A Tree is a widely used data structure that simulates a hierarchical tree structure, with a root value and subtrees of children represented as a set of linked nodes.

• Binary Tree
  A tree data structure in which each node has at most two children referred to as the left child and the right child.

• Binary Search Tree (BST)
  A binary tree in which all the left descendants of a node are smaller than the node, and all the right descendants are larger.

• AVL Tree
  A self-balancing binary search tree where the difference between heights of left and right subtrees cannot be more than one for all nodes.

1. Creation

   • Inserting nodes into the tree (starting from the root).
   • Defining rules for left and right children based on the type of tree (binary, BST, AVL).

2. Traversal

   • Inorder: Left, Root, Right
   • Preorder: Root, Left, Right
   • Postorder: Left, Right, Root
   • Level Order Traversal

3. Search

   • Searching for a node in the tree using Binary Search (in the case of BST).

4. Insertion

   • Adding new nodes to the tree, maintaining the properties of the specific tree (BST, AVL, etc.).

5. Deletion

   • Removing nodes from the tree, ensuring that the tree's properties remain intact after deletion.

6. Rotation (for AVL Tree)

   • Single Rotation (Left or Right)
   • Double Rotation (Left-Right or Right-Left)

7. Balancing (for AVL Tree)

   • Re-balancing the tree after insertions or deletions to maintain height balance.

You can find implementations of these tree structures in the respective directories:

• Binary Tree
• Binary Search Tree (BST)
• AVL Tree

Explore the source code to understand how each operation is implemented.