Regulation: R23 Branch: Information Technology Semester: 2-1

Advanced Data Structures & Algorithms

Verified vs. official syllabus Checked 2026-07-01

Subject names, credits, and semester placement are cross-confirmed against JNTUK's own centrally-administered exam records. Detailed unit topics are sourced from an autonomous JNTUK-affiliated college's published syllabus and have not been independently verified against the university's own document -- autonomous colleges may adapt unit-level content locally.

Unit-wise syllabus

UNIT 01

Advanced Data Structures

AVL trees - creation, insertion, deletion operations and applications; B-trees - creation, insertion, deletion operations and applications; Heap trees (priority queues) - min and max heaps, operations and applications; Graphs - terminology, representations, basic search and traversals, connected and biconnected components, applications

UNIT 02

Algorithm Analysis & Divide and Conquer

Algorithm, types of algorithms, algorithm specifications; Performance analysis: space and time complexity analysis, asymptotic notations; Divide and conquer: general method, quick sort, merge sort; Strassen's matrix multiplication, convex hull

UNIT 03

Greedy Method & Dynamic Programming

Greedy method: general method, job sequencing with deadlines, knapsack problem, minimum cost spanning trees, single source shortest paths; Dynamic programming: general method, all pairs shortest paths, single source shortest paths - general weights (Bellman-Ford); Optimal binary search trees, 0/1 knapsack, string editing; Travelling salesperson problem

UNIT 04

Backtracking & Branch and Bound

Backtracking: general method, 8-queens problem, sum of subsets problem; Graph colouring, 0/1 knapsack problem; Branch and bound: general method, 0/1 knapsack problem; Travelling salesperson problem

UNIT 05

NP Hard and NP Complete Problems

Basic concepts, Cook's theorem; NP hard graph problems: clique decision problem (CDP), chromatic number decision problem (CNDP), travelling salesperson decision problem (TSP); NP hard scheduling problems: scheduling identical processors; Job shop scheduling