertion may yield a tree with height n in rather common situations. For example, when the items are inserted in sorted key order, the tree degenerates into a linked list with n nodes.
In these trees, each node contains one of the input points. Since the division of the plane is decided by the order of point-insertion, the tree's height is sensitive to and dependent on insertion order. Inserting in a "bad" order can lead to a tree of height linear in the number of input points (at which point it becomes a linked-list).