# 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?

A 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
```

A 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).

br>

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 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++

// C++ program to implement basic operations
// (search, insert and delete) on a BST that
// handles duplicates by storing count with
// every node
#include
using namespace std;

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);
cout << 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,
// increment 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 Code
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);

cout << "Inorder traversal of the given tree " << endl; inorder(root); cout << " Delete 20 "; root = deleteNode(root, 20); cout << "Inorder traversal of the modified tree "; inorder(root); cout << " Delete 12 " ; root = deleteNode(root, 12); cout << "Inorder traversal of the modified tree "; inorder(root); cout << " Delete 9 "; root = deleteNode(root, 9); cout << "Inorder traversal of the modified tree "; inorder(root); return 0; } // This code is contributed by Akanksha Rai [tabby title="C"]

 `// C program to implement basic operations (search, insert and delete) ` `// on a BST that handles duplicates by storing count with every node ` `#include ` `#include ` ` `  `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 "````); ` `    ``inorder(root); ` ` `  `    ``printf``(````" Delete 20 "````); ` `    ``root = deleteNode(root, 20); ` `    ``printf``(````"Inorder traversal of the modified tree "````); ` `    ``inorder(root); ` ` `  `    ``printf``(````" Delete 12 "````); ` `    ``root = deleteNode(root, 12); ` `    ``printf``(````"Inorder traversal of the modified tree "````); ` `    ``inorder(root); ` ` `  `    ``printf``(````" Delete 9 "````); ` `    ``root = deleteNode(root, 9); ` `    ``printf``(````"Inorder traversal of the modified tree "````); ` `    ``inorder(root); ` ` `  `    ``return` `0; ` `}`

## Python3

 `# Python3 program to implement basic operations  ` `# (search, insert and delete) on a BST that handles  ` `# duplicates by storing count with every node  ` ` `  `# A utility function to create a new BST node  ` `class` `newNode:  ` ` `  `    ``# Constructor to create a new node  ` `    ``def` `__init__(``self``, data):  ` `        ``self``.key ``=` `data ` `        ``self``.count ``=` `1` `        ``self``.left ``=` `None` `        ``self``.right ``=` `None` ` `  `# A utility function to do inorder  ` `# traversal of BST  ` `def` `inorder(root): ` `    ``if` `root !``=` `None``: ` `        ``inorder(root.left) ` `        ``print``(root.key,``"("``, root.count,``")"``,  ` `                                 ``end ``=` `" "``)  ` `        ``inorder(root.right) ` ` `  `# A utility function to insert a new node  ` `# with given key in BST  ` `def` `insert(node, key): ` `     `  `    ``# If the tree is empty, return a new node  ` `    ``if` `node ``=``=` `None``: ` `        ``k ``=` `newNode(key) ` `        ``return` `k ` ` `  `    ``# If key already exists in BST, increment ` `    ``# count and return  ` `    ``if` `key ``=``=` `node.key: ` `        ``(node.count) ``+``=` `1` `        ``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.  ` `def` `minValueNode(node): ` `    ``current ``=` `node  ` ` `  `    ``# loop down to find the leftmost leaf  ` `    ``while` `current.left !``=` `None``:  ` `        ``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  ` `def` `deleteNode(root, key): ` `     `  `    ``# base case  ` `    ``if` `root ``=``=` `None``: ` `        ``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  ` `    ``elif` `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 ``-``=` `1` `            ``return` `root ` `         `  `        ``# ElSE, delete the node node with ` `        ``# only one child or no child  ` `        ``if` `root.left ``=``=` `None``: ` `            ``temp ``=` `root.right ` `            ``return` `temp ` `        ``elif` `root.right ``=``=` `None``: ` `            ``temp ``=` `root.left ` `            ``return` `temp ` ` `  `        ``# node with two children: Get the inorder  ` `        ``# successor (smallest in the right subtree)  ` `        ``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 Code ` `if` `__name__ ``=``=` `'__main__'``: ` `     `  `    ``# Let us create following BST  ` `    ``# 12(3)  ` `    ``# /   ` `    ``# 10(2) 20(1)  ` `    ``# /   ` `    ``# 9(1) 11(1)  ` `    ``root ``=` `None` `    ``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``) ` ` `  `    ``print``(``"Inorder traversal of the given tree"``)  ` `    ``inorder(root)  ` `    ``print``() ` `     `  `    ``print``(``"Delete 20"``)  ` `    ``root ``=` `deleteNode(root, ``20``)  ` `    ``print``(``"Inorder traversal of the modified tree"``)  ` `    ``inorder(root)  ` `    ``print``() ` ` `  `    ``print``(``"Delete 12"``) ` `    ``root ``=` `deleteNode(root, ``12``)  ` `    ``print``(``"Inorder traversal of the modified tree"``)  ` `    ``inorder(root)  ` `    ``print``() ` ` `  `    ``print``(``"Delete 9"``) ` `    ``root ``=` `deleteNode(root, ``9``)  ` `    ``print``(``"Inorder traversal of the modified tree"``)  ` `    ``inorder(root) ` ` `  `# This code is contributed by PranchalK `

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.