# How to handle duplicates in Binary Search Tree?

In a Binary Search Tree (BST), all keys in left subtree of a key must be smaller and all keys in right subtree must be greater. So a Binary Search Tree by definition has distinct keys.

How to allow duplicates where every insertion inserts one more key with a value and every deletion deletes one occurrence?

Simple Solution is to allow same keys on right side (we could also choose left side). For example consider insertion of keys 12, 10, 20, 9, 11, 10, 12, 12 in an empty Binary Search Tree

```          12
/     \
10      20
/  \     /
9   11   12
/      \
10       12
```

Better Solution is to augment every tree node to store count together with regular fields like key, left and right pointers.
Insertion of keys 12, 10, 20, 9, 11, 10, 12, 12 in an empty Binary Search Tree would create following.

```          12(3)
/        \
10(2)      20(1)
/    \
9(1)   11(1)

Count of a key is shown in bracket
```

This approach has following advantages over above simple approach.

1) Height of tree is small irrespective of number of duplicates. Note that most of the BST operations (search, insert and delete) have time complexity as O(h) where h is height of BST. So if we are able to keep the height small, we get advantage of less number of key comparisons.

2) Search, Insert and Delete become easier to do. We can use same insert, search and delete algorithms with small modifications (see below code).

3) This approach is suited for self-balancing BSTs (AVL Tree, Red-Black Tree, etc) also. These trees involve rotations, and a rotation may violate BST property of simple solution as a same key can be in either left side or right side after rotation.

Below is C implementation of normal Binary Search Tree with count with every key. This code basically is taken from code for insert and delete in BST. The changes made for handling duplicates are highlighted, rest of the code is same.

`// C program to implement basic operations (search, insert and delete)`
`// on a BST that handles duplicates by storing count with every node`
`#include<stdio.h>`
`#include<stdlib.h>`
`struct` `node`
`{`
`    ``int` `key;`
`    ``int` `count;`
`    ``struct` `node *left, *right;`
`};`
`// A utility function to create a new BST node`
`struct` `node *newNode(``int` `item)`
`{`
`    ``struct` `node *temp =  (``struct` `node *)``malloc``(``sizeof``(``struct` `node));`
`    ``temp->key = item;`
`    ``temp->left = temp->right = NULL;`
`    ``temp->count = 1;`
`    ``return` `temp;`
`}`
`// A utility function to do inorder traversal of BST`
`void` `inorder(``struct` `node *root)`
`{`
`    ``if` `(root != NULL)`
`    ``{`
`        ``inorder(root->left);`
`        ``printf``(``"%d(%d) "``, root->key, root->count);`
`        ``inorder(root->right);`
`    ``}`
`}`
`/* A utility function to insert a new node with given key in BST */`
`struct` `node* insert(``struct` `node* node, ``int` `key)`
`{`
`    ``/* If the tree is empty, return a new node */`
`    ``if` `(node == NULL) ``return` `newNode(key);`
`    ``// If key already exists in BST, icnrement count and return`
`    ``if` `(key == node->key)`
`    ``{`
`       ``(node->count)++;`
`        ``return` `node;`
`    ``}`
`    ``/* Otherwise, recur down the tree */`
`    ``if` `(key < node->key)`
`        ``node->left  = insert(node->left, key);`
`    ``else`
`        ``node->right = insert(node->right, key);`
`    ``/* return the (unchanged) node pointer */`
`    ``return` `node;`
`}`
`/* Given a non-empty binary search tree, return the node with`
`   ``minimum key value found in that tree. Note that the entire`
`   ``tree does not need to be searched. */`
`struct` `node * minValueNode(``struct` `node* node)`
`{`
`    ``struct` `node* current = node;`
`    ``/* loop down to find the leftmost leaf */`
`    ``while` `(current->left != NULL)`
`        ``current = current->left;`
`    ``return` `current;`
`}`
`/* Given a binary search tree and a key, this function`
`   ``deletes a given key and returns root of modified tree */`
`struct` `node* deleteNode(``struct` `node* root, ``int` `key)`
`{`
`    ``// base case`
`    ``if` `(root == NULL) ``return` `root;`
`    ``// If the key to be deleted is smaller than the`
`    ``// root's key, then it lies in left subtree`
`    ``if` `(key < root->key)`
`        ``root->left = deleteNode(root->left, key);`
`    ``// If the key to be deleted is greater than the root's key,`
`    ``// then it lies in right subtree`
`    ``else` `if` `(key > root->key)`
`        ``root->right = deleteNode(root->right, key);`
`    ``// if key is same as root's key`
`    ``else`
`    ``{`
`        ``// If key is present more than once, simply decrement`
`        ``// count and return`
`        ``if` `(root->count > 1)`
`        ``{`
`           ``(root->count)--;`
`           ``return` `root;`
`        ``}`
`        ``// ElSE, delete the node`
`        ``// node with only one child or no child`
`        ``if` `(root->left == NULL)`
`        ``{`
`            ``struct` `node *temp = root->right;`
`            ``free``(root);`
`            ``return` `temp;`
`        ``}`
`        ``else` `if` `(root->right == NULL)`
`        ``{`
`            ``struct` `node *temp = root->left;`
`            ``free``(root);`
`            ``return` `temp;`
`        ``}`
`        ``// node with two children: Get the inorder successor (smallest`
`        ``// in the right subtree)`
`        ``struct` `node* temp = minValueNode(root->right);`
`        ``// Copy the inorder successor's content to this node`
`        ``root->key = temp->key;`
`        ``// Delete the inorder successor`
`        ``root->right = deleteNode(root->right, temp->key);`
`    ``}`
`    ``return` `root;`
`}`
`// Driver Program to test above functions`
`int` `main()`
`{`
`    ``/* Let us create following BST`
`             ``12(3)`
`          ``/        \`
`       ``10(2)      20(1)`
`       ``/   \`
`    ``9(1)  11(1)   */`
`    ``struct` `node *root = NULL;`
`    ``root = insert(root, 12);`
`    ``root = insert(root, 10);`
`    ``root = insert(root, 20);`
`    ``root = insert(root, 9);`
`    ``root = insert(root, 11);`
`    ``root = insert(root, 10);`
`    ``root = insert(root, 12);`
`    ``root = insert(root, 12);`
`    ``printf``(``"Inorder traversal of the given tree \n"``);`
`    ``inorder(root);`
`    ``printf``(``"\nDelete 20\n"``);`
`    ``root = deleteNode(root, 20);`
`    ``printf``(``"Inorder traversal of the modified tree \n"``);`
`    ``inorder(root);`
`    ``printf``(``"\nDelete 12\n"``);`
`    ``root = deleteNode(root, 12);`
`    ``printf``(``"Inorder traversal of the modified tree \n"``);`
`    ``inorder(root);`
`    ``printf``(``"\nDelete 9\n"``);`
`    ``root = deleteNode(root, 9);`
`    ``printf``(``"Inorder traversal of the modified tree \n"``);`
`    ``inorder(root);`
`    ``return` `0;`
`}`

Output:

```Inorder traversal of the given tree
9(1) 10(2) 11(1) 12(3) 20(1)
Delete 20
Inorder traversal of the modified tree
9(1) 10(2) 11(1) 12(3)
Delete 12
Inorder traversal of the modified tree
9(1) 10(2) 11(1) 12(2)
Delete 9
Inorder traversal of the modified tree
10(2) 11(1) 12(2)```

We will soon be discussing AVL and Red Black Trees with duplicates allowed.

Disclaimer: This does not belong to TechCodeBit, its an article taken from the below
source and credits.
source and credits: http://www.geeksforgeeks.org
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