To make technologies simpler
by Given an array of sizen, the array contains numbers in range from 0 to k-1 wherekis a positive integer and k <= n.
Find the maximum repeating number in this array.
For example:
Input arr = [1,3,4,5,6,7,4]
Maximum occurence element = 4
Maximum occurence = 2
by Given an unsorted array of size n. Array elements are in range from 1 to n.
One number from set {1, 2, …n} is missing and one number occurs twice in array.
Find these two numbers.
For example:
Input arr = [1,3,4,5,6,7,4]
Missing Item = 2
Duplicate Item = 4
by An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.
For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.
In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n). Before going ahead have a look into AVL Tree Basics.
(more…)by An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.
For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.
In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n). Before going ahead have a look into AVL Tree Basics.
(more…)by An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.
For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.
For every node in an AVL Tree, the difference between the height of its left subtree and right subtree should not be more than 1. Whenever insertion makes a node unbalanced, AVL rotations are used to balance the tree again.
In this article, let’s look into the Right-Left Rotation, also called RL Rotation.
In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n). Before going ahead have a look into AVL Tree Basics.
(more…)by An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.
For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.
For every node in an AVL Tree, the difference between the height of its left subtree and right subtree should not be more than 1. Whenever insertion makes a node unbalanced, AVL rotations are used to balance the tree again.
In this article, let’s look into the Left-Right Rotation, also called LR Rotation.
In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n). Before going ahead have a look into AVL Tree Basics.
(more…)by An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.
For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.
For every node in an AVL Tree, the difference between the height of its left subtree and right subtree should not be more than 1. Whenever insertion makes a node unbalanced, AVL rotations are used to balance the tree again.
In this article, let’s look into the RR imbalance case and the Left Rotation used to fix it.
In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n). Before going ahead have a look into AVL Tree Basics.
(more…)by An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.
For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.
For every node in an AVL Tree, the difference between the height of its left subtree and right subtree should not be more than 1. Whenever insertion makes a node unbalanced, AVL rotations are used to balance the tree again.
In this article, let’s look into the LL imbalance case and the Right Rotation used to fix it.
In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n). Before going ahead have a look into AVL Tree Basics.
(more…)by An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.
For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.
In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n). Before going ahead have a look into Binary Search Tree basics, Binary Search Tree Insert, Binary Search Tree Delete, Binary Search Tree Search operations.
(more…)by An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.
For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.
In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n).
(more…)