Data Structures & Algorithms
DSA Part-1
- Introduction to Data Structures
- Asymptotic Notations: Big-O, Omega, and Theta Notations
- Time Complexity and Space Complexity Analysis of Algorithms
- 1D Arrays: Memory Representation and Address Calculation
- 2D Arrays: Row-Major and Column-Major Order Formulas and Numericals
- Array Operations: Traversal, Insertion, and Deletion with Algorithms
- Sparse Matrix: Triplet Representation and Linked Representation
- String Operations, Memory Storage, and Pattern Matching Basics
- Linear Search Algorithm and Complexity Analysis
- Binary Search Algorithm (Iterative and Recursive)
- Bubble Sort Algorithm and Optimization
- Selection Sort Algorithm and Step-by-Step Trace
- Insertion Sort Algorithm and In-Place Analysis
- Merge Sort Algorithm (Divide and Conquer Approach)
- Quick Sort Algorithm and Partitioning Methods
- Counting Sort Algorithm (Non-Comparison Sorting)
- Radix Sort Algorithm and Bucket Distribution
DSA Part-2
- Singly Linked List: Concept and Memory Allocation
- Singly Linked List: Insertion Operations
- Singly Linked List: Deletion Operations
- Singly Linked List: Reversal and Search Operations
- Doubly Linked List: Node Structure and Traversal
- Doubly Linked List: Insertion and Deletion Operations
- Circular Singly Linked List: Concept and Operations
- Circular Doubly Linked List: Concept and Operations
- Header Linked List: Grounded and Circular Header Lists
- Polynomial Representation and Addition using Linked List
DSA Part-3
- Stack Data Structure: Array Implementation
- Stack Implementation using Linked List
- Infix, Prefix, and Postfix Notations
- Infix to Postfix Conversion using Stack
- Infix to Prefix Conversion using Stack
- Evaluation of Postfix Expression using Stack
- Recursion and System Stack (Tower of Hanoi)
- Linear Queue: Array Implementation and Operations
- Drawbacks of Linear Queue and Memory Wastage
- Circular Queue: Array Implementation and Condition Checks
- Queue Implementation using Linked List
- Double-Ended Queue (Deque): Input and Output-Restricted
- Priority Queue: Concept, Array and Heap Representation
DSA Part-4
- Tree Data Structure: Terminology and Basic Concepts
- Binary Trees: Types and Properties
- Binary Tree Traversals: Inorder, Preorder, and Postorder
- Level Order Traversal of Binary Tree
- Binary Search Tree (BST): Concept and Search Operation
- Binary Search Tree (BST): Insertion and Deletion Operations
- AVL Tree: Concept and Balance Factor
- AVL Tree Rotations: LL, RR, LR, and RL Rotations
- Binary Heap: Min-Heap and Max-Heap Properties
- Heap Operations: Heapify, Insertion, and Deletion
- B-Tree: Properties, Structure, and Insertion
- B+ Tree: Structure and Comparison with B-Tree
DSA Part-5
- Graph Data Structure: Terminology and Types
- Graph Representation: Adjacency Matrix and Adjacency List
- Breadth First Search (BFS) Algorithm for Graphs
- Depth First Search (DFS) Algorithm for Graphs
- Hashing: Hash Tables and Hash Functions
- Collision Resolution: Open Addressing Techniques
- Collision Resolution: Separate Chaining Method
Level Order Traversal of Binary Tree
Level Order Traversal ek Breadth-First Search (BFS) algorithmic traversal hai jisme tree ke nodes ko level-by-level (top to bottom) aur har level ke andar left to right visit kiya jata hai.
Algorithm using FIFO Queue
Depth-first traversals stack ya recursion se hote hain, lekin Level Order Traversal ke liye ek FIFO Queue data structure use kiya jata hai:
- Ek empty queue create karein.
- Root node ko queue me ENQUEUE karein.
- Jab tak queue empty na ho, repeat karein:
- Front node ko DEQUEUE karein aur print karein:
curr = dequeue() - Agar
curr->leftexist karta hai, toh use queue me ENQUEUE karein. - Agar
curr->rightexist karta hai, toh use queue me ENQUEUE karein.
- Front node ko DEQUEUE karein aur print karein:
Tree:
Level 0: [ 10 ]
/ \
Level 1: [ 20 ] [ 30 ]
/ \
Level 2: [ 40 ] [ 50 ]
Queue Execution Trace:
1. Enqueue 10 Queue: [ 10 ]
2. Dequeue 10, Enqueue 20, 30 Queue: [ 20, 30 ] Output: 10
3. Dequeue 20, Enqueue 40, 50 Queue: [ 30, 40, 50 ] Output: 10, 20
4. Dequeue 30 Queue: [ 40, 50 ] Output: 10, 20, 30
5. Dequeue 40 Queue: [ 50 ] Output: 10, 20, 30, 40
6. Dequeue 50 Queue: [ ] Output: 10, 20, 30, 40, 50
Complexity: Time Complexity O(n) (har node 1 bar queue me jata hai aur 1 bar nikalta hai). Space Complexity O(w) jahan w maximum width of tree hai (at most n/2 nodes in queue).
Agli post me hum cover karenge Binary Search Tree (BST): Concept and Search Operation.