📖 Chapters
- 1. Introduction to DSA and Its Importance
- 2. Time and Space Complexity (Big O, Θ, Ω)
- 3. Recursion and Stack Memory
- 4. Mathematics for DSA (GCD, LCM, Modulo Arithmetic)
- 5. Arrays: Basics and Operations
- 6. Strings: Manipulation & Inbuilt Functions
- 7. Structures and Unions with Arrays
- 8. Linked Lists (Singly, Circular, Doubly)
- 9. Stack (Using Array & Linked List)
- 10. Queue (Simple, Circular, Deque)
- 11. Linear Search & Binary Search
- 12. Sorting Basics: Bubble, Selection, Insertion
- 13. Merge Sort
- 14. Quick Sort
- 15. Counting Sort, Radix Sort, Bucket Sort
- 16. Heap Sort
- 17. Binary Trees & Representations
- 18. Binary Tree Traversals (Pre, In, Post)
- 19. Binary Search Tree (BST)
- 20. AVL Trees (Self-balancing BST)
- 21. Trie (Prefix Tree)
- 22. Segment Tree (Range Queries)
- 23. Fenwick Tree / Binary Indexed Tree (BIT)
- 24. Heap & Priority Queues (Min-Heap, Max-Heap)
- 25. Hashing and Hash Tables
- 26. Disjoint Set Union (Union-Find, Path Compression)
- 27. Sparse Tables
- 28. Sliding Window Technique
- 29. Two Pointers Technique
- 30. Graph Representations (Adjacency Matrix & List)
- 31. BFS and DFS (Traversal & Search)
- 32. Topological Sort (Kahn’s & DFS)
- 33. Shortest Path Algorithms (Dijkstra, Bellman-Ford)
- 34. Minimum Spanning Tree (Kruskal, Prim)
- 35. Cycle Detection in Graphs
- 36. Bridges and Articulation Points
- 37. Greedy Algorithms (Activity Selection, Huffman Coding)
- 38. Backtracking (N-Queens, Sudoku Solver)
- 39. Dynamic Programming (Intro, Memoization, Tabulation)
- 40. Advanced DP (LIS, Knapsack, DP on Trees/Grids)
- 41. Bit Manipulation and XOR Tricks
- 42. Interview Problems from FAANG Companies
- 43. Competitive Coding Patterns
- 44. Building Mini Projects Using DSA (Menu-driven)
- 45. Final Quiz + Problem Sheet (100+ questions)
- 46. Next Steps: Competitive Programming or System Design?
Data Structures and Algorithms in C (DSA)
Category: IT Fundamentals & Programming
This course is designed to help learners master the core concepts of Data Structures and Algorithms (DSA) using the C programming language. Starting from the basics and advancing to complex topics like graphs, dynamic programming, and memory optimization, this course …
Recursion and Stack Memory
📘 Recursion and Stack Memory
Recursion is a powerful concept where a function calls itself to solve smaller subproblems. It’s commonly used in algorithms like factorial, Fibonacci, tree traversal, and divide-and-conquer strategies like merge sort.
🔁 What is Recursion?
Recursion is a technique where the solution to a problem depends on solutions to smaller instances of the same problem. It typically involves a base case and a recursive case.
✅ Example: Factorial of a Number
int factorial(int n) { if (n == 0 || n == 1) return 1; // base case return n * factorial(n - 1); // recursive call }
📌 Key Components of Recursion
- Base Case: When the function stops calling itself.
- Recursive Case: The part where the function calls itself.
- Stack Frame: Each function call is stored in memory (stack).
🧠 How Stack Memory Works
In C, each function call creates a new stack frame that stores local variables and return addresses. When a function finishes, the frame is removed (popped) from the stack.
🔍 Illustration of Stack for factorial(3)
factorial(3) └─> factorial(2) └─> factorial(1) └─> return 1 └─> return 2 * 1 = 2 └─> return 3 * 2 = 6
🚫 Common Mistakes in Recursion
- Missing or incorrect base case → leads to infinite recursion
- Modifying global variables inside recursive calls
- Not optimizing tail calls → causes stack overflow for large inputs
🧪 Real-Life Analogy
Imagine a stack of dishes: each recursive call places a new dish on top (push), and when it finishes, it removes it (pop). You must finish the top dish before touching the next one!
⚙️ Applications of Recursion
- Mathematical Problems: Factorial, Fibonacci
- Tree Traversal: Preorder, Inorder, Postorder
- Backtracking: N-Queens, Maze Solving
- Divide-and-Conquer: Merge Sort, Quick Sort
📚 UdaanPath Tip
Practice writing both recursive and iterative versions of functions. Understand the stack trace for each and use debugging tools to see how recursion unfolds.
✅ Summary
- Recursion solves problems by breaking them into smaller parts.
- Each call uses stack memory — watch out for large recursion depths!
- Base cases are critical to stop infinite recursion.
📤 Coming Next
Next, we will dive into Mathematics for DSA (GCD, LCM, Modulo Arithmetic) — the simplest and most fundamental data structure that every programmer must master.