Convert Binary Tree to Doubly Linked List using inorder traversal
Last Updated :
23 Jul, 2025
Given a Binary Tree (BT), the task is to convert it to a Doubly Linked List (DLL) in place. The left and right pointers in nodes will be used as previous and next pointers respectively in converted DLL. The order of nodes in DLL must be the same as the order of the given Binary Tree. The first node of Inorder traversal (leftmost node in BT) must be the head node of the DLL.
Examples:
Input:
Output:
Explanation: The above binary tree is converted into doubly linked list where left pointer of the binary tree node act as the previous node and right pointer of the binary tree node act as the next node.
Input:
Output:
Explanation: The above binary tree is converted into doubly linked list where left pointer of the binary tree node act as the previous node and right pointer of the binary tree node act as the next node.
[Naive Approach] Using Recursion - O(n) Time and O(h) Space
The idea is to recursively traverse the binary tree using inorder traversal. At each node, if left subtree exists, find theinorder predecessor, then process the left subtree and link the current node and predecessor. If right subtree exists, then find theinorder successor, process the right subtree and then link the current node and successor node.
Below is the implementation of the above approach:
C++
// C++ program for in-place
// conversion of Binary Tree to DLL
#include <bits/stdc++.h>
using namespace std;
class Node {
public:
int data;
Node* left;
Node* right;
Node (int x) {
data = x;
left = nullptr;
right = nullptr;
}
};
void inorder(Node* root) {
// if left subtree exists
if (root->left){
// find the inorder predecessor of root node
Node* pred = root->left;
while (pred->right){
pred = pred->right;
}
// process the left subtree
inorder(root->left);
// link the predecessor and root node
pred->right = root;
root->left = pred;
}
// if right subtree exists
if (root->right) {
// find the inorder successor of root node
Node* succ = root->right;
while (succ->left) {
succ = succ->left;
}
// process the right subtree
inorder(root->right);
// link the successor and root node
root->right = succ;
succ->left = root;
}
}
Node* bToDLL(Node* root){
// return if root is null
if (root == nullptr) return root;
// find the head of dll
Node* head = root;
while (head->left != nullptr)
head = head->left;
// recursively convert the tree into dll
inorder(root);
return head;
}
void printList(Node* head){
Node* curr = head;
while (curr != NULL) {
cout << curr->data << " ";
curr = curr->right;
}
cout<<endl;
}
int main() {
// Create a hard coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
Node* root = new Node(10);
root->left = new Node(12);
root->right = new Node(15);
root->left->left = new Node(25);
root->left->right = new Node(30);
root->right->left = new Node(36);
Node* head = bToDLL(root);
printList(head);
return 0;
}
C
// C program for in-place
// conversion of Binary Tree to DLL
#include <stdio.h>
#include <stdlib.h>
struct Node {
int data;
struct Node* left;
struct Node* right;
};
// Inorder traversal to link nodes
void inorder(struct Node* root) {
// if left subtree exists
if (root->left) {
// find the inorder predecessor of root node
struct Node* pred = root->left;
while (pred->right) {
pred = pred->right;
}
// process the left subtree
inorder(root->left);
// link the predecessor and root node
pred->right = root;
root->left = pred;
}
// if right subtree exists
if (root->right) {
// find the inorder successor of root node
struct Node* succ = root->right;
while (succ->left) {
succ = succ->left;
}
// process the right subtree
inorder(root->right);
// link the successor and root node
root->right = succ;
succ->left = root;
}
}
// Function to convert binary tree to doubly linked list
struct Node* bToDLL(struct Node* root) {
// return if root is null
if (root == NULL) return root;
// find the head of dll
struct Node* head = root;
while (head->left != NULL)
head = head->left;
// recursively convert the tree into dll
inorder(root);
return head;
}
void printList(struct Node* head) {
struct Node* curr = head;
while (curr != NULL) {
printf("%d ", curr->data);
curr = curr->right;
}
printf("\n");
}
struct Node* createNode(int x) {
struct Node* node =
(struct Node*)malloc(sizeof(struct Node));
node->data = x;
node->left = NULL;
node->right = NULL;
return node;
}
int main() {
// Create a hard coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
struct Node* root = createNode(10);
root->left = createNode(12);
root->right = createNode(15);
root->left->left = createNode(25);
root->left->right = createNode(30);
root->right->left = createNode(36);
struct Node* head = bToDLL(root);
printList(head);
return 0;
}
Java
// Java program for in-place
// conversion of Binary Tree to DLL
class Node {
int data;
Node left, right;
Node(int x) {
data = x;
left = null;
right = null;
}
}
class GfG {
// Inorder traversal to link nodes
static void inorder(Node root) {
// if left subtree exists
if (root.left != null) {
// find the inorder predecessor of root node
Node pred = root.left;
while (pred.right != null) {
pred = pred.right;
}
// process the left subtree
inorder(root.left);
// link the predecessor and root node
pred.right = root;
root.left = pred;
}
// if right subtree exists
if (root.right != null) {
// find the inorder successor of root node
Node succ = root.right;
while (succ.left != null) {
succ = succ.left;
}
// process the right subtree
inorder(root.right);
// link the successor and root node
root.right = succ;
succ.left = root;
}
}
// Function to convert binary tree to doubly linked list
static Node bToDLL(Node root) {
// return if root is null
if (root == null) return root;
// find the head of dll
Node head = root;
while (head.left != null)
head = head.left;
// recursively convert the tree into dll
inorder(root);
return head;
}
static void printList(Node head) {
Node curr = head;
while (curr != null) {
System.out.print(curr.data + " ");
curr = curr.right;
}
System.out.println();
}
public static void main(String[] args) {
// Create a hard coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
Node root = new Node(10);
root.left = new Node(12);
root.right = new Node(15);
root.left.left = new Node(25);
root.left.right = new Node(30);
root.right.left = new Node(36);
Node head = bToDLL(root);
printList(head);
}
}
Python
# Python program for in-place
# conversion of Binary Tree to DLL
class Node:
def __init__(self, new_value):
self.data = new_value
self.left = None
self.right = None
# Inorder traversal to link nodes
def inorder(root):
# if left subtree exists
if root.left:
# find the inorder predecessor of root node
pred = root.left
while pred.right:
pred = pred.right
# process the left subtree
inorder(root.left)
# link the predecessor and root node
pred.right = root
root.left = pred
# if right subtree exists
if root.right:
# find the inorder successor of root node
succ = root.right
while succ.left:
succ = succ.left
# process the right subtree
inorder(root.right)
# link the successor and root node
root.right = succ
succ.left = root
# Function to convert binary tree to doubly linked list
def bToDLL(root):
# return if root is null
if root is None:
return root
# find the head of dll
head = root
while head.left:
head = head.left
# recursively convert the tree into dll
inorder(root)
return head
def print_list(head):
curr = head
while curr:
print(curr.data, end=" ")
curr = curr.right
print()
if __name__ == "__main__":
# Create a hard coded binary tree
# 10
# / \
# 12 15
# / \ /
# 25 30 36
root = Node(10)
root.left = Node(12)
root.right = Node(15)
root.left.left = Node(25)
root.left.right = Node(30)
root.right.left = Node(36)
head = bToDLL(root)
print_list(head)
C#
// C# program for in-place
// conversion of Binary Tree to DLL
using System;
class Node {
public int data;
public Node left, right;
public Node(int x) {
data = x;
left = right = null;
}
}
class GfG {
// Inorder traversal to link nodes
static void Inorder(Node root) {
// if left subtree exists
if (root.left != null) {
// find the inorder predecessor of root node
Node pred = root.left;
while (pred.right != null) {
pred = pred.right;
}
// process the left subtree
Inorder(root.left);
// link the predecessor and root node
pred.right = root;
root.left = pred;
}
// if right subtree exists
if (root.right != null) {
// find the inorder successor of root node
Node succ = root.right;
while (succ.left != null) {
succ = succ.left;
}
// process the right subtree
Inorder(root.right);
// link the successor and root node
root.right = succ;
succ.left = root;
}
}
// Function to convert binary tree to doubly linked list
static Node BToDLL(Node root) {
// return if root is null
if (root == null) return root;
// find the head of dll
Node head = root;
while (head.left != null)
head = head.left;
// recursively convert the tree into dll
Inorder(root);
return head;
}
static void PrintList(Node head) {
Node curr = head;
while (curr != null) {
Console.Write(curr.data + " ");
curr = curr.right;
}
Console.WriteLine();
}
static void Main(string[] args) {
// Create a hard coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
Node root = new Node(10);
root.left = new Node(12);
root.right = new Node(15);
root.left.left = new Node(25);
root.left.right = new Node(30);
root.right.left = new Node(36);
Node head = BToDLL(root);
PrintList(head);
}
}
JavaScript
// JavaScript program for in-place
// conversion of Binary Tree to DLL
class Node {
constructor(new_value) {
this.data = new_value;
this.left = null;
this.right = null;
}
}
// Inorder traversal to link nodes
function inorder(root) {
// if left subtree exists
if (root.left) {
// find the inorder predecessor of root node
let pred = root.left;
while (pred.right) {
pred = pred.right;
}
// process the left subtree
inorder(root.left);
// link the predecessor and root node
pred.right = root;
root.left = pred;
}
// if right subtree exists
if (root.right) {
// find the inorder successor of root node
let succ = root.right;
while (succ.left) {
succ = succ.left;
}
// process the right subtree
inorder(root.right);
// link the successor and root node
root.right = succ;
succ.left = root;
}
}
// Function to convert binary tree to doubly linked list
function bToDLL(root) {
// return if root is null
if (root === null) return root;
// find the head of dll
let head = root;
while (head.left !== null)
head = head.left;
// recursively convert the tree into dll
inorder(root);
return head;
}
function printList(head) {
let curr = head;
while (curr !== null) {
console.log(curr.data);
curr = curr.right;
}
}
// Create a hard coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
let root = new Node(10);
root.left = new Node(12);
root.right = new Node(15);
root.left.left = new Node(25);
root.left.right = new Node(30);
root.right.left = new Node(36);
let head = bToDLL(root);
printList(head);
Time Complexity: O(n), where n is the number of node in the tree.
Auxiliary Space: O(h), where h is the height of tree.
[Expected Approach] Using Morris Traversal Algorithm - O(n) Time and O(1) Space
The idea is to use Morris traversal algorithmto traverse the binary tree, while maintaining proper linkages between the nodes.
Step by step implementation:
- Initialize pointers head and tail. head will point to the head node of the resultant dll and tail will point to the last node in dll.
- Initialize another pointer curr, which will initially point to root node. Start traversing until curr is not NULL
- If curr.left is null, then add the current node to the list (If head is empty, then make this node as head node) and move curr to curr.right.
- If curr.left is not null, then find the inorder predecessor of the current node. Let that node be 'pred'. There are two possibilites:
- If pred.right is equal to null, then create a link between pred and curr, by setting pred.right = curr and set curr = curr.left.
- If pred->right is equal to curr, then this means we have traversed the left subtree and now we can add the curr node to the list. Then set curr = curr->right.
- Return the head.
C++
// C++ program for in-place
// conversion of Binary Tree to DLL
#include <bits/stdc++.h>
using namespace std;
class Node {
public:
int data;
Node *left;
Node *right;
Node(int x) {
data = x;
left = nullptr;
right = nullptr;
}
};
// Function to perform Morris Traversal and convert
// binary tree to doubly linked list (DLL)
Node* morrisTraversal(Node* root) {
// return if root is null
if (root == nullptr) return root;
// head and tail node for the dll
Node* head = nullptr, *tail = nullptr;
Node* curr = root;
while (curr != nullptr) {
// if left tree does not exists,
// then add the curr node to the
// dll and set curr = curr->right
if (curr->left == nullptr) {
if (head == nullptr) {
head = tail = curr;
}
else {
tail->right = curr;
curr->left = tail;
tail = curr;
}
curr = curr->right;
}
else {
Node* pred = curr->left;
// find the inorder predecessor
while (pred->right != nullptr && pred->right != curr) {
pred = pred->right;
}
// create a linkage between pred and
// curr
if (pred->right == nullptr) {
pred->right = curr;
curr = curr->left;
}
// if pred->right = curr, it means
// we have processed the left subtree,
// and we can add curr node to list
else {
tail->right = curr;
curr->left = tail;
tail = curr;
curr = curr->right;
}
}
}
return head;
}
void printList(Node* head) {
Node* curr = head;
while (curr != nullptr) {
cout << curr->data << " ";
curr = curr->right;
}
cout << endl;
}
int main() {
// Create a hard-coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
Node* root = new Node(10);
root->left = new Node(12);
root->right = new Node(15);
root->left->left = new Node(25);
root->left->right = new Node(30);
root->right->left = new Node(36);
Node* head = morrisTraversal(root);
printList(head);
return 0;
}
C
// C program for in-place
// conversion of Binary Tree to DLL
#include <stdio.h>
#include <stdlib.h>
struct Node {
int data;
struct Node* left;
struct Node* right;
};
struct Node* morrisTraversal(struct Node* root) {
// return if root is null
if (root == NULL) return root;
// head and tail node for the dll
struct Node* head = NULL, *tail = NULL;
struct Node* curr = root;
while (curr != NULL) {
// if left tree does not exists,
// then add the curr node to the
// dll and set curr = curr->right
if (curr->left == NULL) {
if (head == NULL) {
head = tail = curr;
}
else {
tail->right = curr;
curr->left = tail;
tail = curr;
}
curr = curr->right;
}
else {
struct Node* pred = curr->left;
// find the inorder predecessor
while (pred->right != NULL
&& pred->right != curr) {
pred = pred->right;
}
// create a linkage between pred and
// curr
if (pred->right == NULL) {
pred->right = curr;
curr = curr->left;
}
// if pred->right = curr, it means
// we have processed the left subtree,
// and we can add curr node to list
else {
tail->right = curr;
curr->left = tail;
tail = curr;
curr = curr->right;
}
}
}
return head;
}
void printList(struct Node* head) {
struct Node* curr = head;
while (curr != NULL) {
printf("%d ", curr->data);
curr = curr->right;
}
printf("\n");
}
struct Node* createNode(int new_value) {
struct Node* node =
(struct Node*)malloc(sizeof(struct Node));
node->data = new_value;
node->left = node->right = NULL;
return node;
}
int main() {
// Create a hard coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
struct Node* root = createNode(10);
root->left = createNode(12);
root->right = createNode(15);
root->left->left = createNode(25);
root->left->right = createNode(30);
root->right->left = createNode(36);
struct Node* head = morrisTraversal(root);
printList(head);
return 0;
}
Java
// Java program for in-place
// conversion of Binary Tree to DLL
class Node {
int data;
Node left, right;
Node(int x) {
data = x;
left = null;
right = null;
}
}
class GfG {
static Node morrisTraversal(Node root) {
// return if root is null
if (root == null) return root;
// head and tail node for the dll
Node head = null, tail = null;
Node curr = root;
while (curr != null) {
// if left tree does not exists,
// then add the curr node to the
// dll and set curr = curr.right
if (curr.left == null) {
if (head == null) {
head = tail = curr;
}
else {
tail.right = curr;
curr.left = tail;
tail = curr;
}
curr = curr.right;
} else {
Node pred = curr.left;
// find the inorder predecessor
while (pred.right != null
&& pred.right != curr) {
pred = pred.right;
}
// create a linkage between pred and
// curr
if (pred.right == null) {
pred.right = curr;
curr = curr.left;
}
// if pred.right = curr, it means
// we have processed the left subtree,
// and we can add curr node to list
else {
tail.right = curr;
curr.left = tail;
tail = curr;
curr = curr.right;
}
}
}
return head;
}
static void printList(Node head) {
Node curr = head;
while (curr != null) {
System.out.print(curr.data + " ");
curr = curr.right;
}
System.out.println();
}
public static void main(String[] args) {
// Create a hard coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
Node root = new Node(10);
root.left = new Node(12);
root.right = new Node(15);
root.left.left = new Node(25);
root.left.right = new Node(30);
root.right.left = new Node(36);
Node head = morrisTraversal(root);
printList(head);
}
}
Python
# Python program for in-place
# conversion of Binary Tree to DLL
class Node:
def __init__(self, new_value):
self.data = new_value
self.left = None
self.right = None
def morris_traversal(root):
# return if root is None
if root is None:
return root
# head and tail node for the dll
head = None
tail = None
curr = root
while curr is not None:
# if left tree does not exist,
# then add the curr node to the
# dll and set curr = curr.right
if curr.left is None:
if head is None:
head = tail = curr
else:
tail.right = curr
curr.left = tail
tail = curr
curr = curr.right
else:
pred = curr.left
# find the inorder predecessor
while pred.right is not None \
and pred.right != curr:
pred = pred.right
# create a linkage between pred and curr
if pred.right is None:
pred.right = curr
curr = curr.left
# if pred.right = curr, it means
# we have processed the left subtree,
# and we can add curr node to list
else:
tail.right = curr
curr.left = tail
tail = curr
curr = curr.right
return head
def print_list(head):
curr = head
while curr is not None:
print(curr.data, end=" ")
curr = curr.right
print()
if __name__ == "__main__":
# Create a hard coded binary tree
# 10
# / \
# 12 15
# / \ /
# 25 30 36
root = Node(10)
root.left = Node(12)
root.right = Node(15)
root.left.left = Node(25)
root.left.right = Node(30)
root.right.left = Node(36)
head = morris_traversal(root)
print_list(head)
C#
// C# program for in-place
// conversion of Binary Tree to DLL
using System;
class Node {
public int data;
public Node left, right;
public Node(int x) {
data = x;
left = null;
right = null;
}
}
class GfG {
static Node MorrisTraversal(Node root) {
// return if root is null
if (root == null) return root;
// head and tail node for the dll
Node head = null, tail = null;
Node curr = root;
while (curr != null) {
// if left tree does not exists,
// then add the curr node to the
// dll and set curr = curr.right
if (curr.left == null) {
if (head == null) {
head = tail = curr;
} else {
tail.right = curr;
curr.left = tail;
tail = curr;
}
curr = curr.right;
} else {
Node pred = curr.left;
// find the inorder predecessor
while (pred.right != null
&& pred.right != curr) {
pred = pred.right;
}
// create a linkage between pred and
// curr
if (pred.right == null) {
pred.right = curr;
curr = curr.left;
}
// if pred.right = curr, it means
// we have processed the left subtree,
// and we can add curr node to list
else {
tail.right = curr;
curr.left = tail;
tail = curr;
curr = curr.right;
}
}
}
return head;
}
static void PrintList(Node head) {
Node curr = head;
while (curr != null) {
Console.Write(curr.data + " ");
curr = curr.right;
}
Console.WriteLine();
}
static void Main(string[] args) {
// Create a hard coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
Node root = new Node(10);
root.left = new Node(12);
root.right = new Node(15);
root.left.left = new Node(25);
root.left.right = new Node(30);
root.right.left = new Node(36);
Node head = MorrisTraversal(root);
PrintList(head);
}
}
JavaScript
// JavaScript program for in-place
// conversion of Binary Tree to DLL
class Node {
constructor(new_value) {
this.data = new_value;
this.left = this.right = null;
}
}
function morrisTraversal(root) {
// return if root is null
if (root === null) return root;
// head and tail node for the dll
let head = null, tail = null;
let curr = root;
while (curr !== null) {
// if left tree does not exists,
// then add the curr node to the
// dll and set curr = curr.right
if (curr.left === null) {
if (head === null) {
head = tail = curr;
} else {
tail.right = curr;
curr.left = tail;
tail = curr;
}
curr = curr.right;
} else {
let pred = curr.left;
// find the inorder predecessor
while (pred.right !== null && pred.right !== curr) {
pred = pred.right;
}
// create a linkage between pred and curr
if (pred.right === null) {
pred.right = curr;
curr = curr.left;
}
// if pred.right = curr, it means
// we have processed the left subtree,
// and we can add curr node to list
else {
tail.right = curr;
curr.left = tail;
tail = curr;
curr = curr.right;
}
}
}
return head;
}
function printList(head) {
let curr = head;
while (curr !== null) {
console.log(curr.data);
curr = curr.right;
}
}
// Create a hard coded binary tree
// 10
// / \
// 12 15
// / \ /
// 25 30 36
let root = new Node(10);
root.left = new Node(12);
root.right = new Node(15);
root.left.left = new Node(25);
root.left.right = new Node(30);
root.right.left = new Node(36);
let head = morrisTraversal(root);
printList(head);
Time Complexity: O(n), where n is the number of nodes in tree.
Auxiliary Space: O(1)
Convert a given Binary Tree to a Doubly Linked List
Similar Reads
Basics & Prerequisites
Data Structures
Array Data StructureIn this article, we introduce array, implementation in different popular languages, its basic operations and commonly seen problems / interview questions. An array stores items (in case of C/C++ and Java Primitive Arrays) or their references (in case of Python, JS, Java Non-Primitive) at contiguous
3 min read
String in Data StructureA string is a sequence of characters. The following facts make string an interesting data structure.Small set of elements. Unlike normal array, strings typically have smaller set of items. For example, lowercase English alphabet has only 26 characters. ASCII has only 256 characters.Strings are immut
2 min read
Hashing in Data StructureHashing is a technique used in data structures that efficiently stores and retrieves data in a way that allows for quick access. Hashing involves mapping data to a specific index in a hash table (an array of items) using a hash function. It enables fast retrieval of information based on its key. The
2 min read
Linked List Data StructureA linked list is a fundamental data structure in computer science. It mainly allows efficient insertion and deletion operations compared to arrays. Like arrays, it is also used to implement other data structures like stack, queue and deque. Hereâs the comparison of Linked List vs Arrays Linked List:
2 min read
Stack Data StructureA Stack is a linear data structure that follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). LIFO implies that the element that is inserted last, comes out first and FILO implies that the element that is inserted first
2 min read
Queue Data StructureA Queue Data Structure is a fundamental concept in computer science used for storing and managing data in a specific order. It follows the principle of "First in, First out" (FIFO), where the first element added to the queue is the first one to be removed. It is used as a buffer in computer systems
2 min read
Tree Data StructureTree Data Structure is a non-linear data structure in which a collection of elements known as nodes are connected to each other via edges such that there exists exactly one path between any two nodes. Types of TreeBinary Tree : Every node has at most two childrenTernary Tree : Every node has at most
4 min read
Graph Data StructureGraph Data Structure is a collection of nodes connected by edges. It's used to represent relationships between different entities. If you are looking for topic-wise list of problems on different topics like DFS, BFS, Topological Sort, Shortest Path, etc., please refer to Graph Algorithms. Basics of
3 min read
Trie Data StructureThe Trie data structure is a tree-like structure used for storing a dynamic set of strings. It allows for efficient retrieval and storage of keys, making it highly effective in handling large datasets. Trie supports operations such as insertion, search, deletion of keys, and prefix searches. In this
15+ min read
Algorithms
Searching AlgorithmsSearching algorithms are essential tools in computer science used to locate specific items within a collection of data. In this tutorial, we are mainly going to focus upon searching in an array. When we search an item in an array, there are two most common algorithms used based on the type of input
2 min read
Sorting AlgorithmsA Sorting Algorithm is used to rearrange a given array or list of elements in an order. For example, a given array [10, 20, 5, 2] becomes [2, 5, 10, 20] after sorting in increasing order and becomes [20, 10, 5, 2] after sorting in decreasing order. There exist different sorting algorithms for differ
3 min read
Introduction to RecursionThe process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called a recursive function. A recursive algorithm takes one step toward solution and then recursively call itself to further move. The algorithm stops once we reach the solution
14 min read
Greedy AlgorithmsGreedy algorithms are a class of algorithms that make locally optimal choices at each step with the hope of finding a global optimum solution. At every step of the algorithm, we make a choice that looks the best at the moment. To make the choice, we sometimes sort the array so that we can always get
3 min read
Graph AlgorithmsGraph is a non-linear data structure like tree data structure. The limitation of tree is, it can only represent hierarchical data. For situations where nodes or vertices are randomly connected with each other other, we use Graph. Example situations where we use graph data structure are, a social net
3 min read
Dynamic Programming or DPDynamic Programming is an algorithmic technique with the following properties.It is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of
3 min read
Bitwise AlgorithmsBitwise algorithms in Data Structures and Algorithms (DSA) involve manipulating individual bits of binary representations of numbers to perform operations efficiently. These algorithms utilize bitwise operators like AND, OR, XOR, NOT, Left Shift, and Right Shift.BasicsIntroduction to Bitwise Algorit
4 min read
Advanced
Segment TreeSegment Tree is a data structure that allows efficient querying and updating of intervals or segments of an array. It is particularly useful for problems involving range queries, such as finding the sum, minimum, maximum, or any other operation over a specific range of elements in an array. The tree
3 min read
Pattern SearchingPattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data. Patten SearchingImportant Pattern Searching Algorithms:Naive String Matching : A Simple Algorithm that works i
2 min read
GeometryGeometry is a branch of mathematics that studies the properties, measurements, and relationships of points, lines, angles, surfaces, and solids. From basic lines and angles to complex structures, it helps us understand the world around us.Geometry for Students and BeginnersThis section covers key br
2 min read
Interview Preparation
Practice Problem