AVL Tree Deletion Of Node Explained With Simple Example

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.

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AVL Tree Deletion Of Node Explained With Simple Example Read More

AVL Tree Insertion Of Node Explained With Simple Example

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…)
AVL Tree Insertion Of Node Explained With Simple Example Read More

AVL Tree Self Balancing Rotations – Right Left Rotation explained

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…)
AVL Tree Self Balancing Rotations – Right Left Rotation explained Read More

AVL Tree Self Balancing Rotations – Left Right Rotation explained

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…)
AVL Tree Self Balancing Rotations – Left Right Rotation explained Read More

AVL Tree Self Balancing Rotations – Left Rotation explained

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…)
AVL Tree Self Balancing Rotations – Left Rotation explained Read More

AVL Tree Self Balancing Rotations – Right Rotation explained

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…)
AVL Tree Self Balancing Rotations – Right Rotation explained Read More

Program To Check Whether A Binary Search Tree Is AVL Tree

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…)
Program To Check Whether A Binary Search Tree Is AVL Tree Read More

AVL Tree Explanation With Simple Examples

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…)
AVL Tree Explanation With Simple Examples Read More

Program To Check Whether A Binary Tree Is Binary search tree

A Binary Search Tree is a Binary tree in which all the nodes has following properties.

  • Left subtree of a node contains all the nodes having values lesser than the node.
  • Right subtree of a node contains all the nodes having values higher than the node.
  • Both the left and right subtree is also a Binary Search Tree.

As the name suggests, this data structure is mainly used for faster searching. In order to do that, restrictions are applied while inserting/deleting an element into the tree. As a result of these restrictions, worst case search time complexity remains at 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.

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Program To Check Whether A Binary Tree Is Binary search tree Read More