The right view of a binary tree is a list of nodes that are visible when the tree is viewed from the right side. In other words, it is a list of the last node in each level of the tree when viewed from the right. Here’s an example binary tree: The right view of … Read more
he left view of a binary tree is the set of nodes that are visible when the tree is viewed from the left side. In other words, it is the first node encountered at each level of the tree when traversing the tree from left to right. For example, consider the following binary tree: The … Read more
A mirror of a binary tree is a tree that is obtained by swapping the left and right subtrees of each node in the original tree. In other words, the mirror image of a binary tree is the reflection of the tree along its vertical axis. For example, consider the following binary tree: The mirror … Read more
The diameter of a binary tree is defined as the length of the longest path between any two nodes in the tree. This path may or may not pass through the root node. To calculate the diameter of a binary tree, we first find the heights of the left and right subtrees of each node. … Read more
To convert a Binary Search Tree (BST) into a Min Heap, you need to follow these steps: 1. TreeNode Class This class represents a node in a binary tree. It has three properties: value which stores the value of the node, left which points to the left child of the node, and right which points … Read more
A flattened binary search tree is a modified version of a binary search tree (BST) where all the nodes are arranged in a linear order. In a normal binary search tree, the left and right subtrees of each node are stored separately, which results in a tree-like structure. However, in a flattened binary search tree, … Read more
To merge two binary search trees, you can perform an in-order traversal on both trees and merge the resulting sorted arrays. Then, you can construct a new binary search tree from the sorted array using a modified version of the binary search tree creation algorithm. Here’s the general algorithm to merge two binary search trees: … Read more
To check if a binary tree is a binary search tree or not, we can perform an inorder traversal of the tree and check if the resulting sequence is in non-decreasing order. Here’s a Kotlin code implementation of this approach: The isValidBST function takes the root node of a binary tree and returns a boolean … Read more
To find the minimum and maximum values in a binary search tree, we can simply traverse the tree as follows: Example : Minimum value: 2 And Maximum value: 8 The findMin function starts at the root node and keeps traversing the left child nodes until it reaches a leaf node. It returns the value of … Read more
To delete a node in a binary search tree, we need to perform the following steps: The deleteNode function takes the root of the binary search tree and the key of the node to be deleted as input, and returns the updated root of the binary search tree after the deletion operation. The findSuccessor function … Read more
