Data Structures & Analysis of Algorithms (MCA)

Arrays, linked lists, stacks, queues, trees, graphs, sorting, searching and algorithm design and complexity analysis.

6 MonthsDuration 5Chapters30Topics

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Syllabus · पाठ्यक्रम

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01Unit 1: Introduction, Arrays and Linked Lists 6 topics

Data structures and abstract data types
Algorithm complexity: time and space
Asymptotic notations: big-O, Omega, Theta
Arrays: row-major and column-major address calculation
Singly, doubly and circular linked lists
Polynomial representation using linked lists

02Unit 2: Stacks, Queues, Searching, Sorting and Hashing 6 topics

Stack operations and applications
Infix to postfix conversion and postfix evaluation
Queues, circular queues, deques and priority queues
Linear and binary search
Insertion, selection, bubble, quick, merge and heap sort
Hashing: hash functions and collision resolution

03Unit 3: Trees 6 topics

Binary tree terminology and representation
Tree traversals: preorder, inorder, postorder
Binary search tree operations
AVL trees and rotations
Heaps and B-trees
Huffman coding

04Unit 4: Graphs 6 topics

Graph terminology and representations
Breadth-first and depth-first search
Minimum spanning tree: Prim's and Kruskal's algorithms
Single-source shortest path: Dijkstra and Bellman-Ford
All-pairs shortest path: Floyd-Warshall
Topological sort

05Unit 5: Algorithm Design Techniques 6 topics

Divide and conquer and the master theorem
Greedy method: fractional knapsack, activity selection
Dynamic programming: 0/1 knapsack, LCS, matrix chain multiplication
Backtracking: N-Queens, subset sum
Branch and bound
P, NP, NP-complete and NP-hard classes

About

You will be able to

Analyse algorithms using asymptotic notation and recurrence relations
Implement arrays, linked lists, stacks and queues and use them in applications
Compare searching, sorting and hashing techniques by complexity
Build and traverse binary trees, BSTs, AVL trees, heaps and B-trees
Apply BFS, DFS, minimum spanning tree and shortest-path algorithms to graphs
Solve problems using divide and conquer, greedy, dynamic programming and backtracking

Who it is for

MCA students of Semester 2 (AKTU, Lucknow)
Students preparing for coding interviews, GATE and UGC-NET

What you need

Programming in C (pointers and structures)
Basic discrete mathematics

Questions

Which syllabus does this Data Structures & Analysis of Algorithms course follow?

It follows the AKTU (Lucknow) MCA syllabus for Semester 2. If your own university's syllabus differs, the centre follows your university's syllabus and unit order.

Will I write programs too?

Yes. All major structures and algorithms are implemented in the Data Structures & Analysis of Algorithms Lab.

How are students tested at the centre?

Unit-wise MCQ tests, numerical / problem practice, previous AKTU question papers and a final mock paper before the semester exam.