If the tree is balanced -> return height.The absolute between heights of left and right subtrees.The better way to implement this will be returning height in the same function.įor each node, we will return -1 if it is not balanced and the height of that node/subtree if it is balanced. This is going to be computationally inefficient. One way to do this is to write a separate function for calculating the height and call it every time height is needed. We will need a function that can calculate the height of the tree. For each node, its right subtree should be a balanced binary tree.For each node, its left subtree should be a balanced binary tree.The absolute difference between heights of left and right subtrees at any node should be less than 1.To check if a Binary tree is balanced we need to check three conditions : In an AVL tree if the difference between left and right subtrees is greater than 1 then it performs one of the following 4 rotations to rebalance itself :ĪVL tree How to Check if a Binary Tree is balanced? This means that in an AVL tree the difference between left subtree and right subtree height is at most one.ĪVL tree is a self-balancing binary search tree. If a binary search tree has a balance factor of one then it is an AVL ( Adelso-Velskii and Landis) tree. Fully Balanced Binary Tree Self Balancing Binary Search Tree If for a tree, the balance factor (k) is equal to zero, then that tree is known as a fully balanced binary tree. Height balanced binary trees can be denoted by HB(k), where k is the difference between heights of left and right subtrees. For each node, its right subtree is a balanced binary tree.īalanced binary trees are also known as height-balanced binary trees.For each node, its left subtree is a balanced binary tree.The absolute difference of heights of left and right subtrees at any node is less than 1.What is a Balanced Binary Treeīalanced Binary trees are computationally efficient to perform operations on.Ī balanced binary tree will follow the following conditions: Hence the need for balanced binary trees. This is the motivation behind making sure that trees are not skewed. In case of binary trees, if the trees are skewed, they become computationally inefficient to perform operations on.
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