VII Sem/VIII Sem Scheme & Syllabus

Applicable for the academic year 2018-19 Batch: 2015

SCHEME & SYLLABUS OF

VII & VIII SEMESTER B.E.

INFORMATION SCIENCE & ENGINEERING 2020-21

Department of Information Science & Engg., 1

Applicable for the academic year 2020-21 Batch: 2017

Department of Information Science & Engg., 2 Applicable for the academic year 2020-21 Batch: 2017

Vision of the Department: To be a centre for quality education and research in Information Science and Engineering to create high quality professionals for catering to the need of the society.

Mission of the Department: 1) To enable students to acquire strong fundamental concepts related to the Information Science and Engineering through experiential learning. 2) To educate students towards state-of-the-art-technologies and multidisciplinary practices for a successful career by creating learning- teaching-learning ambience. 3) To inculcate life-long learning through innovation and research attitudes among students related to Information Science and Engineering.

Program Educational Objectives (PEOs):

The objectives of Information Science and Engineering degree program are to prepare students to meet the academic excellence, professionalism, and ability to solve a broad range of problems in rapidly changing technological, economic and social environment.

Graduates of the program will: 1. Pursue career as software engineer, project manager, data scientist, entrepreneur and pursue higher studies and research in Information Science and Engineering domains. 2. Apply mathematical, scientific and Information Science and Engineering knowledge with multidisciplinary approaches to solve real world problems. 3. Possess professionalism, ethical and societal responsibilities and engage in life-long learning through pursuit of skill development and certification courses in Information Science and Engineering.

Programme Outcomes (POs): To achieve the above objectives, Information Science and Engineering degree programme strives to obtain the following outcomes which should be achieved by all graduates at the time of their graduation.

Engineering Graduates will be able to:

1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

Department of Information Science & Engg., 3 Applicable for the academic year 2020-21 Batch: 2017

2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences. 3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations. 4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions. 5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations. 6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice. 7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development. 8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice. 9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings. 10. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions. 11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply

Department of Information Science & Engg., 4 Applicable for the academic year 2020-21 Batch: 2017

these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments. 12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Programme Specific Outcomes (PSOs): 1) Computing System: Demonstrate the knowledge of evolving hardware and/or software to develop solutions to real life computational problems with a focus on performance optimization.

2) Communication and Security: Design and develop solutions for providing efficient transmission, storage, security and privacy of data in diverse computing environment.

3) Information management: Apply tools and techniques for management of information system, data analysis and knowledge discovery in the process of decision making.

Department of Information Science & Engg., 5 Applicable for the academic year 2020-21 Batch: 2017

2.0

1.5

3.0

4.0

25.0

Credits

100

850

Total Total

Marks

400

End

Exam Exam

)

Marks.

450

Examination

C.I.E. C.I.E.

Marks

(Batch201

(Hrs.)

Duration

Week

Teaching Hours/ Hours/ Teaching

ISE

Dept.

Teaching Teaching

B.E.(Information Scienceand Engineering)

VII Semester VII academicyear 20

III

DEPARTMENTOF INFORMATION SCIENCEAND ENGINEERING

–

SIDDAGANGA INSTITUTE OFTECHNOLOGY, TUMKUR

Title

Total

III

–

Industrial Training Industrial

Major Project Project Major

Software Testing Laboratory Testing Software

Networks Laboratory Networks

Open Elective Elective Open

Humanities

Professional Elective Elective Professional

Software Testing Software

Cryptography and Network Security Network and Cryptography

Sub. Sub.

Code

7ISIT

7ISMP

7ISL2

7ISL1

ISPEX

7IS01

7CCI1

Sl. Sl.

Department of Information Science & Engg., 6 Applicable for the academic year 2020-21 Batch: 2017

Department of Information Science & Engg., 7 Applicable for the academic year 2020-21 Batch: 2017

Professional Electives for Academic Year 2020-2021 Fifth Semester - Eighth Semester

Sl.No. Code Elective Name Sl.No. Code Elective Name 1 RISE01 Advanced DBMS 17 RISE17 High Performance Computing 2 RISE02 System Software 18 RISE18 Information Retrieval Fuzzy Logic with Engg. 3 RISE03 Computer Vision 19 RISE19 Applications Advanced Data Structures and Artificial Neural Networks and 4 RISE04 Algorithms 20 RISE20 Deep Learning 5 RISE05 Cloud Computing 21 RISE22 Distributed Operating System 6 RISE06 Language Processor 22 RISE23 Big Data Analytics Object Oriented Modeling and 7 RISE07 Design 23 RISE25 Advanced Computer Architecture 8 RISE08 Mobile Programming 24 RISE26 Bioinformatics 9 RISE09 Wireless Sensor Networks 25 RISE27 Intelligent Agent Systems Data warehouse and Data 10 RISE10 Mining 26 RISE28 Human Computer Interaction NLP with Python 11 RISE11 Digital Image Processing 27 RISE35 Sensors and Internet of Things 12 RISE12 Business Intelligence 28 RISE36 Enterprise Content Agile Software Technology 13 RISE13 Management 29 RISE37 Web Technology 14 RISE14 Wireless and Mobile Networks 30 RISE38 15 RISE15 Storage Technology 31 RISE39 JAVA and J2EE System simulation and 16 RISE16 Modeling

Department of Information Science & Engg., 8 Applicable for the academic year 2020-21 Batch: 2017

CRYPTOGRAPHY AND NETWORK SECURITY Contact Hours/ Week : 4 Credits : 4 Total Lecture Hours : 52 CIE Marks : 50 Sub. Code : 7CCI1 SEE Marks : 50

Course Outcomes: Upon completion of this course the student will be able to: CO1: Analyze security principles and Solve problems on classical Encryption Techniques. CO2: Apply the concepts of Block Ciphers and Principles of Pseudorandom Number Generation CO3: Apply Number Theory Principles to develop Public key Cryptosystem and Hash Function CO4: Analyse different Authentication Protocols and Key Management Protocols

CO5: Identify appropriate cryptography scheme and security mechanism for different computing environment and information systems

UNIT I INTRODUCTION: Introduction: Computer Security concepts, The OSI Security Architecture, Security Services, Mechanisms and Attacks, A Model of Network Security. SYMMETRIC CIPHERS: Classical Encryption Techniques: Symmetric Cipher Model, Substitution Techniques, Transposition Techniques, Rotor machine, Steganography. Block Cipher and the Data Encryption Standard: Block Cipher Principles, The Data Encryption Standard, DES Example, Strength of DES, Differential and Linear Cryptanalysis. 10 Hrs UNIT II SYMMETRIC CIPHERS (contd..) Block Cipher Operation: Multiple Encryption and triple DES, Electronic Code Book, Cipher Block Chaining Mode, Cipher Feedback Mode, Output feedback Mode, Counter Mode. Pseudorandom Number Generation and stream ciphers: Principles of Pseudorandom Number Generation, Pseudorandom Number Generators, Pseudorandom Number Generation using a block cipher, Stream cipher, RC4. 10 Hrs UNIT III Number Theory: Prime Numbers, Fermat’s and Euler’s Theorems, Testing for Primality. PUBLIC-KEY CRYPTOGRAPHY AND RSA: Principles of Public-Key Cryptosystems, The RSA Algorithm. Diffie-Hellman Key Exchange. CRYPTOGRAPHIC DATA INTEGRITY ALGORITHMS: Cryptographic Hash Functions: Applications of Cryptographic hash functions, Two simple hash Functions, Secure Hash Algorithm. 10 Hrs

Department of Information Science & Engg., 9 Applicable for the academic year 2020-21 Batch: 2017

UNIT IV MESSAGE AUTHENTICATION: Authentication Requirements, Authentication Functions, Message Authentication Codes, Security of MACs, MACs based on Hash Functions: HMAC.

DIGITAL SIGNATURES: Digital Signatures, Digital Signature Standard. KEY MANAGEMENT AND DISTRIBUTION: Symmetric Key distribution using symmetric encryption, Symmetric Key distribution using Asymmetric encryption, Distribution of public keys, X.509 certificates, Kerberos. 11 Hrs UNIT V TRANSPORT-LEVEL SECURITY Transport level security: Web Security considerations, Secure Sockets Layer and Transport Layer Security. Transport Layer Security. HTTPS, Secure Shell. INTERNET SECURITY: Electronic Mail Security: Pretty Good Privacy, S/MIME. IP Security: Overview, IP Security Policy. SYSTEM SECURITY: Intruders: Intruders, Intrusion detection. Malicious Software: Types of Malicious Software, Viruses. Firewalls: The need for Firewalls, Firewall Characteristics, Types of Firewalls. 11 Hrs TEXT BOOK: William Stallings, Cryptography and Network Security, Fifth Edition, Prentice Hall of India, 2005 (Chapters 1.1-1.6, 2.1-2.5, 3.1-3.5, 6.1-6.6, 7.1- 7.5, 8.1-8.3, 9.1-9.2, 10.1, 11.1-11.2, 11.5, 12.1-12.5, 13.1,13.4, 14.1-14.4, 15.3, 16.1-16.5, 18.1-18.2, 19.1,19.2, 20.1-20.2, 21.1-21.2, 22.1-22.3)

REFERENCES: 1. Charlie Kaufman, Radia Perlman, Mike Speciner, Network Security: Private Communication in a Public World, Second Edition, Pearson Education Asia, 2002. 2. Atul Kahate, Cryptography and Network Security, Tata Mc GrawHill, 2003.

SOFTWARE TESTING Contact Hours/ Week : 4 Credits : 4 Total Lecture Hours : 52 CIE Marks : 50 Sub. Code : 7IS01 SEE Marks : 50

Course Outcomes: Upon completion of this course the student will be able to:

Department of Information Science & Engg., 10 Applicable for the academic year 2020-21 Batch: 2017

CO1: Identify various software testing techniques, strategies and principles. CO2: Design the test cases the application testing using test data. CO3: Demonstrate various levels of testing on real time applications using appropriate techniques. CO4: Create the Test goals, Policies, Plans, and Documents. CO5: Apply the defect life cycle and defect prevention techniques.

UNIT-I A Perspective on Testing, Examples: Basic definitions, Test cases, Insights from a Venn diagram, Identifying test cases, Error and fault taxonomies, Examples: Generalized pseudo code, The triangle problem, The commission problem, The SATM (Simple Automatic Teller Machine) problem NextDate function, The currency converter, Saturn windshield wiper. Boundary Value Testing: Boundary value analysis, Robustness testing, Worst-case testing, Special value testing, Examples, Random Testing, Guidelines for Boundary value testing. [Text book 1] 10hrs

UNIT II The Equivalence Class Testing, Decision Table-Based Testing: Equivalence classes, Equivalence test cases for the triangle problem, NextDate function, The commission problem, Guidelines and observations. Decision tables, Test cases for the triangle problem NextDate function, The commission problem, Guidelines and observations.[Textbook1] 12hrs

UNIT III Path Testing, Data flow testing: DD paths, Test coverage metrics, Basis path testing, guidelines and observations. Definition-Use testing, Define/Use Testing, Examples, du-Paths for Stocks, Locks, du-Paths, Sales, Commission problem, Test coverage Metrics, Slice-based testing, Guidelines and observations. [Text book 1] Levels of testing: The Need for Levels of Testing, Unit Test, Unit Test Planning, Designing the Unit Tests. The Class as a Testable Unit, Running the Unit tests and Recording results, Integration tests, Designing Integration Tests, Integration Test Planning, System Test–The Different Types, Regression Testing, Alpha, Beta and Acceptance Tests.[Text book 2] 12hrs UNIT IV Test goals, Policies, Plans, and Documentation: Introductory Concepts, Testing and Debugging Goals and Policies, Test Planning, Test Plan Components, Test Plan Attachments,Test Design Specifications, Test Case Specifications, Test Procedure Specifications, Locating Test Items: The Test Transmittal Report, Reporting Test Results, The Role of the Three Critical Groups in Test Planning and Policy Development.[Text book 2] 10hrs

Department of Information Science & Engg., 11 Applicable for the academic year 2020-21 Batch: 2017

UNIT V Defect analysis and prevention: Processes and Defects, History of Defect Analysis and Prevention, Necessary Support for a Defect Prevention Program, Techniques for Defect Analysis, Defect Causal Analysis, The Action Team: Making Process Changes, Monitoring Actions and Process Changes, Benefits of a Defect Prevention Program, Defect Prevention and the Three Critical Views. [Text book 2] 8 Hrs.

TEXT BOOK: 1.Paul C. Jorgensen: Software Testing, A Craftsman’s Approach, 3rd Edition, Auerbach Publications, 2008. 2. Ilene Burnstein, Practical software testing, Springer international edition.

REFERENCES: 1. Boris Beizer, software system testing and quality assurance, Vannostrand reinhold, New york . 2. Gordon schulmeyer, Zero defect software, McGraw hill book. 3. Watts Humphrey, Managing the software process, Addison Wesel, pub .co.inc .

NETWORK LABORATORY Lab Hours/ Week : 3 Credits : 1.5 Sub. Code : 7ISL1 CIE Marks : 50 SEE Marks : 50 Course Outcomes: Upon completion of this course the student will be able to:

CO1: Analyse the data from a live network or from captured file disk using a network protocol analyser. CO2: Analyze the behavior of network/protocols under different conditions using a network simulator. CO3: Develop and analyze the code for network algorithms using any programing languages. CO4: Develop Client server program using socket and FIFO files. CO5: Demonstrate network utilities to diagnose TCP/IP problems or to find the information.

Part – A

The Following experiments are conducted using NS.

Department of Information Science & Engg., 12 Applicable for the academic year 2020-21 Batch: 2017

1. Simulate a three nodes point to point network with duplex links between them. Set the queue size and vary the bandwidth. Determine the total number of packets dropped. 2. Simulate a network topology with the links connected as follows:

Apply TCP agent between S1-S4 and UDP between S2-S3. Apply relevant applications over TCP and UDP agents. By varying the parameters, determine the packet delivery fraction for TCP and UDP.

3. Simulate the different types of Internet traffic such as FTP and TELNET over a network. Plot and analyze the instantaneous throughput using Xgraph.

4. Simulate any topology of N nodes (6-10), change error rate and data rate and compare the throughput of the link where error is introduced.

5. Simulate a topology of n nodes and plot the congestion window (use slow start) for each source – destination pair.

6. Simulate the transmission of ping messages over a network of N nodes and find the round trip time of each ping message.

Part – B Implement the following in C++/Java 1. Using TCP/IP sockets, write a client – server program, the client sends the file name and the server sends back the content of requested text file if present.

2. Using FIFO files as IPC channel, write a client – server program, the client sends the file name and the server sends back the content of requested text file if present

3. For the given network graph, write a program to implement Distance Vector routing algorithm to build a routing table for the given node.

4. Write a program for frame sorting technique used in buffers.

Department of Information Science & Engg., 13 Applicable for the academic year 2020-21 Batch: 2017

5. Write a program for simple RSA algorithm to encrypt and decrypt the data.

6. Write a program for error detecting code using CRC-CCITT (16- bits).

Open Ended Experiment

The Following experiments are conducted using Wireshark.

1. Use Wireshark to capture packets and perform packet analysis of HTTP for the following. a. Basic HTTP GET/response interaction Send a HTTP request to the following URL http://gaia.cs.umass.edu/wireshark-labs/HTTP-wireshark-file1.html using a web browser and Answer the following questions i. Is your browser running HTTP version 1.0 or 1.1? What version of HTTP is the server running? ii. What languages (if any) does your browser indicate that it can accept to the server? iii. What is the IP address of your computer? Of the gaia.cs.umass.edu server? iv. What is the status code returned from the server to your browser? v. When was the HTML file that you are retrieving last modified at the server? vi. How many bytes of content are being returned to your browser?

b. HTTP Conditional GET/response interaction Send a HTTP request to the following URL http://gaia.cs.umass.edu/wireshark-labs/HTTP-wireshark-file2.html and Answer the following questions i. Inspect the contents of the first HTTP GET request from your browser to the server. Do you see an “IF-MODIFIED-SINCE” line in the HTTP GET? ii. Inspect the contents of the server response. Did the server explicitly return the contents of the file? How can you tell? iii. Now inspect the contents of the second HTTP GET request from your browser to the server. Do you see an “IF-MODIFIED-SINCE:” line in the HTTP GET? If so, what information follows the “IF-MODIFIED-SINCE:” header? iv. What is the HTTP status code and phrase returned from the server in response to this second HTTP GET? Did the server explicitly return the contents of the file? Explain.

c. Retrieving the long documents.

Department of Information Science & Engg., 14 Applicable for the academic year 2020-21 Batch: 2017

Use the following URL into your browser to retrieve a long document http://gaia.cs.umass.edu/wireshark-labs/HTTP-wireshark-file3.html and answer to the following. i. How many HTTP GET request messages did your browser send? Which packet number in the trace contains the GET message for the Bill or Rights? ii. Which packet number in the trace contains the status code and phrase associated with the response to the HTTP GET request? iii. What is the status code and phrase in the response? iv. How many data-containing TCP segments were needed to carry the single HTTP response and the text of the Bill of Rights?

d. HTML Documents with Embedded Objects. Use the following URL http://gaia.cs.umass.edu/wireshark-labs/HTTP- wireshark-file4.html to capture the data and answer the following questions. i. How many HTTP GET request messages did your browser send? To which Internet addresses were these GET requests sent? ii. Can you tell whether your browser downloaded the two images serially, or whether they were downloaded from the two web sites in parallel?

e. HTTP Authentication Capture the data for the following URL http://gaia.cs.umass.edu/wireshark-labs/protected_pages/HTTP- wireshark-file5.html and use the following data, username (wireshark- students) and password (network) while capturing and answer the following i. What is the server’s response (status code and phrase) in response to the initial HTTP GET message from your browser? ii. When your browser’s sends the HTTP GET message for the second time, what new field is included in the HTTP GET message?

2. Use Wireshark to capture DNS packets and perform packet analysis of DNS by making use of nslookup command. a. With your browser, visit the Web page: http://www.google.comand answer the following questions i. Locate the DNS query and response messages. Are then sent over UDP or TCP? ii. What is the destination port for the DNS query message? What is the source port of DNS response message? iii. To what IP address is the DNS query message sent? Use nm-tool to determine the IP address of your local DNS server. Are these two IP addresses the same? iv. Examine the DNS query message. What “Type” of DNS query is it? Does the query message contain any “answers”? v. Examine the DNS response message. How many “answers” are provided? What do each of these answers contain?

Department of Information Science & Engg., 15 Applicable for the academic year 2020-21 Batch: 2017

b. Do an nslookup on www.google.com and answer the following questions i. What is the destination port for the DNS query message? What is the source port of DNS response message? ii. To what IP address is the DNS query message sent? Is this the IP address of your default local DNS server? iii. Examine the DNS query message. What “Type” of DNS query is it? Does the query message contain any “answers”? iv. Examine the DNS response message. How many “answers” are provided? What do each of these answers contain? c. Execute the following command “nslookup –type=NS www.google.com” to answer the following questions i. To what IP address is the DNS query message sent? Is this the IP address of your default local DNS server? ii. Examine the DNS query message. What “Type” of DNS query is it? Does the query message contain any “answers”? iii. Examine the DNS response message. What google nameservers does the response message provide? Does this response message also provide the IP addresses of the google nameservers? d. Execute the following command “nslookup www.gmail.com ns1.google.com ” and answer the following questions i. To what IP address is the DNS query message sent? Is this the IP address of your default local DNS server? If not, what does the IP address correspond to? ii. Examine the DNS query message. What “Type” of DNS query is it? Does the query message contain any “answers”? iii. Examine the DNS response message. How many “answers” are provided? What does each of these answers contain?

3. a. Use Wireshark to perform packet analysis of TCP. Capture a bulk TCP transfer from your computer to a remote server. Do the following. 1. Start up your web browser. Go to the http://gaia.cs.umass.edu/wireshark-labs/alice.txt and retrieve an ASCII copy of Alice in Wonderland. Store this file somewhere on your computer. 2. Next go to http://gaia.cs.umass.edu/wireshark-labs/TCP- wireshark-file1.html. 3. Next Upload the alice.txtfile to capture the data. Answer the following queries i. What is the IP address and TCP port number used by the client computer (source) that is transferring the file to gaia.cs.umass.edu?

Department of Information Science & Engg., 16 Applicable for the academic year 2020-21 Batch: 2017

ii. What is the IP address of gaia.cs.umass.edu? On what port number is it sending and receiving TCP segments for this connection? iii. What is the sequence number of the TCP SYN segment that is used to initiate the TCP connection between the client computer and gaia.cs.umass.edu? What is it in the segment that identifies the segment as a SYN segment? iv. What is the sequence number of the SYNACK segment sent by gaia.cs.umass.edu to the client computer in reply to the SYN? What is the value of the Acknowledgement field in the SYNACK segment? How did gaia.cs.umass.edu determine that value? What is it in the segment that identifies the segment as a SYNACK segment? v. What is the sequence number of the TCP segment containing the HTTP POST command? vi. Consider the TCP segment containing the HTTP POST as the first segment in the TCP connection. What are the sequence numbers of the first six segments in the TCP connection (including the segment containing the HTTP POST)? At what time was each segment sent? When was the ACK for each segment received? Given the difference between when each TCP segment was sent, and when its acknowledgement was received, what is the RTT value for each of the six segments? vii. What is the length of each of the first six TCP segments? viii. What is the minimum amount of available buffer space advertised at the received for the entire trace? Does the lack of receiver buffer space ever throttle the sender? ix. Are there any retransmitted segments in the trace file? What did you check for (in the trace) in order to answer this question? x. What is the throughput (bytes transferred per unit time) for the TCP connection? Explain how you calculated this value.

b. Use Wireshark to perform packet analysis of UDP and answer the following. i. Select one UDP packet from your trace. From this packet, determine how many fields are there in the UDP header. Name these fields. ii. By consulting the displayed information in Wireshark’s packet content field for this packet, determine the length (in bytes) of each of the UDP header fields. iii. The value in the Length field is the length of what? iv. What is the maximum number of bytes that can be included in a UDP payload? v. What is the largest possible source port number? vi. What is the protocol number for UDP? Give your answer in both hexadecimal and decimal notation.

Department of Information Science & Engg., 17 Applicable for the academic year 2020-21 Batch: 2017

vii. Examine a pair of UDP packets in which your host sends the first UDP packet and the second UDP packet is a reply to this first UDP packet. Describe the relationship between the port numbers in the two packets.

4. Use Wireshark to capture an IP packet and analyze the header and payload of IP packet. Sending a request to gaia.cs.umass.edu using traceroute command and set three different packet sizes : say 56bytes, 2000bytes and 3500bytes respectively to capture the same. a. IP basics Answer the following Questions i. Select the first ICMP Echo Request message sent by your computer, and expand the Internet Protocol part of the packet in the packet details window. What is the IP address of your computer? ii. Within the IP packet header, what is the value in the upper layer protocol field? iii. How many bytes are in the IP header? How many bytes are in the payload of the IP datagram? Explain how you determined the number of payload bytes. iv. Has this IP datagram been fragmented? Explain how you determined whether or not the datagram has been fragmented. v. Which fields in the IP datagram always change from one datagram to the next within this series of ICMP messages sent by your computer? vi. Which fields stay constant? Which of the fields must stay constant? Which fields must change? Why?

b. Fragmentation Sort the packet listing according to time again by clicking on the Time column. Answer the following Questions. 1. Find the first ICMP Echo Request message that was sent by your computer after you changed the Packet Size to be 2000. Has that message been fragmented across more than one IP datagram? 2. Print out the first fragment of the fragmented IP datagram. What information in the IP header indicates that the datagram been fragmented? What information in the IP header indicates whether this is the first fragment versus a latter fragment? How long is this IP datagram? 3. Print out the second fragment of the fragmented IP datagram. What information in the IP header indicates that this is not the first datagram fragment? Are the more fragments? How can you tell? 4. What fields change in the IP header between the first and second fragment?

Now find the first ICMP Echo Request message that was sent by your computer after you changed the Packet Size to be 3500.

Department of Information Science & Engg., 18 Applicable for the academic year 2020-21 Batch: 2017

5. How many fragments were created from the original datagram? 6. What fields change in the IP header among the fragments?

Note: 1. Two experiments to be executed in the exam based on lots. 2. One experiment is from Part B and another experiment can be from Part A. 3. One experiment each from Part A and Part B is Compulsory.

References: 1. Computer Networking: A Top-Down Approach by James F. Kurose, Keith W. Ross, Sams Teach Yourself Series (6th Edition) 2012. 2. www.wireshark.org/ 3. www.isi.edu/nsnam/ns/ 4. Computer Networks: A Systems Approach, Larry L Peterson and Bruce S Davie 5th Edition, Elsevier, 2011 5. Advanced Programming in the Unix Environment by W. Richard Stevens, Stephen A. Rago Addison-Wesley, 2008

SOFTWARE TESTING LABORATORY Lab Hours/ Week : 3 Credits : 1.5 Sub. Code : 7ISL2 CIE Marks : 50 SEE Marks : 50

Course Outcomes: Upon completion of this course the student will be able to: CO1: Design, Develop and implement a program for a given problem. CO2: Apply software testing methods to design and implement test cases and analyse the behaviour of test cases under real time environment. CO3: Apply tools like Selenium, Eclipse to automate the given real time problem.

PART A: 1. Design and develop a program in a language of your choice to solve the triangle problem defined as follows: Accept three integers which are supposed to be the three sides of a triangle and determine if the three values represent an equilateral triangle, isosceles triangle, scalene triangle, or they do not form a triangle at all. Assume that the upper limit for the size of any side is 10. Derive test cases for your program based on boundary-value analysis, execute the test cases and discuss the results. Test Data : Enter the 3 Integer Value( a , b And c ) Pre-condition : 1 ≤ a ≤ 10 , 1 ≤ b ≤ 10 and 1 ≤ c ≤ 10 and a < b + c , b < a + c and c < a + b

Department of Information Science & Engg., 19 Applicable for the academic year 2020-21 Batch: 2017

2. Design and develop a program in a language of your choice to solve the triangle problem defined as follows: Accept three integers which are supposed to be the three sides of a triangle and determine if the three values represent an equilateral triangle, isosceles triangle, scalene triangle, or they do not form a triangle at all. Assume that the upper limit for the size of any side is 10. Derive test cases for your program based on equivalence class partitioning, execute the test cases and discuss the results.

Test Data : Enter the 3 Integer Value( a , b And c ) Pre-condition : 1 ≤ a ≤ 10 , 1 ≤ b ≤ 10 and 1 ≤ c ≤ 10 and a < b + c , b < a + c and c < a + b

3. Design, develop and run the program in any suitable programming language to implement the NextDate function. Analyze it from the perspective of Equivalence partition testing, derive different test cases, execute these test cases and discuss the test results. Test data : Enter three integer Pre-condition : Month 1 to 12 , DAY 1 TO 31 AND YEAR 1812 TO 2014

4. Design, develop and run the program in any suitable programming language to solve the commission problem. Analyze it from the perspective of dataflow testing, derive different test cases, execute these test cases and discuss the test results. Test data : price Rs for lock - 45.0 , stock - 30.0 and barrel - 25.0 sales = total lock * lock price + total stock * stock price + total barrel * barrel price commission : 10% for the sales of up to Rs. 1000 , 15 % from Rs. 1001 to Rs. 1800 and 20 % for any sale excess of Rs. 1800 Pre-condition : lock = -1 to exit and 1< =lock < = 70 , 1<=stock <=80 and 1<=barrel<=90

5. Design, develop and run the program in any suitable programming language to solve the commission problem. Analyze it from the perspective of decision table-based testing, derive different test cases, execute these test cases and discuss the test results.

Test data : price Rs for lock - 45.0 , stock - 30.0 and barrel - 25.0 sales = total lock * lock price + total stock * stock price + total barrel * barrel price commission : 10% for the sales of up to Rs. 1000 , 15 % from Rs. 1001 to Rs. 1800 and 20 % for any sale excess of Rs. 1800 Pre-condition : lock = -1 to exit and 1< =lock < = 70 , 1<=stock <=80 and 1<=barrel<=90

6. Design, develop and run the program in any suitable programming language to solve the commission problem. Analyze it from the perspective of boundary value testing, derive different test cases, execute these test cases and discuss the test results. Test data : price Rs for lock - 45.0 , stock - 30.0 and barrel - 25.0 sales = total lock * lock price + total stock * stock price + total barrel * barrel price commission : 10% for the sales of up to Rs. 1000 , 15 % from Rs. 1001 to Rs. 1800 and 20 % for any sale excess of Rs. 1800 Pre-condition : lock = -1 to exit and 1< =lock < = 70 , 1<=stock <=80 and 1<=barrel<=90

Part –B

Department of Information Science & Engg., 20 Applicable for the academic year 2020-21 Batch: 2017

1) Write and test a Program to automate Gmail Login, Logout. 2) Write and test Program to calculate and testing the GCD of number using webpage. 3) Write and test a Program to update 10 student records into Spreadsheet. 4) Write and test a program to select the number of students who have scored less than 60 in any subject from the existing Spreadsheet to the new Spreadsheet. 5) Write and test a program to provide total number of objects present / available on the given path. 6)Write and Test a Program to search a 16-character license key from the provided input spreadsheet.

Note: (Input spreadsheet must contain minimum 20 input data and duplicate entry may present)

Department of Information Science & Engg., 21 Applicable for the academic year 2020-21 Batch: 2017

Department of Information Science & Engg., 22 Applicable for the academic year 2020-21 Batch: 2017

LANGUAGE PROCESSOR Contact Hours/ Week: 3L Credits: 3 Total Lecture Hours: 39 CIE Marks: 50 Sub. Code: RISE06 SEE Marks: 50

Course objectives: This course will enable students to: 1. Understand various phases of compilation. 2. Understand the usage of various compiler construction tools. 3. Construct various parsing tables by applying Top and bottom up approach. 4. Understand intermediate code generation and run-time environment.

UNIT I INTRODUCTION, LEXICAL ANALYSIS, SYNTAX ANALYSIS Compilers; Analysis of Source Program; The Phases of a Compiler; Cousins of the Compiler; The grouping of phases; Compiler-Construction tools. The Role of Lexical Analyzer; Input Buffering; Specifications of Tokens; Recognition of Tokens. SYNTAX ANALYSIS: The Role of the Parser; Context-free Grammars Writing a Grammar. 8 Hrs.

UNIT II SYNTAX ANALYSIS CONTINUED ... Top-down Parsing; Recursive descent parsing, Transition diagrams for predictive parsers, Non recursive predictive parsing, FIRST and FOLLOW, LL(1) Grammars Bottom-up Parsing, Handles, Handle pruning, Stack implementation of shift reduce parsing , viable prefix 8 Hrs.

UNIT III SYNTAX-DIRECTED TRANSLATION, RUN-TIME ENVIRONMENTS LR Parsers – LR Parsing algorithm, construction of SLR, CLR, LALR Parsing tables, Syntax-Directed definitions; Constructions of Syntax Trees; Bottom-up evaluation of S-attributed definitions; L-attributed definitions; Top-down translation. 9 Hrs.

UNIT IV INTERMEDIATE CODE GENERATION Intermediate Languages; Declarations; Assignment statements; Boolean Expressions, Type Checking, Case statements; Backpatching: Backpatching for Boolean Expressions, Flow-of-Control Statements.

Department of Information Science & Engg., 23 Applicable for the academic year 2020-21 Batch: 2017

8 Hrs.

UNIT V CODE GENERATION Issues in the design of Code Generator; The Target Machine; Run-time Storage Management; Issues in the design of Code Generator; The Target Machine; Run-time, Storage Management; A Simple Code Generator; 7 Hrs.

TEXT BOOKS 1 Alfred V Aho, Compilers-Principles, Techniques and Tools, Ravi Sethi, Addison-Wesley, 2nd Ed, 2007 Jeffrey D Ullman

REFERENCE BOOKS 1 Charles N. Crafting a Compiler with C, Pearson Education, Fischer, 1991. Richard J. leBlanc, Jr. 2 Andrew W Apple Modern Compiler Implementation in C, Cambridge University Press, 1997.

Course Outcomes: Upon completion of this course the student will be able to: CO1: Apply the acquired knowledge to illustrate the various phases of compilation and compiler construction tools. CO2: Identify the issues, specifications and recognition of tokens during lexical analysis. CO3: Design different parsing tables for the given grammar and associate the semantic rules for the productions of the grammar. CO4: Analyze the program dynamics during runtime. CO5: Analyze and Apply suitable techniques to generate the target code.

ENTERPRISE CONTENT MANAGEMENT Contact Hours/ Week: 2L+2P Credits: 3.0 Total Lecture Hours: 52 CIE Marks: 50 Sub. Code: RISE13 SEE Marks: 50

Course objectives: This course will enable students to:

Department of Information Science & Engg., 24 Applicable for the academic year 2020-21 Batch: 2017

1. Gain understanding about Digital Technology, best practices and relevant success stories of the industry. 2. Have hands on proficiency on Adobe Experience Manager - a platform for delivering, engaging, multichannel experience. 3. Create components and templates in AEM using JCR 4. Design responsive and dynamic webpages with digital asset management.

UNIT I WCM & AEM Introduction: AEM Terminology, Basic concepts. AEM Setup & Overview: Install and deploy AEM, Work with various Web Consoles, Work with User interfaces (UIs) Web Framework: Understand Representational State Transfer (REST) architectural style, Apache Sling. OSGi Framework: Understand the concepts of OSGi and Apache Sling, Describe the AEM functional building blocks, Describe the Granite platform, Understand OSGi framework, Understand about OSGi bundles

(5+5) Hrs.

UNIT II Content Repository: Basic Concepts – JCR, learn about the Java Content Repository (JCR), Understand the concepts of Apache Jackrabbit, Explore Adobe CRX, Understand the underlying repository structure. AEM – Developer UI: Content Authoring Overview, CRX Interface, CRXDE Lite Interface. AEM – Templates & Components: Creating Project Structure, Introduction to Sightly, Creating Template & Page Component (JSP and Sightly), Creating Pages & Website Structure. (5+5) Hrs.

UNIT II Sightly: Features of Sightly in AEM Development, Sightly versus JSP, Building Blocks, Expressions & Statements. AEM Authoring Framework – Components & Design: Modularize the template, Extend the component hierarchy, assign a design, Create and include components in scripts. AEM Authoring Framework – Dialog Boxes: Create dialog boxes for components, Create Design dialog boxes for global content, Use the Edit_Config property to enhance components. (5+5) Hrs.

UNIT IV

Department of Information Science & Engg., 25 Applicable for the academic year 2020-21 Batch: 2017

Authoring Responsive and Mobile Pages: Define Responsive Design Work with Responsive page layout, create a Mobile page, Add content to the Mobile page. DAM: Finding & Viewing Assets, create a folder and upload assets to it, edit an asset and its properties, Add a content fragment and an asset to a page. Adding New Content: Create a page, insert a new paragraph, Edit the text paragraph, Add new components, Work with the Content Finder. Handling Page Properties: Describe Page Properties, Provide Multiple titles for a Page, Bulk Editing. (6+6) Hrs.

UNIT V Workflows: Creating and Managing Workflows, Creating and Managing Launches. Admin Basics: Roles, Users, Groups and Permissions (ACLs), Apache Felix Console Interface, Package Manager. Agile Basics: Agile Basics for AEM Projects. (5+5) Hrs.

TEXT BOOKS 1 Ryan D Lunka Adobe Experience Manager: Classroom in a book, Adobe Press, 2014

REFERENCE BOOKS 1 Shane closer Adobe Experience Manager: Quick reference guide, Adobe Press, 2014. 2 Shivanikarwal Digital Marketing Handbook, Create Space Independent Publishing Platform, 2015

Course Outcomes: Upon completion of this course the student will be able to: CO1: Understand the knowledge of digital touch points to provide unified experience CO2: Develop templates on AEM by applying the knowledge of JCR and Apache Jackrabbit CO3: Create dialog boxes and components using Sightly language CO4: Design the responsive pages, mobile pages, folders and manipulation on AEM framework CO5: Create and manage AEM workflows.

Department of Information Science & Engg., 26 Applicable for the academic year 2020-21 Batch: 2017

STORAGE TECHNOLOGY Contact Hours/ Week: 3L Credits: 3 Total Lecture Hours: 39 CIE Marks: 50 Sub. Code: RISE15 SEE Marks: 50

Course objectives: This course will enable students to: 1. Understand different storage centric and server centric IT infrastructures. 2. Compare different network storage options in multiple platforms. 3. Define information security and identify different storage virtualization technologies. 4. Identify security considerations to be taken across different storage network devices. 5. Understand the Sensor management, power management, and sensor network middleware.

UNIT I

Introduction: Server Centric IT Architecture and its Limitations; Storage – Centric IT Architecture and its advantages; Case study: Replacing a server with Storage Networks. Intelligent Disk Subsystems- 1: Architecture of Intelligent Disk Subsystems; Hard disks and Internal I/O Channels, JBOD, Storage virtualization using RAID and different RAID levels. Caching: Acceleration of Hard Disk Access

8 Hrs.

UNIT II Intelligent Disk Subsystems -2, I/O Techniques - 1: Intelligent disk subsystems; Availability of disk subsystems. The Physical I/O path from the CPU to the Storage System; SCSI.

I/O Techniques -2 NETWORK ATTACHED STORAGE: Fibre Channel Protocol Stack; Fibre Channel SAN; IP Storage. 8 Hrs.

UNIT III File System and NAS: Local File Systems; Network file Systems and file servers; Shared disk file systems; Comparison of fibre Channel and NAS.

Department of Information Science & Engg., 27 Applicable for the academic year 2020-21 Batch: 2017

Storage Virtualization-1: Once again virtualization in the I/O path, Limitations and requirements 8Hrs.

UNIT IV Storage Virtualization-2 Definition of Storage virtualization; Implementation Considerations; Storage virtualization on Block or file level; Storage virtualization on various levels of the storage Network; Symmetric and Asymmetric storage virtualization in the Network

8 Hrs.

UNIT V Security Considerations-Overview of Information Security, Security Methods, StorageSecurity Technology, Storage Security Challenges, Fiber Channel SAN Security, NAS Security.

7 Hrs.

TEXT BOOKS 1 Ulf Troppens, Storage Networks Explained – John Wiley & Sons, Rainer Erkens 2nd Edition, 2011. and Wolfgang Muller 2 Robert Spalding Storage Networks: The Complete Reference-Tata McGraw Hill Publications,2003 (ISBN:0072224762)

REFERENCE BOOKS 1 Richard Barker, Storage Area Network Essentials: A Complete Paul Massiglia, Guide to understanding and Implementing SANs and John – Wiley India, 2002. 2 Marc Farley Storage Networking Fundamentals, Cisco Press, 2005

Course Outcomes: Upon completion of this course the student will be able to: CO1: Discuss the fundamental requirements of the file systems. CO2: Comprehend storage area network architectures. CO3: Deliberate different RAID levels, SAN and NAS technologies.

Department of Information Science & Engg., 28 Applicable for the academic year 2020-21 Batch: 2017

CO4: Identify and adopt different storage virtualization techniques. CO5: Analyze security elements to address solutions across different storage network.

ARTIFICIAL NEURAL NETWORKS AND DEEP LEARNING Contact Hours/ Week: 3 Credits: 3 Total Lecture Hours: 39 CIE Marks: 50 Sub. Code: RISE20 SEE Marks: 50

Course objectives: This course will enable students to: 1. Understand the evolution of artificial neural networks. 2. Use & comprehend different models of ANN to solve the problems. 3. Understand the philosophy and working of Deep Forward Neural Networks. 4. Discuss the salient features and benefits of Associative Neural Networks. 5. Acquire the knowledge of the significance of Competitive and SOFM nets.

UNIT I INTRODUCTION TO NEURAL NETWORKS: Neural Processing, Overview of Neural Networks, The rise of neurocomputing, Definition of Neural Network, Introduction to Neural Networks, Historical Developments of Neural Networks, Biological Neural Networks, Comparison between the Brain and the computer, Comparison between Artificial and Biological Neural Networks, Basic Building Blocks of Artificial Neural Network. (Chapter 1, Text Book 1) 7 Hrs.

UNIT II FUNDAMENTAL MODELS OF ANN: McCulloch-Pitts Neuron Mode: Learning Rules: Hebbian Learning Rule, Perceptron Learning Rule, Delta Learning Rule, Competitive Learning Rule, Outstar Learning Rule, Boltzmann Learning Rule, Hebbian Network, Perceptron Networks: Architecture, Algorithm and Application Procedure, Adaline and Madaline Networks: FEED FORWARD NETWORKS Structure, Delta rule, generalized Delta Rule, Architecture, Training extensions, Practical considerations, Generalization, Prunning Techniques, advantages and disadvantages, applications. (Reference 9 Hrs.

UNIT III

Department of Information Science & Engg., 29 Applicable for the academic year 2020-21 Batch: 2017

DEEP FORWARD NEURAL NETWORKS Definition of Deep Forward Neural Networks, Brief Survey on Deep Neural Networks, Advantages and Disadvantages of Deep Neural Network, Applications of Deep Neural Networks, Deep Neural Network Architecture, Learning in Deep forward Neural Networks. (Chapter No.1 and Chapter No. 3 of Text Book 2) 8 Hrs.

UNIT IV ASSOCIATIVE MEMORY NEURAL NETWORKS Introduction, Algorithms for Pattern Associations, Hetero Associative Memory Neural Networks, Auto Associative Memory Neural Networks, Bi-Directional Associative Memory Neural Networks (Chapter 6, Text Book 1) 8 Hrs.

UNIT V COMPETITIVE AND SELF ORGNIZING NETWORKS Introduction: general clustering procedures, competitive learning architectures and algorithms, self organizing feature maps(Chapter 9, Text Book 1) 10 Hrs.

TEXT BOOKS 1 S.N.Shivanadam, Introduction to Neural Networks using MATLAB S Sumathi, S N 6.0, Second Reprint 2006, ISBN:0-07-059112-1, Deepa TMH Publishing House, New Delhi. 2 Dr. Rajiv Chopra Deep Learning-A Practical Approach using Python. Second Edition, ISBN:978-93-86173-41-6, Khanna Publisher, 2020.

REFERENCE BOOKS 1 James A. Freeman Neural Networks: Algorithms, Applications and and David M. Programming Techniques, ISBN 13: Skupura 9780201513769, Pearson Education Publications, 2003. 2 Dr. Shivanandam Principles of Soft Computing, Third Edition, Wiley and Deepa Publication, 2019. ISBN: 978-81-265-7713-2. 3 Robert J Schalkoff Artificial Neural Networks, Mc Graw Hill, International Edition ISBN-13: 978-0262019309, 1997. 4 B. Yegnanarayana Artificial Neural Networks, PHI 1999.

Department of Information Science & Engg., 30 Applicable for the academic year 2020-21 Batch: 2017

Course Outcomes: Upon completion of this course the student will be able to: CO1: Apply the fundamental concepts of ANN CO2: Analyze and apply the different ANN models to solve the real world problem. CO3: Discuss the fundamental issues with Deep Neural Networks. CO4: Analyze and Apply training and testing algorithms to Associative NN. CO5: Explore the salient features and significance of Competitive and SOFM nets.

BIG DATA AND ANALYTICS Contact Hours/ Week: 3 Credits: 3 Total Lecture Hours: 39 CIE Marks: 50 Sub. Code: RISE23 SEE Marks: 50

Course objectives: This course will enable students to: 1. Understand the concepts of data, classification of data and its importance. 2. Gain the knowledge about Hadoop Ecosystem and how Map Reduce helps in concurrent processing of data. 3. Practise the usage of hive and pig scripts across Hadoop database for data manipulation. 4. Understand how Oozie schedules Hadoop jobs 5. Compare NoSQL database and SQL database.

UNIT I Getting an Overview of Big Data: What is Big Data? History of Data Management-Evolution of Big Data, Structuring Big Data-Types of Data, Elements of Data, Advantages of Big Data Analytics Introducing Technologies for Handling Big Data Distributed and Parallel Computing for Big Data, Introducing Hadoop, Cloud Computing and Big Data: Features of Cloud Computing, Cloud Deployment Models, Cloud Delivery Models, Cloud Services for Big Data, Cloud Providers in Big Data Market, In-Memory Computing Technology for Big Data. 8 Hrs.

UNIT II Understanding Hadoop Ecosystem

Department of Information Science & Engg., 31 Applicable for the academic year 2020-21 Batch: 2017

Hadoop Ecosystem, Hadoop Distributed File System, HDFS Architecture, MapReduce, Hadoop YARN, Introducing HBase- HBase Architecture, Regions, Storing Big Data with HBase, Interacting with the Hadoop Ecosystem, HBase in Operation-Programming with HBase, Combining HBase with HDFS, Hive, Pig and Pig Latin, Sqoop, ZooKeeper, Flume, Oozie Understanding MapReduce Fundamentals and HBase The MapReduce Framework: Exploring the features of MapReduce, working of MapReduce, Exploring Map and Reduce Functions, Techniques to optimize MapReduce Jobs: Hardware/ Network Topology, Synchronization, File System, Uses of MapReduce, Role of HBase in Big Data Processing: Characteristics of HBase, Installation of HBase. 8 Hrs.

UNIT III Exploring Hive Introducing Hive, Getting Started with Hive: Hive Variables, Hive Properties, Hive Queries, Data Types in Hive, Built-in Functions inHive, Hive DDL, Data Manipulation in Hive, Data Retrieval Queries, Using JOINS in Hive. Analyzing Data with Pig Introducing Pig: The Pig Architecture, Benefits of Pig, Properties of Pig, Running Pig, Getting Started with Pig Latin, Working with Operators in Pig, Debugging Pig, Working with Functions in Pig, Error Handling in Pig. 8 Hrs.

UNIT IV Using Oozie Introducing Oozie: Main Functional Components of Oozie, Benefits of Oozie, Installing and Configuring Oozie, Understanding the Oozie Workflow, Oozie Coordinator, Oozie Bundle, Oozie Parameterization with EL, Oozie Job Execution Model, Accessing Oozie, Oozie SLA. NoSQL Data Management Introducing to NoSQL, Types of NoSQL Data Models, Characteristics of NoSQL, Schema-less Databases, Materialized Views, Distribution Models, CAP theorem, Sharding 7 Hrs.

UNIT V MongoDB What is MongoDB? Why MongoDB? Terms Used in RDBMS and MongoDB, Data Types in MongoDB, MongoDB Query Language

Department of Information Science & Engg., 32 Applicable for the academic year 2020-21 Batch: 2017

Cassandra Apache Cassandra - An Introduction, Features of Cassandra, CQL Data types, CQLSH, Keyspaces, CRUD (Create, Read, Update and Delete) Operations, Collections, Using a Counter, Time to Live (TTL), Alter Commands, Import and Export, Querying System Tables, Practice Examples 10 Hrs.

TEXT BOOKS 1 DT Editorial Big Data: Black Book: Dreamtech Press, Edition Services 2016 (Chapters 1,3,4,5,12,13,14,15) 2 Seema Acharya, Big Data and Analytics, Infosys Limited, Subhashini Publication: Wiley India Private Limited,1st Edition Chellappan 2015(Chapters 6,7)

REFERENCE BOOKS 1 Alex Holmes Hadoop in Practice, Manning Publications Co., Second Edition, September 2014 2 Alan Gates Programming Pig, O’Reilly, Kindle Publication, 2016 3 Dean Wampler Programming Hive, O’Reilly, Kindle Publication, September 2012 ISBN 9781449319335

Course Outcomes: Upon completion of this course the student will be able to: CO1: Identify the different types of digital data, sources, challenges, elements and technologies for handling Big Data CO2: Demonstrate the Hadoop Ecosystem and have broad comprehension of HDFS, MapReduce Fundamentals and HBase CO3: Apply Pig and Hive scripts with Hadoop Distributed File System to analyse stored Big Data. CO4: Describe managing Hadoop jobs using Oozie and basic concepts of NoSQL Data Management. CO5: Create NoSQL Databases and explore Mongo DB and Cassandra

NATURAL LANGUAGE PROCESSING WITH PYTHON Contact Hours/ Week: 3L Credits: 3 Total Lecture Hours: 39 CIE Marks: 50 Sub. Code: RISE35 SEE Marks: 50

Course objectives:

Department of Information Science & Engg., 33 Applicable for the academic year 2020-21 Batch: 2017

This course will enable students to: 1. Understand the trends and systems in natural language processing. 2. Understand the concepts of morphology, syntax, semantics and pragmatics of the language. 3. Recognize the significance of pragmatics for natural language understanding 4. Classify and extracting the meaning of the text.

UNIT I Language Processing and Python Computing with Language: Texts and Words, A Closer Look at Python: Texts as Lists of Words, Computing with Language: Simple Statistics, Back to Python: Making Decisions and Taking Control, Automatic Natural Language Understanding Accessing Text Corpora and Lexical Resources Accessing Text Corpora, Conditional Frequency Distributions, More Python: Reusing Code, Lexical Resources, WordNet 8Hrs

UNIT II Processing Raw Text Accessing Text from the Web and from Disk, Strings: Text Processing at the Lowest Level, Text Processing with Unicode, Regular Expressions for Detecting Word Patterns, Useful Applications of Regular Expressions, Normalizing Text, Regular Expressions for Tokenizing Text, Segmentation, Formatting: From Lists to Strings Writing Structured Programs Back to the Basics, Sequences, Questions of Style, Functions: The Foundation of Structured Programming, Doing More with Functions, Program Development, Algorithm Design, A Sample of Python Libraries. 8 Hrs.

UNIT III Categorizing and Tagging Words Using a Tagger, Tagged Corpora, Mapping Words to Properties Using Python Dictionaries, Automatic Tagging, N-Gram Tagging, Transformation-Based Tagging, How to Determine the Category of a Word Learning to Classify Text Supervised Classification, Further Examples of Supervised Classification Evaluation, Decision Trees, Naive Bayes Classifiers, Maximum Entropy Classifiers, Modeling Linguistic Patterns Extracting Information from Text

Department of Information Science & Engg., 34 Applicable for the academic year 2020-21 Batch: 2017

Information Extraction, Chunking, Developing and Evaluating Chunkers, Recursion in Linguistic Structure, Named Entity Recognition, Relation Extraction 9Hrs

UNIT IV Analyzing Sentence Structure Some Grammatical Dilemmas, What’s the Use of Syntax?, Context-Free Grammar, Parsing with Context-Free Grammar, Dependencies and Dependency Grammar, Grammar Development Building Feature-Based Grammars Grammatical Features, Processing Feature Structures, Extending a Feature-Based Grammar. 07 Hrs

UNIT V Analyzing the Meaning of Sentences Natural Language Understanding, Propositional Logic, First-Order Logic, The Semantics of English Sentences, Discourse Semantics Managing Linguistic Data Corpus Structure: A Case Study, The Life Cycle of a Corpus, Acquiring Data, Working with XML, Working with Toolbox Data, Describing Language Resources using OLAC Metadata. 07 Hrs

TEXT BOOKS 1 Steven Bird, Ewan Natural Language Processing with Python, 1st Klein, and Edward Edition, O’Reilly Media, 2009 Loper

REFERENCE BOOKS 1 Hardeniya, Nitin Natural Language Processing: Python and NLTK, Packt, 2016

Course Outcomes: Upon completion of this course the student will be able to: CO1: Comprehend the basic concepts of language processing and tool kit. CO2: Apply corpora and lexical resources to access the text.

Department of Information Science & Engg., 35 Applicable for the academic year 2020-21 Batch: 2017

CO3: Determine the category of a word using tagging and classification. CO4: Analyze the meaning of the sentences using different logic. CO5: Identify the information from the given text.

SENSORS AND INTERNET OF THINGS Contact Hours/ Week: 3 Credits: 3 Total Lecture Hours: 39 CIE Marks: 50 Sub. Code: RISE36 SEE Marks: 50

Course objectives: This course will enable students to: 1. Understand concepts and principles of different sensors. 2. Discuss the fundamental concepts of IoT. 3. Familiarize with the design methodology and research directions. 4. Use Python to IoT domain. 5. Discuss different IoT Physical Devices and End points.

UNIT I Introduction: Definition of a transducer, Block Diagram, Active and Passive Transducers, Advantages of Electrical transducers. Resistive Transducers: Potentiometers: Characteristics, Loading effect, and problems. Strain gauge: Theory, Types, applications and problems. Thermistor, RTD: Theory, Applications and Problems. 07 Hrs.

UNIT II Fundamentals Of IOT: Introduction, Physical design of IoT, Logical design of IoT, IoT Enabling technologies, IoT Levels and Deployment Templates, IoTvs M2M. 08 Hrs.

UNIT III IOT Design Methodology: Need for IoT systems management, IoT Design Methodology Internet of Things Strategic Research and Innovation Agenda: Internet of Things Vision, IoT Strategic Research and Innovation Directions, IoT Smart-X Applications, Internet of Things and Related Future Internet Technologies. 08 Hrs.

UNIT IV IOT Systems: Logical Design using Python: Provides an introduction to Python, installing Python, Python data types & data structures, control flow, functions, modules, packages, file input/output, data/time operations and classes.

Department of Information Science & Engg., 36 Applicable for the academic year 2020-21 Batch: 2017

08 Hrs.

UNIT V IOT Physical Devices & Endpoints: What is an IoT device, Raspberry Pi device, About the board, Linux on Raspberry Pi, Raspberry Pi interfaces, Programming Raspberry Pi with Python 08 Hrs.

TEXT BOOKS 1 Vijay Madisetti Internet of Things (A Hands-on-Approach), 1st & Arshdeep Edition, VPT, 2014, ISBN-13: 978-0996025515. Bahga 2 A.K. Sawhney Electrical and Electronic Measurements and Instrumentation, 18th Edition, 2008, Dhanpat Rai and Sons, ISBN: 81-7700-016-0.

REFERENCE BOOKS 1 Ovidiu Vermesan, Internet of Things – From Research and Peter Friess, Innovation to Market Deployment, River Publishers Series in Communication, River Publishers, 2014, ISBN: 978-87-93102-94-1 (Hard copy), 978-87-93102-95-8 (Ebook) (UnitsII 2nd part). 2 Clarence W.de Sensor systems: Fundamentals and applications, Silva 2016 Edition, CRC Press, ISBN: 9781498716246.

Course Outcomes: Upon completion of this course the student will be able to: CO1: Comprehend concepts, principles and applications of different sensors CO2: Apply the fundamental concepts of IoT. CO3: Discuss the design methodology and research directions. CO4: Apply Python to IoT domain. CO5: Discuss different IoT Physical Devices and End Points.

AGILE SOFTWARE TECHNOLOGY Contact Hours/ Week: 3L Credits: 3 Total Lecture Hours: 39 CIE Marks: 50 Sub. Code: RISE37 SEE Marks: 50

Course objectives:

Department of Information Science & Engg., 37 Applicable for the academic year 2020-21 Batch: 2017

This course will enable students to: 1. Understand traditional testing activities versus agile methodologies. 2. Apply agile development practices, design achieve agility. 3. Understand roles and responsibilities of scrum master and product owner. 4. Understand testing activities within an Agile project development.

UNIT I Introduction What Is Agile Testing, Anyway? Agile Values What Do We Mean by “Agile Testing”? A Little Context for Roles and Activities on an Agile Team, How Is Agile Testing Different, Whole-Team Approach.

Ten Principles for Agile Testers What’s an Agile Tester? The Agile Testing Mind-Set x CONTENTS, Applying Agile Principles and Values, Adding value.

7 Hrs.

UNIT II Organizational Challenges Cultural Challenges, Organizational Culture, Barriers to Successful Agile Adoption by Test/QA Teams, Introducing Change, Management Expectations, Change Doesn’t Come Easy. Transitioning Typical Processes Seeking Lightweight Processes, Metrics, Defect Tracking, Test Planning, Existing Processes and Models. The Agile Testing Quadrants The Agile Testing Quadrants, Knowing When a Story Is Done, Managing Technical Debt, Testing in Context. 8 Hrs.

UNIT III Technology-Facing Tests that Support the Team An Agile Testing Foundation, Why Write and Execute These Tests?, Where Do Technology-Facing Tests Stop?, What If the Team Doesn’t Do These Tests?, Toolkit. Business-Facing Tests that Support the Team Driving Development with Business-Facing Tests, The Requirements Quandary, Thin Slices, Small Chunks, How Do We Know We’re Done?, Tests Mitigate Risk, Testability and Automation. 8Hrs.

Department of Information Science & Engg., 38 Applicable for the academic year 2020-21 Batch: 2017

UNIT IV Backdrop: The Science of Scrum Empirical Process Control , Complex Software Development , The Skeleton and Heart of Scrum , Scrum Roles , Scrum Flow , Scrum Artifacts New Management Responsibilities The ScrumMaster at MetaEco, The Product Owner at MegaEnergy, The Team at Service1st The ScrumMaster The Untrained ScrumMaster at Trey Research, The Untrained ScrumMaster at Litware, Overzealous at Contoso.com, Wolves at MegaFund 8 Hrs.

UNIT V The Product Owner Customer and Team Collaboration, Getting Service1st’s Management Back in Action, Fixing the Problem of XFlow at MegaFund, Company Goals at TechCore, Company Goals at MegaBank Funds Transfer System Planning a Scrum Project Managing Cash at MegaBank Project Reporting—Keeping Everything Visible New Project Reporting at the MegaEnergy Title Project,Getting More Information at MegaBank Scaling Projects Using Scrum Scaling at MegaFund, Scrum Scaling, Scaling at Medcinsoft 8 Hrs.

TEXT BOOKS 1 Lisa Crispin, Janet Agile Testing: Practical guide for Testers and Agile Gregory team, Copyright © 2009 Pearson Education, Inc. ISBN-13: 978-0-321-53446-0 2 Ken Schawber, Agile Software Development with Scrum. Pearson Mike Beedle Publication, ISBN 0-7356-1993-X

REFERENCE BOOKS 1 Robert C. Martin Agile Software Development, Principles, Patterns, and Practices, Prentice Hall; 1st edition, 2002.

Department of Information Science & Engg., 39 Applicable for the academic year 2020-21 Batch: 2017

2 Craig Larman “Agile and Iterative Development A Manger’s Guide”, Pearson Education, First Edition, India, 2004.

Course Outcomes: Upon completion of this course the student will be able to: CO1: Analyze the various principles of agile Testers and purpose of agile testing. CO2: Explain various Organizational Challenges and Agile Testing Quadrants. CO3: Interpret the business values of adopting agile development. CO4: Apply the role of the scrum master in handling the real time projects. CO5: Apply scrum for the Scaling the Projects and planning.

WEB TECHNOLOGY Contact Hours/ Week: 3L Credits: 3 Total Lecture Hours: 39 CIE Marks: 50 Sub. Code: RISE38 SEE Marks: 50

Course objectives: This course will enable students to: 1. Acquire knowledge and skills for creation of web site considering both client and server-side programming. 2. Gain ability to develop responsive web applications. 3. Acquire skills to validate and handle errors using PHP. 4. Create web services using XML, JSON and PHP. 5. Acquire knowledge and skills for creation of web site considering both client and server-side programming.

UNIT I Introduction to HTML: What is HTML and Where did it come from? HTML Syntax, Semantic Markup, Structure of HTML Documents, Quick Tour of HTML Elements, HTML5 Semantic Structure Elements. HTML Tables and Forms: Introducing Tables, Styling Tables, Introducing Forms, Form Control Elements, Table and Form Accessibility, Microformats. 8 Hrs.

UNIT II Introduction to CSS: What is CSS, CSS Syntax, Location of Styles, Selectors, The Cascade: How Styles Interact, The Box Model, CSS Text Styling.

Department of Information Science & Engg., 40 Applicable for the academic year 2020-21 Batch: 2017

Advanced CSS Layout: Normal Flow, Positioning Elements, Floating Elements, Constructing Multicolumn Layouts, Approaches to CSS Layout, Responsive Design, CSS Frameworks. 8 Hrs.

UNIT III JavaScript: Client-Side Scripting: What is JavaScript and What can it do? JavaScript Design Principles, where does JavaScript Go? Syntax, JavaScript Objects, The Document Object Model (DOM), JavaScript Events, Forms, Introduction to Server-Side Development with PHP: What is Server- Side Development, A Web Server’s Responsibilities, Quick Tour of PHP, Program Control, Functions 6Hrs.

UNIT IV PHP Arrays and Superglobals: Arrays, $_GET and $_POST Super global Arrays, $_SERVER Array, $_Files Array, Reading/Writing Files Error Handling and Validation: What are Errors and Exceptions? PHP Error Reporting, PHP Error and Exception Handling INTRODUCTION TO PHP FRAMEWORKS: What is a framework? Why frameworks? When to use Frame Work? What are the factors to be considered using frameworks? Available Open Source Frame Work: CodeIgniter 8 Hrs.

UNIT V Advanced JavaScript and jQuery: JavaScript Pseudo-Classes, jQuery Foundations, AJAX, Asynchronous File Transmission, Animation, Backbone MVC Frameworks. XML Processing and Web Services: XML Processing, JSON, Overview of Web Services, Creating and Consuming Web Services in PHP, Interacting Asynchronously with Web Services. 9 Hrs.

TEXT BOOKS 1 Randy Connolly, Fundamentals of Web Development, Pearson Ricardo Hoar Education India, 2nd Edition,2018, ISBN:978- 9332575271

REFERENCE BOOKS 1 Robin Nixon Learning PHP, MySQL &JavaScript with jQuery, CSS and

Department of Information Science & Engg., 41 Applicable for the academic year 2020-21 Batch: 2017

HTML5”, 4th Edition, O’Reilly Publications, 2015. (ISBN:978-9352130153) 2 Nicholas C Zakas, Professional JavaScript for Web Developers, 3rd Edition, Wrox/Wiley India, 2012. (ISBN:978-8126535088)

Course Outcomes: Upon completion of this course the student will be able to: CO1: Apply HTML, CSS and JavaScript to implement dynamic and responsive web pages. CO2: Integrate client side and server-side scripting languages to develop web applications. CO3: Implement validation and error handling using PHP to build efficient server-side web applications. CO4: Apply and implement JSON and XML scripts to share information across web applications. CO5: Create web services using SOAP, Rest API and develop web applications.

Department of Information Science & Engg., 42 Applicable for the academic year 2020-21 Batch: 2017

FOR OTHER PROFESSIONAL ELECTIVE SUBJECTS REFER V & VI SEMESTER SYLLABUS COPY OF BATCH 2017

Department of Information Science & Engg., 43