AVL Tree in Data Structure with explanation

An AVL tree is a self-balancing binary search tree. It was named AVL on its inventor Adelson-Velsky and Landis. There are some scenarios in the Binary search tree where complexity can go O(n) in the worst-case search. so to get search in O(log n) in worst case AVL tree is designed.

Property of AVL tree is the difference of the height of its left and right subtree can be either -1, 0, and 1, this is also known as balance factor. If the balance factor is other than these three values then rebalancing required to maintain this property.

Balance Factor = height(left subtree)-height(right subtree)

Lets see the below example to understand this property

AVL Tree in data structure
AVL Tree Left Unbalanced
AVL Tree right unbalanced

To persist its property and deal with the unbalanced trees there is some rotation that we can apply on the AVL tree.

There are 4 types of rotation to maintain AVL tree property

  1. LR (left right) rotation
  2. RR (right right) rotation
  3. LR(Left Right) rotation
  4. RL(Right Left) rotation

1). Left Rotation

If a tree becomes unbalanced, means the balance factor of a node becomes 2. This has happened when a node is inserted into the right subtree of the right subtree. So to maintain the AVL tree property we do left rotation shown below in figure

Left Rotation in tree

In the above example, node 1 has become unbalanced because its balanced factor becomes 2. Here We perform the left rotation by making 2 the root and 1 as left node of 2.

2). Right Rotation

If a tree becomes unbalanced, means the balance factor of a node becomes 2. This has happened when a node is inserted into the left subtree of the Left subtree. So to maintain the AVL tree property we do right rotation shown below in figure

AVL tree right rotation
Right Rotation in AVL Tree

In the above example, node 3 has become unbalanced because its balanced factor is 2. Here We perform the right rotation by making 2 the root and 3 as the right node of 2.

3). Left-Right Rotation

In this case, a node has inserted into the right subtree of the left subtree. So node 3 becomes an unbalanced node because its balance factor is 2 (2-0). So to balance it we perform left-right rotation means first left rotation and then right rotation.

We first perform the left rotation on the left subtree of 3. This rotation will make 1 left subtree of 2.

Now after the left rotation tree will be still unbalanced because the Balance Factor of 3 becomes 2. it is because of the left subtree of the left-subtree.

We will now perform the right rotation to balance node  3. 

The tree is now balanced.

AVL Tree in data structure

4). Right-Left Rotation

In this case, a node has inserted into the left subtree of the right subtree. So node 3 becomes an unbalanced node because its balance factor is 2 (2-0). So to balance it we perform left-right rotation means first left rotation and then right rotation.

We first perform the right rotation on the right subtree of 1. This rotation will make 3 right subtree of 2.

Now after the right rotation tree will be still unbalanced because the Balance Factor of 1 becomes 2. it is because of the right subtree of the right-subtree.

AVL Tree right unbalanced

We will now perform the right rotation to balance node  1

The tree is now balanced.

AVL Tree in data structure

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