SRM UNIVERSITY FACULTY OF ENGINEERING AND TECHNOLOGY SCHOOL OF COMPUTING DEPARTMENT OF CSE COURSE PLAN

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1 SRM UNIVERSITY FACULTY OF ENGINEERING AND TECHNOLOGY SCHOOL OF COMPUTING DEPARTMENT OF CSE COURSE PLAN Course Code : CS0251 Course Title : DATA STRUCTURES AND ALGORITHMS Semester : III Course Time : July Dec 2011 DAY SECTION A B Hour Timing Hour Timing , Location : S.R.M.E.C Tech Park Faculty Details SEC NAME OFFICE OFFICE HOUR MAIL ID A Ms.Snehalatha Tech park 8 th floor Mon-Fri snehalatha@ktr.srmuniv.ac.in B Ms.Sasi Rekha Sankar Tech park 8 th floor Mon-Fri sasirekhasankar@ktr.srmuniv.ac.in Required Text Books: 1. Mark Allen Weiss Data Structures and Analysis in C - Pearson Education Pubs Aho, Ullman & Hopcraft, The Design and Analysis of Algorithms, Addison Wesley, Richard F.gilberg and Behrouz A. Forouzan Data Structures- A Pseudocode Approach with C++, Thomson Asia, Web resources Prerequisite : Nil Objectives To Learn Several data structure concepts like stacks, queues, linked list, trees Applications of data structures Algorithm design concepts like Divide and Conquer, Backtracking and Dynamic programming

2 Assessment Details Cycle Test I : 10 Marks Surprise Test I : 8 Marks Cycle Test II : 10 Marks Surprise Test II : 7 Marks Model Exam : 15 Marks Test Schedule S.No. DATE TEST TOPICS DURATION 1 Cycle Test - I Unit I & II 2 periods 2 Cycle Test - II Unit III & IV 2 periods 3 Model Exam All 5 units 3 Hrs Outcomes Students who have successfully completed this course will have full understanding of the following concepts Course outcome Program outcome To learn The analysis of algorithms Several abstract data types such as Stack, Queue, linked lists, Trees and graphs Applications of Data structures Sorting and Searching algorithms An ability to understand the basic operations on Abstract Data types and their use Implementation of Abstract Data Types using an by Array or a linked list To analyze the running time of different algorithms for a given problem for worst case and average case To implement various searching and sorting concepts Detailed Session Plan INTRODUCTION Definitions of Data Structure and Algorithm. Time and Space complexity- Algorithm notations and Analysis Orders, Variables Data types- Arrays- String processing Sorting and Searching- Insertion- Selection-Merge-Quick-Radix-Binary Search- Linear Search-Hashing Sessi on No. Topics to be covered Time (min) Ref Teaching Method Testing Method 1 Definitions of Data Structure and Algorithm. Time and Space complexity 2 Algorithm Notations and Analysis 3 Orders of Notations 4 Variables-Datatypes 5 Arrays and string processing

3 Insertion Sort and Selection Sort 6 7 Merge Sort and Quick Sort, Radix Sort, Linear and Binary Search 8

4 Hashing 9 STACKS,QUEUES AND LINKED LIST Stacks: Array representation of stacks Arithmetic expressions- Quick sort using stack- Towers of Hanoi problem- Queues: : Array representation of Queues 10 Array representation of stacks 11 Arithmetic expressions- Quick sort using stack 12 Towers of Hanoi problem Surprise Test 13 Array representation of Queues 14 Deque, Priority Queue, Circular Queue-, 15 Representation of Linked List- Traversing, a Linked List 16 Insertion and Deletion in a singly linked list 17 Doubly Linked List 18 Circular Linked List, Comparative study TREES AND GRAPHS Binary tree- Representation Traversing Threaded Binary tree- Binary Search tree- Insertion deletion into a binary search tree. Graph- Representation of Graph- Shortest path Operation on Graphs- Traversing a Graph- Topological Sorting Binary tree representatiom Traversing a binary tree Threaded Binary Tree Binary Search Tree 23 Insertion and Deletion into a BST Surprise Test Representation of a graph 24 Shortest path 25 Operation on graph and traversing a graph 26 Topological sorting 27 DIVIDE AND CONQUER METHOD General Method - Binary Search Finding Maximum and Minimum Greedy Method General Method KnapSack Problem Minimum Spanning Tree Algorithm Single Source Shortest Path Algorithm. 28 General method

5 Binary search 29 Finding Max and Min 30 Greedy method 31 Knapsack problem 32 Knapsack problem Minimum Spanning Tree Algorithm Single Source Shortest Path Algorithm Single Source Shortest Path Algorithm DYNAMIC PROGRAMMING AND BACKTRACKING Shortest Path Algorithm 0/1 Knapsack Problem Travelling Salesman Problem - Depth First Search Breadth First Search- 8-Queens Problem- Sum of Subsets Graph Coloring- Hamiltonian Cycle-Knapsack Problem Branch and Bound Method Shortest Path algorithm:0/1 Knapsack problem Travelling Salesman problem 39 Depth First Search 40 Breadth First Search 8-Queens problem Surprise test Sum of Subsets 43 Graph coloring 44 Hamiltonian Cycle 45 Branch and Bound Method

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