Explores stacks, queues, lists, hash tables, graphs, trees and sorting over data structures.

Transcription

1 Course Code : 15ACS04 Course Title : Data Structures Course Structure : Lectures Tutorials Practicals Credits Course Coordinator : Sri V Sunil Babu Team of Instructors : Mr. G.Murali I. Course Overview Explores stacks, queues, lists, hash tables, graphs, trees and sorting over data structures. II. Prerequisite(s): Level Credits Periods / Week Prerequisites UG 4 4 Mathematical background,logical Thinking and Basic concepts of Computer Programming. III. Assessment: FORMATIVE ASSESMENT Mid Semester Test I for 20 Marks in first 2 units is conducted at8 the end of 9 th week. Mid Semester Test II for 20 Marks in last three units is conducted at the end of the course work. 20 Marks Average of two tests is taken as final Multiple Choice Mid Semester Test I for 10 Marks in first 2 units is conducted at8 the end of 9 th week. Multiple Choice Mid Semester Test I for 10 Marks in first 2 units is conducted at the end of the course work. Average of two tests is taken as final Total ( Formative) SUMMATIVE ASSESMENT End Semester Examination in all units is conducted for 70 Marks Grand Total 10 Marks 30 Marks 70 marks 100 Marks

2 IV. Course objectives: 1. Demonstrate familiarity with major algorithms and data structures. 2. Analyze performance of algorithms. 3. Choose the appropriate data structure and algorithm design method for a specified application. 4. Determine which algorithm or data structure to use in different scenarios. 5. Demonstrate understanding of the abstract properties of various data structures such as stacks, queues, lists, trees and graphs 6. Use various data structures effectively in application programs. 7. Demonstrate understanding of various sorting algorithms, including bubble sort, insertion sort, selection sort, heap sort and quick sort. 8. Understand and apply fundamental algorithmic problems including Tree traversals, Graph traversals, and shortest paths. V. Course Outcomes: 1. Upon completion of this course, students will acquire knowledge about programming skills. 2. An understanding of the basic data structures and problem solving knowledge. 3. An understanding of the basic sorting algorithms. 4. The appropriate use of particular data structures and algorithm to solve a problem. 5. An understanding of the linear data structures such as stack, queue, and linked list. 6. An understanding of the non-linear data structures such as trees and graphs.

3 VI. Program outcomes: Program Outcomes a An ability to apply knowledge of computing, mathematical foundations, algorithmic principles, and computer science and engineering theory in the modeling and design of computer-based systems to real-world problems (fundamental engineering analysis skills) b An ability to design and conduct experiments, as well as to analyze and interpret data (information retrieval skills) c An ability to design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs, within realistic constraints such as economic, health and safety, manufacturability, and sustainability (Creative Skills) d An ability to function effectively on multi-disciplinary teams (team work) e An ability to analyze a problem, identify, formulate and use the appropriate computing and engineering skills for obtaining its solution (engineering problem solving skills) f Obtaining the knowledge of algorithmic skills regarding data structures. (program oriented skills) g An ability to communicate effectively both in writing and orally (speaking / writing skills) h The broad education necessary to analyze the local and global impact of computing and engineering solutions on individuals, organizations, and society (engineering impact assessment skills) i Recognition of the need for, and an ability to engage in continuing professional development and life-long learning (continuing education awareness) j A Knowledge of structural skills which are related to theoretical skills for programming (detailed subject oriented skills). k An ability to use current techniques, skills, and tools necessary for computing and engineering practice (practical engineering analysis skills) l An ability to apply design and development principles in the construction of software and hardware systems of varying complexity (software hardware interface) m An ability to recognize the importance of professional development by pursuing postgraduate studies or face competitive examinations that offer challenging and rewarding careers in computing (successful career and immediate employment)..

4 VII. Syllabus: JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY ANANTHAPURAMU COLLEGE OF ENGINEERING (AUTONOMOUS) :: PULIVENDULA Regulation R15 B.Tech. I Year -IISem(C.S.E) L T P C Data Structures UNIT-I Stacks & Queues: stacks, stacks using dynamic arrays, Queues, circular queues using dynamic arrays, amazing problem, evaluation of expressions. Linked List: single linked list and chains, representing chains in C, Linked stacks and queues, polynomials, additional list operations, equivalence classes, sparse matrices, double linked list. UNIT II Trees : Introduction, Binary tree, Binary tree traversals, Additional binary tree operations, Threaded binary trees, Heaps, Binary search trees, Selection trees, Forests, Representation of disjoint sets, Counting binary trees. UNIT-III Graphs: The graph abstract datatype, Elementary graph operations, Minimam cost spanning trees, Shortest paths and transitive closure. Sorting: Motivation, Insertion sort, Quick sort, Merge sort, Heap sort, sorting on several keys, list and table sorts, external sorting. UNIT IV Hashing: Introduction, Static hashing, dynamic hashing, Bloom Filters. Priority Queues: Single ended and double ended priority queues, leftist trees, Binominal Heaps, Fibonacci Heaps, Pairing Heaps, Symmetric Min-Max Heaps, and Interval Heaps. UNIT-V Efficient binary search trees: Optimal binary search trees, AVL Trees, RED Black Trees, Splay Trees, M- Way search trees, B-Trees, B+ -Trees. Text Books: 1. Fundamentals of Data structures in C 2 nd edition HOROWITZ, SAHNI, ANDERSON-FREED.

5 IX. Course Plan: The course plan is meant as a guideline. There may probably be changes. Lecture No. Course Learning Outcomes Topics to be covered Reference 1-4 An understanding of the linear Introduction to Data Structures,Linear Data T1: data structures like Stacks. Structures Stack implementation using Arrays and linked List 4-6 An understanding of the linear Linear Data Structures Queue implementation T1: data structures like Queues. using Arrays and linked List 6-8 Evaluate mathematical expressions using precedence rules.. Stack applications Evaluation of expressions: Infix, postfix, prefix T1: An understanding of the Linear single linked list and chains, representing data structures like single linked chains in C list An understanding of the Implements the polynomials Equations, polynomials equations, 13 An understanding of the Linear Double Linked List Creation, Insertion, data structures like Double linked list. Deletion T1: T1:4.4 T1:4.5, Reduce the size of the matrices sparse matrices T1: An understanding of the Non Linear data Structures like trees An understanding the binary trees An understanding the searching and selection in trees An understanding a counting the binary trees In this learning the graph operations Introduction, Binary tree, Binary tree traversals T1: Additional binary tree operations, Threaded T1: binary trees, Heaps, binary search trees, selection trees T1: Forests, representation of disjoint sets, counting binary trees Graphs: The graph abstract data type, Elementary graph operations T1: T1: Here learning about shortest path trees and their closure. Minimum cost spanning trees, shortest paths and transitive closure An understanding about sorting Sorting: Motivation, Insertion sort, quick sort, programs. merge sort, Heap sort Here learning the sorting Sorting on several keys, list and table sorts, programs external sorting. T1: T1: T1:

6 37-40 An understanding sbout hashing Hashing: Introduction, static hashing, dynamic T1: programs hashing 41 Discuss about Bloom filters. Bloom filters T1: An understanding about queues. Priority queues: single ended and double ended priority queues T1: Discuss about leftist trees. Leftist trees T1: Describe the basic concept of Binomial heaps, Fibonacci heaps, pairing heaps T1: heaps Detail discussion about heaps. Symmetric min-max heaps, and interval heaps. T1: An introduction about trees Efficient binary search trees: Optimal binary search trees T1: Explain about the trees with an AVL trees, RED Black trees, splay trees, T1: examples Describe different types of trees with an example. M-way search trees, b-trees, b+-trees T1: X. Mapping course outcomes leading to the achievement of the program outcomes: Course Outcomes Program Outcomes a b c d e f g h i j k l m 1 H S 2 H S 3 H S 4 S H 5 S H 6 H S S = Supportive H = Highly Related Justification of Course syllabus covering Course Outcomes: By covering the syllabus a student can understand the designing of algorithm and flowcharts. Student is able to develop applications using C Program Constructs. Justification of CO s PO s Mapping Table: By mapping CO-1 to the PO s F and J which are related to the course CO1: The student is able to analyze the programming skills. By mapping CO-2 to the PO s A and M, which are related to the course CO2: The student is able to design algorithm and draw the flowcharts for different types of problems By mapping CO-3 to the PO s E and M which are related to the course CO3: The student is able to understand the purpose of different programming Constructs.

7 By mapping CO-4 to the PO s C and K which are related to the course CO4: The student is able to understand the creative skills and practical skills of data structures. By mapping CO-5 to the PO s E and F which are related to the course CO5: The student is able to understand the Purpose of Stacks, Queues and Linked lists. By mapping CO-6 to the PO s B and M which are related to the course CO6: The student is able to understand the concept of Graphs and Trees.