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
Polynomial Representation and Addition using Linked List
Mathematical polynomials jaise P(x) = 5x^4 - 2x^2 + 7x + 3 ko memory me efficiently store aur manipulate karne ke liye linked lists ideal data structure hain. Agar hum array use karein aur polynomial me powers high hon (jaise 10x^100 + 4), toh size 101 ka array waste hoga jisme 99 entries zeroes hongi.
Node Structure for Polynomial Term
struct PolyNode {
int coeff; // Coefficient (e.g. 5)
int exp; // Exponent (e.g. 4)
struct PolyNode* next; // Link to next term
};
Poly 1: 5x^2 + 4x + 2 [ 5 | 2 | Next ] ---> [ 4 | 1 | Next ] ---> [ 2 | 0 | NULL ] Poly 2: 3x^2 + 6 [ 3 | 2 | Next ] ---> [ 6 | 0 | NULL ] Result (Poly 1 + Poly 2): 8x^2 + 4x + 8 [ 8 | 2 | Next ] ---> [ 4 | 1 | Next ] ---> [ 8 | 0 | NULL ]
Polynomial Addition Algorithm
Dono polynomials ko head se compare karte hue merge sort ki tarah traverse karte hain:
- Agar
p1->exp == p2->exp: Coefficients add kareinsum = p1->coeff + p2->coeff, aur naya term result list me daalein. Dono pointers aage badhayein. - Agar
p1->exp > p2->exp:p1ka term result me daalein aurp1 = p1->nextkarein. - Agar
p2->exp > p1->exp:p2ka term result me daalein aurp2 = p2->nextkarein.
Time Complexity: O(m + n) jahan m aur n dono polynomials me number of terms hain.
Agli post me hum start karenge DSA Part-4: Stacks, Queues & Recursion, jisme pehla topic hoga Stack Data Structure: Array Implementation.