CP5151 ADVANCED DATA STRUCTURES AND ALGORITHMS SYLLABUS - ANNA UNIVERSITY PG REGULATION 2017 - Anna University Internal marks 2018
OBJECTIVES:

• To understand the usage of algorithms in computing.
• To learn and use hierarchical data structures and its operations
• To learn the usage of graphs and its applications.
• To select and design data structures and algorithms that is appropriate for problems.
• To study about NP Completeness of problems.

 CP5151 ADVANCED DATA STRUCTURES AND ALGORITHMS SYLLABUS

UNIT I ROLE OF ALGORITHMS IN COMPUTING

Algorithms – Algorithms as a Technology- Insertion Sort – Analyzing Algorithms – Designing Algorithms- Growth of Functions: Asymptotic Notation – Standard Notations and Common Functions- Recurrences: The Substitution Method – The Recursion-Tree Method

UNIT II HIERARCHICAL DATA STRUCTURES
Binary Search Trees: Basics – Querying a Binary search tree – Insertion and Deletion- Red-Black trees: Properties of Red-Black Trees – Rotations – Insertion – Deletion -B-Trees: Definition of Btrees – Basic operations on B-Trees – Deleting a key from a B-Tree- Fibonacci Heaps: structure – Mergeable-heap operations- Decreasing a key and deleting a node-Bounding the maximum degree.

UNIT III GRAPHS
Elementary Graph Algorithms: Representations of Graphs – Breadth-First Search – Depth-First Search – Topological Sort – Strongly Connected Components- Minimum Spanning Trees: Growing a Minimum Spanning Tree – Kruskal and Prim- Single-Source Shortest Paths: The Bellman-Ford algorithm – Single-Source Shortest paths in Directed Acyclic Graphs – Dijkstra‘s Algorithm; All-Pairs Shortest Paths: Shortest Paths and Matrix Multiplication – The FloydWarshall Algorithm;

UNIT IV ALGORITHM DESIGN TECHNIQUES
Dynamic Programming: Matrix-Chain Multiplication – Elements of Dynamic Programming – Longest Common Subsequence- Greedy Algorithms: An Activity-Selection Problem – Elements of the Greedy Strategy- Huffman Codes.

UNIT V NP COMPLETE AND NP HARD
NP-Completeness: Polynomial Time – Polynomial-Time Verification – NP- Completeness and Reducability – NP-Completeness Proofs – NP-Complete Problems

TOTAL: 60 PERIODS

OUTCOMES:

• Upon the completion of the course the students should be able to:
• Design data structures and algorithms to solve computing problems
• Design algorithms using graph structure and various string matching algorithms to solve real-life problems
• Apply suitable design strategy for problem solving

REFERENCES:

1. Alfred V. Aho, John E. Hopcroft, Jeffrey D. Ullman, ―Data Structures and Algorithms‖, Pearson Education, Reprint 2006.
2. Robert Sedgewick and Kevin Wayne, ―ALGORITHMS‖, Fourth Edition, Pearson Education.
3. S.Sridhar,‖Design and Analysis of Algorithms‖, First Edition, Oxford University Press. 2014
4. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, ―Introduction to Algorithms‖, Third Edition, Prentice-Hall, 2011.
Anna University PG Regulation 2017 CSE Syllabus, CP5151 Applied Probability And Statistics Syllabus, Reg 2017 CP5151 Syllabus, 1st Sem PG Advanced Data Structures