1. Professional Elective-I Advanced Data Structure

2. Advanced Data Structure (2CS302)
Theory Course- 2CO521 (3 lectures, 3 credits)
NO LAB

3. Text Books
Peter Brass, “ Advanced Data Structures”, Cambridge University Press
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, “Introduction to Algorithms,” 3rd Edition, PHI, 2009

4. Reference Books ReinhardDiestel, “Graph Theory”, Spinger-Verlag, 2000
MIT Courseware by Erik Demaine

5. Course Objectives
To be able to understand balanced search trees and tree structures for set intervals, transformations of data structures and data structures for strings.
To be able to learn and understand advanced concepts and types of heaps, graphs and hashing.
To be able to apply the knowledge, identify appropriate data structures to be used in real applications and analyse the algorithms.

6. Course Outcomes CO
After the completion of the course the student should be able to
Bloom’s Cognitive
level
Descriptor
CO1
Explain and describe the different advanced data structures. 2
Understanding
CO2
Apply and demonstrate knowledge of advanced data structures such as trees, graphs etc. for solving real world problems
3, 4
Applying, Analyzing
CO3
Compare and evaluate the impact of data structure transformations done and performance of different searching techniques.
4, 5
Analyzing, Evaluating

7. Division into 6 Modules Module 1: Balanced Search Trees
Module 2: Tree Structures for Set of Intervals
Module 3- Heaps
Module 4- Data Structure Transformations
Module 5- Hashing
Module 6- Selected Graph Problems

8. Division into 6 Modules Module-1 Module 1: Balanced Search Trees
AVL trees,
B Trees
Lexical Search Trees
Red-black trees
Splay Tree

9. Division into 6 Modules Module-2
Module 2: Tree Structures for Set of Intervals
Module-2
Interval Trees, Segment Trees,
Trees for the Union of Intervals,
Trees for Sums of Weighted Intervals,
Trees for Interval-Restricted Maximum Sum Queries,
Orthogonal Range Trees,
Range-Counting and the Semigroup Model,
kd-Trees and Related Structures

10. Division into 6 Modules Module-3 Module 3- Heaps
Balanced Search Trees as Heaps,
Array-Based Heaps, Heap-Ordered Trees and Half-Ordered Trees,
Leftist Heaps, Skew Heaps, Binomial Heaps,
Changing Keys in Heaps, Fibonacci Heaps,
Double-Ended Heap Structures and Multidimensional Heaps

11. Division into 6 Modules Module-4
Module 4- Data Structure Transformations
Module-4
Data Structure Transformations
Making Structures Dynamic,
Making Structures Persistent
Data Structures for Strings: Tries
Tries and Compressed Tries, Dictionaries Allowing Errors in Queries,
Suffix Trees, Suffix Arrays

12. Division into 6 Modules Module-5 Module 5- Hashing
Basic Hash Tables and Collision Resolution,
Universal Families of Hash Functions,
Perfect Hash Functions,
Hash Trees, Extendible Hashing,
Membership Testers and Bloom Filters

13. Division into 6 Modules Module-6 Module 6- Selected Graph Problems
Network flows: Max flow – mincut theorem,
Probabilistic methods – Markov’s inequality,
Dynamic Graph Problems

14. Evaluation ISE-I (10 marks): Assignment Submissions
MSE (30 marks): Module 1, 2 & 3
ISE-II (10 marks): Declared Test (5 marks) Surprise Test (5 marks)
ESE(50 marks): Module 1, 2 & 3 (30 to 35 marks) &
Module 4, 5 & 6 (15 to 20 marks)
ESE Separate Passing

15. ALL THE BEST