Paper 2: DATA STRUCTURE AND ALGORITHMS WITH ‘C’ from the MCA syllabus:
Unit-I: Basics of Data Structures and Algorithms
-
Structures, Unions, and File Input/Output:
- Structures: User-defined data type to group variables (e.g.,
struct
in C). - Unions: Similar to structures but share memory.
- File I/O: Functions like
fopen
,fclose
,fprintf
,fscanf
, etc.
- Structures: User-defined data type to group variables (e.g.,
-
Pointers and Dynamic Memory Allocation:
- Pointers: Variables that store memory addresses.
- Dynamic Memory Allocation: Functions like
malloc
,calloc
,realloc
, andfree
.
-
Algorithm Analysis and Complexity:
- Time Complexity: Measures how runtime grows with input size (e.g., O(1), O(n), O(n²)).
- Space Complexity: Memory usage by an algorithm.
-
Recursion:
- Function calls itself to solve smaller instances of the problem.
- Types: Linear Recursion (direct calls), Binary Recursion (multiple calls).
-
Searching Techniques:
- Linear Search: Sequentially checks each element (O(n)).
- Binary Search: Divides sorted array into halves (O(log n)).
Unit-II: Linked Lists
-
Introduction to Linked Lists:
- Single Linked List: Nodes connected linearly with a pointer to the next node.
- Circular Linked List: Last node points back to the first node.
- Double Linked List: Each node has pointers to both the next and previous nodes.
-
Operations on Linked Lists:
- Insertion: Adding elements to the list.
- Deletion: Removing elements from the list.
- Traversal: Accessing all nodes in sequence.
-
Advantages and Disadvantages:
- Advantages: Dynamic memory allocation, efficient insertions/deletions.
- Disadvantages: Overhead of pointers, sequential access only.
Unit-III: Stacks and Queues
-
Stacks:
- LIFO (Last-In-First-Out): Data added last is accessed first.
- Operations:
- Push: Add data.
- Pop: Remove data.
- Peek: View the top element.
- Applications:
- Reverse strings.
- Evaluate postfix expressions.
- Convert infix to postfix notation.
-
Queues:
- FIFO (First-In-First-Out): Data added first is accessed first.
- Types:
- Simple Queue: Regular insertion and deletion.
- Circular Queue: Wraps around to use unused space.
- Priority Queue: Elements prioritized during insertion.
- Applications:
- Round-robin scheduling.
- Handling requests in real-time systems.
-
Implementation:
- Using arrays or linked lists.
Unit-IV: Sorting Techniques
-
Basic Concepts:
- Sorting arranges data in ascending or descending order.
-
Sorting Algorithms:
- Insertion Sort: Builds sorted array one item at a time (O(n²)).
- Selection Sort: Repeatedly selects the smallest/largest item (O(n²)).
- Bubble Sort: Repeatedly swaps adjacent elements if out of order (O(n²)).
- Quick Sort: Divides array using a pivot, sorts partitions (O(n log n)).
- Merge Sort: Divides array into halves, merges sorted halves (O(n log n)).
- Heap Sort: Builds a max/min heap and extracts elements (O(n log n)).
- Radix Sort: Non-comparative, sorts digits position by position.
Unit-V: Trees and Graphs
-
Trees:
- Hierarchical data structure with nodes connected by edges.
- Types:
- Binary Tree: Each node has at most two children.
- Binary Search Tree (BST): Left child < parent < right child.
- AVL Tree: Self-balancing binary search tree.
- B+ Tree: Used for databases, balances multiple keys.
- Traversals:
- Inorder: Left → Root → Right.
- Preorder: Root → Left → Right.
- Postorder: Left → Right → Root.
-
Graphs:
- Collection of vertices (nodes) and edges (connections).
- Representation:
- Adjacency matrix.
- Adjacency list.
- Graph Traversal:
- DFS (Depth First Search): Explores as far as possible along branches.
- BFS (Breadth First Search): Explores level by level.
- Applications:
- Shortest path (e.g., Dijkstra’s algorithm).
- Minimum spanning tree (e.g., Prim’s and Kruskal’s algorithms).
Key Features of the Subject
- Provides foundational knowledge of algorithms, data structures, and their efficiency.
- Covers practical implementations in C programming.
- Includes advanced topics like AVL Trees, B+ Trees, and graph algorithms.
- Practical focus on solving problems like searching, sorting, and dynamic memory allocation.
Would you like explanations for any specific algorithm, code implementation, or practical examples?
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