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1 SRM UNIVERSITY FACULTY OF ENGINEERING AND TECHNOLOGY SCHOOL OF COMPUTING DEPARTMENT OF CSE COURSE PLAN Course Code Course Title : DATA STRUCTURES AND ALGORITHMS Semester : I Course Time : July Dec 207 : CS200 Day Hour ROOM NO Day Day 2 Day TP702 Day TP702 Day LAB TP702 DS LAB Faculty Details Sec. Name Office Office hour Mail id A S.Ganesh kumar Tech Park p.m ganesh.ks@ktr.srmuniv.ac.in Required Text Books:. Mark Allen Weiss, "Data Structures and Algorithm Analysis in C", 2 nd Edition, Pearson Education, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, "Introduction to Algorithms", PHI Learning Pvt. Ltd., Gilles Brassard, Paul Bratley, Fundamentals of Algorithms, PHI Learning Pvt. Ltd Aaron M. Tanenbaum, Yedidyah Langsam, Moshe J.Augenstein, Data structures using C, Pearson Education, Richard F. Gillberg, Behrouz A. Forouzan, Data structures: A Pseudocode Appproach with C, Cengage Learning, Second Edition, Kenneth A. Berman, Jerome L. Paul, Algorithms, Cengage Learning, Web resources. engineering and computer science/6 046j introduction to algorithms 2. engineering and computer science/6 85 advanced data structures. Prerequisite : C,C++

2 Objectives. To learn about analyzing and designing of algorithms 2. To learn various data structure concepts like Stacks, Queues, Linked List and Hashing 3. To learn advanced Data structures such as balanced search trees, hash tables and priority queues and sorting algorithms. 4. To study various graph processing algorithms Assessment Details Component Assessment tool Weight age Theory component Practical component Test Schedule Test-I 0% Test-II 0% Surprise test I 5% Assignment 5% End Semester Examination 40% Carrying out laboratory work, 5% attendance, and, submission of record, class tests, model examination, quizzes etc. End semester practical 5% examination S.No. DATE TEST TOPICS DURATION Cycle Test - I Unit I & II 2 periods As per calendar 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 To learn about analyzing and designing algorithms To learn various data structure concepts like Stacks, Queues, Linked List and Hashing. To Learn advanced Data structures such as balanced search trees, hash tables and priority queues and sorting algorithms. To study various graph processing algorithms Program outcome An ability to understand and analyze the algorithms To understand the concepts of Stack, Queue and Linked List To implement Sorting,Search tree and Hash tables. To understand various types of Graph Algorithms

3 Detailed Session Plan UNIT II LISTS, STACKS, QUEUES AND HASHING Abstract Data Types (ADTs) The List ADT The Stack ADT The Queue ADT Hashing: Hash Function Separate Chaining Open Addressing Rehashing Extendible hashing. Implementation in C or C++: Operations (Create, Access, Insert and Delete) - Singly linked List - Doubly linked List - Circular linked List - Operations on a Hash Table Create, Insert, Find and Retrieve Session No Topics to be covered Abstract Data Types (ADTs) The List ADT Singly Linked List Circular Linked List Doubly Linked List The Stack ADT The Queue ADT Hashing: Hash Function Time (min) Ref Teaching Method Testing Method Brain storming,,,, 9 Separate Chaining, Assignment, Assignment 0 Open Addressing,2, Assignment Rehashing, Extendible hashing 2,3 4,5 6,7 Implementation in C or C++: Operations (Create, Access, Insert and Delete) - Singly linked List Doubly linked List - Circular linked List Operations on a Hash Table Create, Insert, Find and Retrieve 00 Lab Sessio n Lab Sessio n Lab Sessio n 22,23 24,25 26,27 Implementation in C or C++: Operations (Create, Access, Insert and Delete) - Singly linked List Doubly linked List - Circular linked List Operations on a Hash Table Create, Insert, Find and Retrieve UNIT I INTRODUCTION The Role of Algorithms in computing Analyzing Algorithms Designing Algorithms Growth of functions Asymptotic Notations Divide and Conquer Recurrences Maximum sub array problem Stressan s Method Substitution method Recurrence tree method The Master method Floors and

4 Ceilings The Role of Algorithms in computing Analyzing Algorithms,Designing Algorithms Growth of functions Asymptotic Notations Divide and Conquer, Recurrences,2,2 2 2,2 Maximum sub array problem 23,2 Objective type test 24 Stressan s Method,Substitution method 2, Assignment Recurrence tree method, The Master method Floors and Ceilings UNIT III TREES AND SORTING Implementation of Trees Tree Traversals with an application Binary Trees Binary Search Trees AVL trees Splay Trees B Trees Sorting: Insertion Sort Shell Sort Heap Sort Merge Sort Quick Sort - Implementation in C or C++: Tree Traversals Inorder, Preorder and Postorder - Operations on Binary Search trees Insert, Find, Delete and Traversals - Soring Techniques Insertion Sort, Merge Sort and Quick Sort. 28 Implementation of Trees, 29 Tree Traversals with an application, 30 Binary Trees, Binary Search Trees AVL trees AVL trees Splay Trees,2,,,, 35 B Trees, 36 Sorting: Insertion Sort, Shell Sort, 37 Heap Sort,2, 38 Merge Sort, 39 Quick Sort,2,

5 40,4 42,43 44,45 Implementation in C or C++: Tree Traversals Inorder, Preorder and Postorder Operations on Binary Search trees Insert, Find, Delete and Traversals Techniques Insertion Sort, Merge Sort 00 Lab Session 00 Lab Session 00 Lab Session 46,47 Quick Sort. 00 Lab Session UNIT IV GRAPH ALGORITHMS Representations of Graphs Topological sort Shortest Path Algorithms Network Flow Problems Minimum Spanning Tree Applications of Depth First Search NP Completeness Implementation in C or C++: Graph Traversals - Breadth First Search - Depth First Search - Graph Processing Algorithms - Dijkstra s Algorithm for minimum cost path - Kruskal s Algorithm for minimum spanning trees Representations of Graphs Graph Processing Algorithms Topological sort Shortest Path Algorithms- Dijkstra s Algorithm 52 Shortest Path Algorithms,2, Network Flow Problems Minimum Spanning Tree- Kruskal s Algorithm, Assignment Assignment Assignment 55 Minimum Spanning Tree,2, 56 Applications of Depth First search, 57 Introduction to NP Completeness, 58 NP Complete problems, 59,60 6,62 63,64 Implementation in C or C++: Graph Traversals - Breadth First Search - Depth First Search 00 Lab session Dijkstra s Algorithm for minimum cost path 00 Lab session Kruskal s Algorithm for minimum spanning trees. 00 Lab Session UNIT V ALGORITHM DESIGN TECHNIQUES Greedy Algorithms Divide and Conquer Dynamic Programming Randomized algorithms Backtracking Algorithms. Implementation in C or C++: Divide and Conquer Knapsack Problem - Backtracking 8-Queen s Problem 65 Greedy Algorithms,2

6 66 Divide and Conquer,2 Objective type test 67 Dynamic Programming,2 Brain storming Dynamic Programming Randomized algorithms Backtracking Algorithms,2 Brain storming Surprise test 7 Backtracking Algorithms Implementation in C or C++: Divide and 72,73 Conquer- Knapsack Problem 00 Lab session 74,75 Backtracking 8-Queen s Problem 00 Lab session -Black Board -Power Point Signature of Staff Signature of H.O.D

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