Professional Elective-I Advanced Data Structure

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

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

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

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.

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

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

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

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

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

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

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

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

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

ALL THE BEST