CS501PC: DESIGN AND ANALYSIS OF ALGORITHMS

Prerequisites:

1. A course on “Computer Programming and Data Structures”.

2. A course on “Advanced Data Structures”.

Course Objectives:  Introduces the notations for analysis of the performance of algorithms and the
data structure of disjoint sets.

 Describes major algorithmic techniques (divide-and-conquer, backtracking, dynamic programming,

greedy, branch and bound methods) and mention problems for which each technique is appropriate
 Describes how to evaluate and compare different algorithms using worst-, average-, and best case
analysis.

 Explains the difference between tractable and intractable problems, and introduces the problems
that are P, NP and NP complete.

Course Outcomes:

 Analyse the performance of algorithms

 Choose appropriate data structures and algorithm design methods for a specified application

 Understand the choice of data structures and the algorithm design methods

UNIT - I Introduction: Algorithm, Performance Analysis-Space complexity, Time complexity,

Asymptotic Notations- Big oh notation, Omega notation, Theta notation and Little oh notation. Divide
and conquer: General method, applications-Binary search, Quick sort, Merge sort, Strassen’s matrix
multiplication.

UNIT - II Disjoint Sets: Disjoint set operations, union and find algorithms, Priority Queue- Heaps,
Heapsort Backtracking: General method, applications, n-queen’s problem, sum of subsets problem,
graph Colouring, Hamiltonian cycles.

UNIT - III Dynamic Programming: General method, applications- Optimal binary search tree, 0/1
knapsack problem, All pairs shortest path problem, Traveling salesperson problem, Reliability design.

UNIT - IV Greedy method: General method, applications-Job sequencing with deadlines, knapsack
problem, Minimum cost spanning trees, Single source shortest path problem. Basic Traversal and
Search Techniques: Techniques for Binary Trees, Techniques for Graphs, Connected components,
Biconnected components.

UNIT - V Branch and Bound: General method, applications - Traveling salesperson problem, 0/1
knapsack problem - LC Branch and Bound solution, FIFO Branch and Bound solution. NP-Hard and
NP-Complete problems: Basic concepts, non-deterministic algorithms, NP-Hard and NP-Complete
classes, Cook’s theorem.

TEXT BOOK: 1. Fundamentals of Computer Algorithms, Ellis Horowitz, Satraj Sahni and Rajasekharan,
University press, 1998.

REFERENCE BOOKS: 1. Design and Analysis of algorithms, Aho, Ullman and Hopcroft, Pearson
education.
2. Introduction to Algorithms, second edition, T. H. Cormen, C.E. Leiserson, R. L. Rivest, and C. Stein,
PHI Pvt. Ltd./ Pearson Education.

3. Algorithm Design: Foundations, Analysis and Internet Examples, M.T. Goodrich and R. Tamassia,
John Wiley and sons.

CS502PC: COMPUTER NETWORKS

Prerequisites

1. A course on “Programming for problem solving”

2. A course on “Data Structures”

Course Objectives  The objective of the course is to equip the students with a general overview of
the concepts and fundamentals of computer networks.

 Familiarize the students with the standard models for the layered approach to communication
between machines in a network and the protocols of the various layers.

Course Outcomes

 Gain the knowledge of the basic computer network technology.

 Gain the knowledge of the functions of each layer in the OSI and TCP/IP reference model.

 Obtain the skills of subnetting and routing mechanisms.

 Familiarity with the essential protocols of computer networks, and how they can be applied in
network design and implementation.

UNIT - I Network hardware, Network software, OSI, TCP/IP Reference models, Example Networks:
ARPANET, Internet. Physical Layer: Guided Transmission media: twisted pairs, coaxial cable, fiber
optics, Wireless Transmission. Data link layer: Design issues, framing, Error detection and correction.

UNIT - II Elementary data link protocols: simplex protocol, A simplex stop and wait protocol for an
error-free channel, A simplex stop and wait protocol for noisy channel. Sliding Window protocols: A
one-bit sliding window protocol, A protocol using Go-Back-N, A protocol using Selective Repeat,
Example data link protocols. Medium Access sublayer: The channel allocation problem, Multiple
access protocols: ALOHA, Carrier sense multiple access protocols, collision free protocols. Wireless
LANs, Data link layer switching.

UNIT - III Network Layer: Design issues, Routing algorithms: shortest path routing, Flooding,
Hierarchical routing, Broadcast, Multicast, distance vector routing, Congestion Control Algorithms,
Quality of Service, Internetworking, The Network layer in the internet.

UNIT - IV Transport Layer: Transport Services, Elements of Transport protocols, Connection

management, TCP and UDP protocols.

UNIT - V Application Layer –Domain name system, SNMP, Electronic Mail; the World WEB, HTTP,
Streaming audio and video.

TEXT BOOK:
 1. Computer Networks -- Andrew S Tanenbaum, David. j. Wetherall, 5th Edition. Pearson
Education/PHI

REFERENCE BOOKS: 1. An Engineering Approach to Computer Networks-S. Keshav, 2nd Edition,

Pearson Education 2. Data Communications and Networking – Behrouz A. Forouzan. Third Edition
TMH.

CS503PC: DEVOPS

Pre-Requisites: 1. Software Engineering 2. Software Project Management

Course Objectives:  Understand the skill sets and high-functioning teams involved in Agile, DevOps
and related methods to reach a continuous delivery capability.

 Implement automated system update and DevOps lifecycle.

Course Outcomes:  Understand the various components of DevOps environment.

 Identify Software development models and architectures of DevOps

 Use different project management and integration tools.

 Select an appropriate testing tool and deployment model for project.

UNIT-I Introduction to DevOps: Introduction, Agile development model, DevOps and ITIL. DevOps
process and Continuous Delivery, Release management, Scrum, Kanban, delivery pipeline, identifying
bottlenecks.

UNIT-II Software development models and DevOps: DevOps Lifecycle for Business Agility, DevOps,
and Continuous Testing. DevOps influence on Architecture: Introducing software architecture, The
monolithic scenario, Architecture rules of thumb, The separation of concerns, Handling database
migrations, Micro services and the data tier, DevOps, architecture, and resilience.

UNIT-III Introduction to project management: The need for source code control, the history of source
code management, Roles and code, source code management system and migrations, shared
authentication, Hosted Git servers, Different Git server implementations, Docker intermission, Gerrit,
The pull request model, GitLab.

UNIT-IV Integrating the system: Build systems, Jenkins build server, Managing build dependencies,
Jenkins plugins, and file system layout, The host server, Build slaves, Software on the host, Triggers,
Job chaining and build pipelines, Build servers and infrastructure as code, Building by dependency
order, Build phases, Alternative build servers, Collating quality measures.

UNIT-V Testing Tools and Deployment: Various types of testing, Automation of testing Pros and cons,
Selenium - Introduction, Selenium features, JavaScript testing, Testing backend integration points,
Test-driven development, REPL-driven development. Deployment of the system: Deployment
systems, Virtualization stacks, code execution at the client, Puppet master and agents, Ansible,
Deployment tools: Chef, Salt Stack and Docker.

TEXT BOOKS: 1. Joakim Verona., Practical DevOps, Packt Publishing, 2016.

REFERENCE BOOKS: 1. Deepak Gaikwad, Viral Thakkar. DevOps Tools from Practitioner's Viewpoint.
Wiley publications. 2. Len Bass, Ingo Weber, Liming Zhu. DevOps: A Software Architect's Perspective.
Addison Wesley
 CS511PE: QUANTUM COMPUTING (Professional Elective – I)

Course Objectives

 To introduce the fundamentals of quantum computing

 The problem-solving approach using finite dimensional mathematics

Course Outcomes  Understand basics of quantum computing

 Understand physical implementation of Qubit

 Understand Quantum algorithms and their implementation

 Understand The Impact of Quantum Computing on Cryptography

UNIT - I History of Quantum Computing: Importance of Mathematics, Physics and Biology.

Introduction to Quantum Computing: Bits Vs Qubits, Classical Vs Quantum logical operations

UNIT - II Background Mathematics: Basics of Linear Algebra, Hilbert space, Probabilities and
measurements. Background Physics: Paul's exclusion Principle, Superposition, Entanglement and
super-symmetry, density operators and correlation, basics of quantum mechanics, Measurements in
bases other than computational basis. Background Biology: Basic concepts of Genomics and
Proteomics (Central Dogma)

UNIT - III Qubit: Physical implementations of Qubit. Qubit as a quantum unit of information. The
Bloch sphere Quantum Circuits: single qubit gates, multiple qubit gates, designing the quantum
circuits. Bell states.

UNIT - IV Quantum Algorithms: Classical computation on quantum computers. Relationship between

quantum and classical complexity classes. Deutsch’s algorithm, Deutsch’s-Jozsa algorithm, Shor’s
factorization algorithm, Grover’s search algorithm.

UNIT - V Noise and error correction: Graph states and codes, Quantum error correction, fault-
tolerant computation. Quantum Information and Cryptography: Comparison between classical and
quantum information theory. Quantum Cryptography, Quantum teleportation

TEXT BOOKS: 1. Nielsen M. A., Quantum Computation and Quantum Information, Cambridge
REFERENCE BOOKS: 1. Quantum Computing for Computer Scientists by Noson S. Yanofsky and Mirco
A. Mannucci

2. Benenti G., Casati G. and Strini G., Principles of Quantum Computation and Information, Vol. I:
Basic Concepts, Vol II

3. Basic Tools and Special Topics, World Scientific. Pittenger A. O., An Introduction to Quantum
Computing Algorithms

CS512PE: ADVANCED COMPUTER ARCHITECTURE (Professional Elective – I)

Prerequisites: Computer Organization Course Objectives:

 To impart the concepts and principles of parallel and advanced computer architectures.

 To develop the design techniques of Scalable and multithreaded Architectures.

 To Apply the concepts and techniques of parallel and advanced computer architectures to design
modern computer systems Course Outcomes:

 Computational models and Computer Architectures.

 Concepts of parallel computer models.

 Scalable Architectures, Pipelining, Superscalar processors

UNIT - I Theory of Parallelism, Parallel computer models, The State of Computing, Multiprocessors
and Multicomputers, Multivector and SIMD Computers, PRAM and VLSI models, Architectural
development tracks, Program and network properties, Conditions of parallelism, Program
partitioning and Scheduling, Program flow Mechanisms, System interconnect Architectures.

UNIT - II Principles of Scalable performance, Performance metrics and measures, Parallel Processing
applications, Speed up performance laws, Scalability Analysis and Approaches, Hardware
Technologies, Processes and Memory Hierarchy, Advanced Processor Technology, Superscalar and
Vector Processors

UNIT - III Shared-Memory Organizations, Sequential and weak consistency models, Pipelining and
superscalar techniques, Linear Pipeline Processors, Non-Linear Pipeline Processors, Instruction
Pipeline design, Arithmetic pipeline design, superscalar pipeline design.

UNIT - IV Parallel and Scalable Architectures, Multiprocessors and Multicomputers, Multiprocessor

system interconnects, cache coherence and synchronization mechanism, Three Generations of
Multicomputers, Message-passing Mechanisms, Multivetor and SIMD computers.

UNIT - V Vector Processing Principles, Multivector Multiprocessors, Compound Vector processing,

SIMD computer Organizations, The connection machine CM-5.

TEXT BOOK 1. Advanced Computer Architecture, Kai Hwang, 2nd Edition, Tata McGraw Hill
Publishers.

REFERENCE BOOKS: 1. Computer Architecture, J.L. Hennessy and D.A. Patterson, 4th Edition,
ELSEVIER. 2. Advanced Computer Architectures, S.G.Shiva, Special Indian edition, CRC, Taylor
&Francis. 3. Introduction to High Performance Computing for Scientists and Engineers, G. Hager and
G. Wellein, CRC Press, Taylor & Francis Group. 4. Advanced Computer Architecture, D. Sima, T.
Fountain, P. Kacsuk, Pearson education. 5. Computer Architecture, B. Parhami, Oxford Univ. Press.

CS513PE: DATA ANALYTICS (Professional Elective – I)

Prerequisites 1. A course on “Database Management Systems”.

2. Knowledge of probability and statistics.

Course Objectives:  To explore the fundamental concepts of data analytics.  To learn the principles
and methods of statistical analysis

 Discover interesting patterns, analyze supervised and unsupervised models and estimate the
accuracy of the algorithms.

 To understand the various search methods and visualization techniques. Course Outcomes: After
completion of this course students will be able to
  Understand the impact of data analytics for business decisions and strategy  Carry out data
analysis/statistical analysis  To carry out standard data visualization and formal inference procedures
 Design Data Architecture  Understand various Data Sources

UNIT - I Data Management: Design Data Architecture and manage the data for analysis, understand
various sources of Data like Sensors/Signals/GPS etc. Data Management, Data Quality(noise, outliers,
missing values, duplicate data) and Data Processing & Processing.

UNIT - II Data Analytics: Introduction to Analytics, Introduction to Tools and Environment,

Application of Modeling in Business, Databases & Types of Data and Variables, Data Modeling
Techniques, Missing Imputations etc. Need for Business Modeling.

UNIT - III Regression – Concepts, Blue property assumptions, Least Square Estimation, Variable
Rationalization, and Model Building etc. Logistic Regression: Model Theory, Model fit Statistics,
Model Construction, Analytics applications to various Business Domains etc.

UNIT - IV Object Segmentation: Regression Vs Segmentation – Supervised and Unsupervised

Learning, Tree Building – Regression, Classification, Overfitting, Pruning and Complexity, Multiple
Decision Trees etc. Time Series Methods: Arima, Measures of Forecast Accuracy, STL approach,
Extract features from generated model as Height, Average Energy etc and Analyze for prediction

UNIT - V Data Visualization: Pixel-Oriented Visualization Techniques, Geometric Projection

Visualization Techniques, Icon-Based Visualization Techniques, Hierarchical Visualization Techniques,
Visualizing Complex Data and Relations.

TEXT BOOKS: 1. Student’s Handbook for Associate Analytics – II, III. 2. Data Mining Concepts and
Techniques, Han, Kamber, 3rd Edition, Morgan Kaufmann Publishers.

REFERENCE BOOKS: 1. Introduction to Data Mining, Tan, Steinbach and Kumar, Addision Wisley,
2006.

2. Data Mining Analysis and Concepts, M. Zaki and W. Meira

3. Mining of Massive Datasets, Jure Leskovec Stanford Univ. Anand Rajaraman Milliway Labs Jeffrey
D Ullman Stanford Univ.

CS514PE: IMAGE PROCESSING (Professional Elective – I)

Prerequisites 1. Students are expected to have knowledge in linear signals and systems, Fourier
Transform, basic linear algebra, basic probability theory and basic programming techniques;
knowledge of digital signal processing is desirable.

2. A course on “Computational Mathematics”

3. A course on “Computer Oriented Statistical Methods”

Course Objectives  Provide a theoretical and mathematical foundation of fundamental Digital Image
Processing concepts.  The topics include image acquisition; sampling and quantization;
preprocessing; enhancement; restoration; segmentation; and compression.

Course Outcomes  Demonstrate the knowledge of the basic concepts of two-dimensional signal
acquisition, sampling, and quantization.  Demonstrate the knowledge of filtering techniques. 
Demonstrate the knowledge of 2D transformation techniques.  Demonstrate the knowledge of
image enhancement, segmentation, restoration and compression techniques.

UNIT - I Digital Image Fundamentals: Digital Image through Scanner, Digital Camera. Concept of Gray
Levels. Gray Level to Binary Image Conversion. Sampling and Quantization. Relationship between
Pixels. Imaging Geometry. 2D Transformations-DFT, DCT, KLT and SVD.

UNIT - II Image Enhancement in Spatial Domain Point Processing, Histogram Processing, Spatial
Filtering, Enhancement in Frequency Domain, Image Smoothing, Image Sharpening.

UNIT - III Image Restoration Degradation Model, Algebraic Approach to Restoration, Inverse Filtering,
Least Mean Square Filters, Constrained Least Squares Restoration, Interactive Restoration.

UNIT - IV Image Segmentation Detection of Discontinuities, Edge Linking and Boundary Detection,
Thresholding, Region Oriented Segmentation.

UNIT - V Image Compression Redundancies and their Removal Methods, Fidelity Criteria, Image
Compression Models, Source Encoder and Decoder, Error Free Compression, Lossy Compression.

TEXT BOOK: 1. Digital Image Processing: R.C. Gonzalez & R. E. Woods, Addison Wesley/ Pearson
Education, 2nd Ed, 2004.

REFERENCE BOOKS: 1. Fundamentals of Digital Image Processing: A. K. Jain, PHI. 2. Digital Image
Processing using MAT LAB: Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins: Pearson Education
India, 2004. 3. Digital Image Processing: William K. Pratt, John Wiley, 3rd Edition, 2004.

CS515PE: PRINCIPLES OF PROGRAMMING LANGUAGES (Professional Elective – I)

Prerequisites 1. A course on “Mathematical Foundations of Computer Science”.

2. A course on “Computer Programming and Data Structures”.

Course Objectives  Introduce important paradigms of programming languages

 To provide conceptual understanding of high-level language design and implementation

 Topics include programming paradigms; syntax and semantics; data types, expressions and
statements; subprograms and blocks; abstract data types; concurrency; functional and logic
programming languages; and scripting languages

Course Outcomes

 Acquire the skills for expressing syntax and semantics in formal notation

 Identify and apply a suitable programming paradigm for a given computing application

 Gain knowledge of the features of various programming languages and their comparison

UNIT - I Preliminary Concepts: Reasons for Studying Concepts of Programming Languages,

Programming Domains, Language Evaluation Criteria, Influences on Language Design, Language
Categories, Language Design Trade-Offs, Implementation Methods, Programming Environments
Syntax and Semantics: General Problem of Describing Syntax and Semantics, Formal Methods of
Describing Syntax, Attribute Grammars, Describing the Meanings of Programs
UNIT - II Names, Bindings, and Scopes: Introduction, Names, Variables, Concept of Binding, Scope,
Scope and Lifetime, Referencing Environments, Named Constants Data Types: Introduction, Primitive
Data Types, Character String Types, User Defined Ordinal Types, Array, Associative Arrays, Record,
Union, Tuple Types, List Types, Pointer and Reference Types, Type Checking, Strong Typing, Type
Equivalence Expressions and Statements, Arithmetic Expressions, Overloaded Operators, Type
Conversions, Relational and Boolean Expressions, Short Circuit Evaluation, Assignment Statements,
Mixed-Mode Assignment Control Structures – Introduction, Selection Statements, Iterative
Statements, Unconditional Branching, Guarded Commands.

UNIT - III Subprograms and Blocks: Fundamentals of Sub-Programs, Design Issues for Subprograms,
Local Referencing Environments, Parameter Passing Methods, Parameters that Are Subprograms,
Calling Subprograms Indirectly, Overloaded Subprograms, Generic Subprograms, Design Issues for
Functions, User Defined Overloaded Operators, Closures, Coroutines Implementing Subprograms:
General Semantics of Calls and Returns, Implementing Simple Subprograms, Implementing
Subprograms with Stack-Dynamic Local Variables, Nested Subprograms, Blocks, Implementing
Dynamic Scoping Abstract Data Types: The Concept of Abstraction, Introductions to Data Abstraction,
Design Issues, Language Examples, Parameterized ADT, Encapsulation Constructs, Naming
Encapsulations

UNIT - IV Concurrency: Introduction, Introduction to Subprogram Level Concurrency, Semaphores,

Monitors, Message Passing, Java Threads, Concurrency in Function Languages, Statement Level
Concurrency. Exception Handling and Event Handling: Introduction, Exception Handling in Ada, C++,
Java, Introduction to Event Handling, Event Handling with Java and C#.

UNIT - V Functional Programming Languages: Introduction, Mathematical Functions, Fundamentals

of Functional Programming Language, LISP, Support for Functional Programming in Primarily
Imperative Languages, Comparison of Functional and Imperative Languages Logic Programming
Language: Introduction, an Overview of Logic Programming, Basic Elements of Prolog, Applications of
Logic Programming. Scripting Language: Pragmatics, Key Concepts, Case Study: Python – Values and
Types, Variables, Storage and Control, Bindings and Scope, Procedural Abstraction, Data Abstraction,
Separate Compilation, Module Library. (Text Book 2)

TEXT BOOKS: 1. Concepts of Programming Languages Robert. W. Sebesta 10/E, Pearson Education. 2.
Programming Language Design Concepts, D. A. Watt, Wiley Dreamtech, 2007.

REFERENCE BOOKS: 1. Programming Languages, 2nd Edition, A.B. Tucker, R. E. Noonan, TMH. 2.
Programming Languages, K. C. Louden, 2nd Edition, Thomson, 2003.

CS521PE: COMPUTER GRAPHICS (Professional Elective – II)

Prerequisites 1. Programming for problem solving and Data Structures

Course Objectives  Provide the basics of graphics systems including Points and lines, line drawing
algorithms, 2D, 3D objective transformations

Course Outcomes  Explore applications of computer graphics

 Understand 2D, 3D geometric transformations and clipping algorithms

 Understand 3D object representations, curves, surfaces, polygon rendering methods, color models
 Analyze animation sequence and visible surface detection methods
UNIT - I Introduction: Application areas of Computer Graphics, overview of graphics systems, video-
display devices, raster-scan systems, random-scan systems, graphics monitors and work stations and
input devices Output primitives: Points and lines, line drawing algorithms (DDA and Bresenham’s
Algorithm) circle generating algorithms and ellipse - generating algorithms Polygon Filling: Scan-line
algorithm, boundary-fill and flood-fill algorithms

UNIT - II 2-D geometric transformations: Translation, scaling, rotation, reflection and shear
transformations, matrix representations and homogeneous coordinates, composite transforms,
transformations between coordinate systems 2-D viewing: The viewing pipeline, viewing coordinate
reference frame, window to view-port coordinate transformation, viewing functions, clipping
operations, point clipping, Line clipping-Cohen Sutherland algorithms, Polygon clipping-Sutherland
Hodgeman polygon clipping algorithm.

UNIT - III 3-D object representation: Polygon surfaces, quadric surfaces, spline representation,
Hermite curve, Bezier curve and B-Spline curves, Bezier and B-Spline surfaces, Polygon rendering
methods, color models and color applications.

UNIT - IV 3-D Geometric transformations: Translation, rotation, scaling, reflection and shear
transformations, composite transformations. 3-D viewing: Viewing pipeline, viewing coordinates,
projections, view volume and general projection transforms and clipping.

UNIT - V Computer animation: Design of animation sequence, general computer animation functions,
raster animations, computer animation languages, key frame systems, motion specifications. Visible
surface detection methods: Classification, back-face detection, depth-buffer method, BSP tree
method, area sub-division method and octree method.

TEXT BOOKS: 1. “Computer Graphics C version”, Donald Hearn and M. Pauline Baker, Pearson
Education R22 B.Tech. CSE Syllabus JNTU Hyderabad

REFERENCE BOOKS: 1. Procedural elements for Computer Graphics, David F Rogers, Tata Mc Graw
hill, 2nd edition. 2. Principles of Interactive Computer Graphics”, Neuman and Sproul, TMH. 3.
Principles of Computer Graphics, Shalini Govil, Pai, 2005, Springer. 4. “Computer Graphics Principles
& practice”, second edition in C, Foley, Van Dam, Feiner and Hughes, Pearson Education. 5. Computer
Graphics, Steven Harrington, TMH.

CS522PE: EMBEDDED SYSTEMS (Professional Elective – II)

Pre-requisites: 1. A course on “Digital Logic Design and Microprocessors” 2. A course on “Computer

Organization and Architecture”

Course Objectives:  To provide an overview of principles of Embedded System  To provide a clear

understanding of role of firmware, operating systems in correlation with hardware systems.

Course Outcomes:  Expected to understand the selection procedure of processors in the embedded
domain.  Design procedure of embedded firm ware.  Expected to visualize the role of realtime
operating systems in embedded systems.  Expected to evaluate the correlation between task
synchronization and latency issues

UNIT - I Introduction to Embedded Systems: Processor embedded into a system, Embedded

Hardware units and devices in a system, Embedded software in a system, Design process of an
embedded system, classification of embedded systems, characteristics and quality attributes of an
embedded systems

UNIT - II Introduction to processor/microcontroller architecture, Real world interfacing, processor

and memory organization, memory types, memory maps and addresses, interrupt sources and
interrupt service mechanism.

UNIT - III On board Communication Basics: serial; communication devices, Parallel devices, Wireless
devices, Real time clock, Serial bus communication Protocols - I2C, SPI; Parallel buss communication -
ISA, PCI.

UNIT - IV Embedded Firmware Development: Overview of programming concepts - in assembly

language and in high level language ‘C’, C Program elements- Heads, Source files, Processor
Directives, Macros, Functions, Data types and Data Structures

UNIT - V OS Based Embedded Systems: OS services - Process/Task Management, Memory

Management, I/O subsystem manager, Inter Process/Task communications - Tasks, Task states,
Shared data, Signals, Message Queues, Mailbox, Pipes and concepts of Semaphores.

TEXT BOOK: 1. Embedded Systems, Raj Kamal, 2nd edition, Tata Mc Graw Hill 2. Shibu K V,
“Introduction to Embedded Systems”, Second Edition, Mc Graw Hill

REFERENCE BOOKS: 1. Rajkamal, Embedded Systems Architecture, Programming and Design, Tata
McGraw-Hill 2. Frank Vahid and Tony Givargis, “Embedded Systems Design” - A Unified
Hardware/Software Introduction, John Wiley 3. Lyla, “Embedded Systems” –Pearson 4. David E.
Simon, An Embedded Software Primer, Pearson Education Asia, First Indian Reprint 2000.

CS523PE: INFORMATION RETRIEVAL SYSTEMS (Professional Elective – II)

Prerequisites: 1. Data Structures

Course Objectives:  To learn the concepts and algorithms in Information Retrieval Systems  To
understand the data/file structures that are necessary to design, and implement information
retrieval (IR) systems.

Course Outcomes:  Ability to apply IR principles to locate relevant information large collections of
data  Ability to design different document clustering algorithms  Implement retrieval systems for
web search tasks.  Design an Information Retrieval System for web search tasks.

UNIT - I Introduction to Information Retrieval Systems: Definition of Information Retrieval System,

Objectives of Information Retrieval Systems, Functional Overview, Relationship to Database
Management Systems, Digital Libraries and Data Warehouses Information Retrieval System
Capabilities: Search Capabilities, Browse Capabilities, Miscellaneous Capabilities

UNIT - II Cataloging and Indexing: History and Objectives of Indexing, Indexing Process, Automatic
Indexing, Information Extraction Data Structure: Introduction to Data Structure, Stemming
Algorithms, Inverted File Structure, N-Gram Data Structures, PAT Data Structure, Signature File
Structure, Hypertext and XML Data Structures, Hidden Markov Models.

UNIT - III Automatic Indexing: Classes of Automatic Indexing, Statistical Indexing, Natural Language,
Concept Indexing, Hypertext Linkages Document and Term Clustering: Introduction to Clustering,
Thesaurus Generation, Item Clustering, Hierarchy of Clusters
 UNIT - IV User Search Techniques: Search Statements and Binding, Similarity Measures and Ranking,
Relevance Feedback, Selective Dissemination of Information Search, Weighted Searches of Boolean
Systems, Searching the INTERNET and Hypertext Information Visualization: Introduction to
Information Visualization, Cognition and Perception, Information Visualization Technologies

UNIT - V Text Search Algorithms: Introduction to Text Search Techniques, Software Text Search
Algorithms, Hardware Text Search Systems Multimedia Information Retrieval: Spoken Language
Audio Retrieval, Non-Speech Audio Retrieval, Graph Retrieval, Imagery Retrieval, Video Retrieval

TEXT BOOK: 1. Information Storage and Retrieval Systems – Theory and Implementation, Second
Edition, Gerald J. Kowalski, Mark T. Maybury, Springer

REFERENCE BOOKS: 1. Frakes, W.B., Ricardo Baeza-Yates: Information Retrieval Data Structures and
Algorithms, Prentice Hall, 1992. 2. Information Storage & Retrieval by Robert Korfhage – John Wiley
& Sons. 3. Modern Information Retrieval by Yates and Neto Pearson Education.

CS524PE: DISTRIBUTED DATABASES (Professional Elective – II)

Prerequisites: 1. A course on “Database Management Systems”

Course Objectives:  The purpose of the course is to enrich the previous knowledge of database
systems and expose the need for distributed database technology to confront the deficiencies of the
centralized database systems.  Introduce basic principles and implementation techniques of
distributed database systems.  Equip students with principles and knowledge of parallel and object-
oriented databases.  Topics include distributed DBMS architecture and design; query processing and
optimization; distributed transaction management and reliability; parallel and object database
management systems.

Course Outcomes:  Understand theoretical and practical aspects of distributed database systems. 
Study and identify various issues related to the development of distributed database systems. 
Understand the design aspects of object-oriented database systems and related developments.

UNIT - I Introduction; Distributed Data Processing, Distributed Database System, Promises of DDBSs,
Problem areas. Distributed DBMS Architecture: Architectural Models for Distributed DBMS, DDMBS
Architecture. Distributed Database Design: Alternative Design Strategies, Distribution Design issues,
Fragmentation, Allocation.

UNIT - II Query processing and decomposition: Query processing objectives, characterization of

query processors, layers of query processing, query decomposition, localization of distributed data.
Distributed query Optimization: Query optimization, centralized query optimization, distributed
query optimization algorithms.

UNIT - III Transaction Management: Definition, properties of transaction, types of transactions,

distributed concurrency control: serializability, concurrency control mechanisms & algorithms, time -
stamped & optimistic concurrency control Algorithms, deadlock Management.

UNIT - IV Distributed DBMS Reliability: Reliability concepts and measures, fault-tolerance in

distributed systems, failures in Distributed DBMS, local & distributed reliability protocols, site failures
and network partitioning. Parallel Database Systems: Parallel database system architectures, parallel
data placement, parallel query processing, load balancing, database clusters.
UNIT - V Distributed object Database Management Systems: Fundamental object concepts and
models, object distributed design, architectural issues, object management, distributed object
storage, object query Processing.Object Oriented Data Model: Inheritance, object identity, persistent
programming languages, persistence of objects, comparison OODBMS and ORDBMS

TEXT BOOKS: 1. M. Tamer OZSU and Patuck Valduriez: Principles of Distributed Database Systems,
Pearson Edn. Asia, 2001. 2. Stefano Ceri and Giuseppe Pelagatti: Distributed Databases, McGraw Hill.
REFERENCE BOOK: 1. Hector Garcia-Molina, Jeffrey D. Ullman, Jennifer Widom: “Database Systems:
The Complete Book”, Second Edition, Pearson International Edition.

CS525PE: NATURAL LANGUAGE PROCESSING (Professional Elective – II)

Prerequisites: 1. Data structures and compiler design

Course Objectives:  Introduction to some of the problems and solutions of NLP and their relation to
linguistics and statistics.

Course Outcomes:  Show sensitivity to linguistic phenomena and an ability to model them with
formal grammars.  Understand and carry out proper experimental methodology for training and
evaluating empirical NLP systems  Manipulate probabilities, construct statistical models over strings
and trees, and estimate parameters using supervised and unsupervised training methods.  Design,
implement, and analyze NLP algorithms; and design different language modeling Techniques.

UNIT - I Finding the Structure of Words: Words and Their Components, Issues and Challenges,
Morphological Models Finding the Structure of Documents: Introduction, Methods, Complexity of
the Approaches, Performances of the Approaches, Features

UNIT - II Syntax I: Parsing Natural Language, Treebanks: A Data-Driven Approach to Syntax,

Representation of Syntactic Structure, Parsing Algorithms

UNIT – III Syntax II: Models for Ambiguity Resolution in Parsing, Multilingual Issues Semantic Parsing
I: Introduction, Semantic Interpretation, System Paradigms, Word Sense

UNIT - IV Semantic Parsing II: Predicate-Argument Structure, Meaning Representation Systems

UNIT - V Language Modeling: Introduction, N-Gram Models, Language Model Evaluation, Bayesian
parameter estimation, Language Model Adaptation, Language Models- class based, variable length,
Bayesian topic based, Multilingual and Cross Lingual Language Modeling

TEXT BOOKS: 1. Multilingual natural Language Processing Applications: From Theory to Practice –
Daniel M. Bikel and Imed Zitouni, Pearson Publication.

REFERENCE BOOK: 1. Speech and Natural Language Processing - Daniel Jurafsky & James H Martin,
Pearson Publications. 2. Natural Language Processing and Information Retrieval: Tanvier Siddiqui, U.S.
Tiwary.

CS504PC: COMPUTER NETWORKS LAB

Course Objectives  To understand the working principle of various communication protocols.  To

understand the network simulator environment and visualize a network topology and observe its
performance  To analyze the traffic flow and the contents of protocol frames
 Course Outcomes  Implement data link layer farming methods  Analyze error detection and error
correction codes.  Implement and analyze routing and congestion issues in network design. 
Implement Encoding and Decoding techniques used in presentation layer  To be able to work with
different network tools

List of Experiments

1. Implement the data link layer framing methods such as character, character-stuffing and bit
stuffing.

2. Write a program to compute CRC code for the polynomials CRC-12, CRC-16 and CRC CCIP

3. Develop a simple data link layer that performs the flow control using the sliding window protocol,
and loss recovery using the Go-Back-N mechanism.

4. Implement Dijsktra’s algorithm to compute the shortest path through a network

5. Take an example subnet of hosts and obtain a broadcast tree for the subnet.

6. Implement distance vector routing algorithm for obtaining routing tables at each node.

7. Implement data encryption and data decryption

8. Write a program for congestion control using Leaky bucket algorithm.

9. Write a program for frame sorting techniques used in buffers.

10. Wireshark

i. Packet Capture Using Wire shark

ii. Starting Wire shark

iii. Viewing Captured Traffic

iv. Analysis and Statistics & Filters.

How to run Nmap scan

Operating System Detection using Nmap

Do the following using NS2 Simulator

i. NS2 Simulator-Introduction

ii. Simulate to Find the Number of Packets Dropped

iii. Simulate to Find the Number of Packets Dropped by TCP/UDP

iv. Simulate to Find the Number of Packets Dropped due to Congestion

v. Simulate to Compare Data Rate & Throughput.

vi. Simulate to Plot Congestion for Different Source/Destination

vii. Simulate to Determine the Performance with respect to Transmission of Packets

TEXT BOOK: 1. Computer Networks, Andrew S Tanenbaum, David. j. Wetherall, 5th Edition. Pearson
Education/PHI.
REFERENCE BOOKS: 1. An Engineering Approach to Computer Networks, S. Keshav, 2nd Edition,
Pearson Education. 2. Data Communications and Networking – Behrouz A. Forouzan. 3rd Edition,
TMH.

CS505PC: DEVOPS LAB

Course Objectives:  Develop a sustainable infrastructure for applications and ensure high scalability.
DevOps aims to shorten the software development lifecycle to provide continuous delivery with
high-quality.

Course Outcomes: 1. Understand the need of DevOps tools

2. Understand the environment for a software application development

3. Apply different project management, integration and development tools

4. Use Selenium tool for automated testing of application

List of Experiments:

1. Write code for a simple user registration form for an event.

2. Explore Git and GitHub commands.

3. Practice Source code management on GitHub. Experiment with the source code in exercise 1.

4. Jenkins installation and setup, explore the environment.

5. Demonstrate continuous integration and development using Jenkins.

6. Explore Docker commands for content management.

7. Develop a simple containerized application using Docker.

8. Integrate Kubernetes and Docker

9. Automate the process of running containerized application for exercise 7 using Kubernetes.

10. Install and Explore Selenium for automated testing.

11. Write a simple program in JavaScript and perform testing using Selenium.

12. Develop test cases for the above containerized application using selenium.

TEXT BOOKS: 1. Joakim Verona., Practical DevOps, Packt Publishing, 2016.

REFERENCE BOOKS: 1. Deepak Gaikwad, Viral Thakkar. DevOps Tools from Practitioner's Viewpoint.
Wiley publications. 2. Len Bass, Ingo Weber, Liming Zhu. DevOps: A Software Architect's Perspective.
Addison Wesley.

EN508HS: ADVANCED ENGLISH COMMUNICATION SKILLS LAB

1. Introduction The introduction of the Advanced English Communication Skills Lab is considered
essential at the B.Tech 3rd year level. At this stage, the students need to prepare themselves for their
career which may require them to listen to, read, speak and write in English both for their
professional and interpersonal communication in the globalised context. The proposed course should
be a laboratory course to enable students to use appropriate English and perform the following:

1. Gathering ideas and information to organise ideas relevantly and coherently.

2. Making oral presentations.

3. Writing formal letters.

4. Transferring information from non-verbal to verbal texts and vice-versa.

5. Writing project/research reports/technical reports.

6. Participating in group discussions.

7. Engaging in debates.

8. Facing interviews.

9. Taking part in social and professional communication.

2. Objectives: This Lab focuses on using multi-media instruction for language development to meet
the following targets:

 To improve the students’ fluency in English, with a focus on vocabulary

 To enable them to listen to English spoken at normal conversational speed by educated English
speakers

 To respond appropriately in different socio-cultural and professional contexts

 To communicate their ideas relevantly and coherently in writing

 To prepare the students for placements.

3. Syllabus: The following course content to conduct the activities is prescribed for the Advanced
English Communication Skills (AECS) Lab:

1. Activities on Listening and Reading Comprehension: Active Listening – Development of Listening

Skills Through Audio clips - Benefits of Reading – Methods and Techniques of Reading – Basic Steps to
Effective Reading – Common Obstacles – Discourse Markers or Linkers - Sub skills of reading -
Reading for facts, negative facts and Specific Details- Guessing Meanings from Context, Inferring
Meaning - Critical Reading –– Reading Comprehension – Exercises for Practice.

2. Activities on Writing Skills: Vocabulary for Competitive Examinations - Planning for Writing –
Improving Writing Skills - Structure and presentation of different types of writing – Free Writing and
Structured Writing - Letter Writing –Writing a Letter of Application –Resume vs. Curriculum Vitae –
Writing a Résumé – Styles of Résumé - e-Correspondence – Emails – Blog Writing - (N)etiquette –
Report Writing – Importance of Reports – Types and Formats of Reports– Technical Report Writing–
Exercises for Practice.

3. Activities on Presentation Skills - Starting a conversation – responding appropriately and relevantly

– using the right language and body language – Role Play in different situations including Seeking
Clarification, Making a Request, Asking for and Refusing Permission, Participating in a Small Talk –
Oral presentations (individual and group) through JAM sessions- PPTs – Importance of Presentation
Skills – Planning, Preparing, Rehearsing and Making a Presentation – Dealing with Glossophobia or
Stage Fear – Understanding Nuances of Delivery - Presentations through Posters/Projects/Reports –
Checklist for Making a Presentation and Rubrics of Evaluation

4. Activities on Group Discussion (GD): Types of GD and GD as a part of a Selection Procedure -

Dynamics of Group Discussion- Myths of GD - Intervention, Summarizing - Modulation of Voice, Body
Language, Relevance, Fluency and Organization of Ideas – Do’s and Don’ts - GD Strategies – Exercises
for Practice.

5. Interview Skills: Concept and Process - Interview Preparation Techniques - Types of Interview
Questions – Pre-interview Planning, Opening Strategies, Answering Strategies - Interview Through
Tele-conference & Video-conference - Mock Interviews.

4. Minimum Requirement: The Advanced English Communication Skills (AECS) Laboratory shall have
the following infrastructural facilities to accommodate at least 35 students in the lab:  Spacious
room with appropriate acoustics  Round Tables with movable chairs  Audio-visual aids  LCD
Projector  Public Address system  One PC with latest configuration for the teacher  T. V, a digital
stereo & Camcorder  Headphones of High quality

5. Suggested Software: The software consisting of the prescribed topics elaborated above should be
procured and used.  TOEFL & GRE (KAPLAN, AARCO & BARRONS, USA, Cracking GRE by CLIFFS) 
Oxford Advanced Learner’s Dictionary, 10th Edition  Cambridge Advanced Learner’s Dictionary 
DELTA’s key to the Next Generation TOEFL Test: Advanced Skill Practice.  Lingua TOEFL CBT Insider,
by Dreamtech

6. Books Recommended: 1. Rizvi, M. Ashraf (2018). Effective Technical Communication. (2nd ed.).
McGraw Hill Education (India) Pvt. Ltd. 2. Suresh Kumar, E. (2015). Engineering English. Orient
BlackSwan Pvt. Ltd. 3. Bailey, Stephen. (2018). Academic Writing: A Handbook for International
Students. (5th Edition). Routledge. 4. Koneru, Aruna. (2016). Professional Communication. McGraw
Hill Education (India) Pvt. Ltd. 5. Raman, Meenakshi & Sharma, Sangeeta. (2022). Technical
Communication, Principles and Practice. (4TH Edition) Oxford University Press. 6. Anderson, Paul V.
(2007). Technical Communication. Cengage Learning Pvt. Ltd. New Delhi. 7. McCarthy, Michael;
O’Dell, Felicity & Redman, Stuart. (2017). English Vocabulary in Use Series. Cambridge University
Press 8. Sen, Leela. (2009). Communication Skills. PHI Learning Pvt Ltd., New Delhi. 9. Elbow, Peter.
(1998 ). Writing with Power. Oxford University Press. 10. Goleman, Daniel. (2013). Emotional
Intelligence: Why it can matter more than IQ. Bloomsbury Publishing.

CS506PC: UI DESIGN-FLUTTER

Course Objectives:  Learns to Implement Flutter Widgets and Layouts  Understands Responsive UI
Design and with Navigation in Flutter  Knowledge on Widges and customize widgets for specific UI
elements, Themes  Understand to include animation apart from fetching data

Course Outcomes:  Implements Flutter Widgets and Layouts  Responsive UI Design and with
Navigation in Flutter  Create custom widgets for specific UI elements and also Apply styling using
themes and custom styles.  Design a form with various input fields, along with validation and error
handling  Fetches data and write code for unit Test for UI components and also animation

List of Experiments: Students need to implement the following experiments

1. a) Install Flutter and Dart SDK.

b) Write a simple Dart program to understand the language basics.

2. a) Explore various Flutter widgets (Text, Image, Container, etc.).

b) Implement different layout structures using Row, Column, and Stack widgets.

3. a) Design a responsive UI that adapts to different screen sizes.

b) Implement media queries and breakpoints for responsiveness.

4. a) Set up navigation between different screens using Navigator.

b) Implement navigation with named routes.

5. a) Learn about stateful and stateless widgets.

b) Implement state management using set State and Provider.

6. a) Create custom widgets for specific UI elements.

b) Apply styling using themes and custom styles.

7. a) Design a form with various input fields.

b) Implement form validation and error handling.

8. a) Add animations to UI elements using Flutter's animation framework.

b) Experiment with different types of animations (fade, slide, etc.).

9. a) Fetch data from a REST API.

b) Display the fetched data in a meaningful way in the UI.

10. a) Write unit tests for UI components.

b) Use Flutter's debugging tools to identify and fix issues.

TEXT BOOK: 1. Marco L. Napoli, Beginning Flutter: A Hands-on Guide to App Development.

*MC510: INTELLECTUAL PROPERTY RIGHTS

Course Objectives:  Significance of intellectual property and its protection  Introduce various forms
of intellectual property

Course Outcomes:  Distinguish and Explain various forms of IPRs.  Identify criteria to fit one's own
intellectual work in particular form of IPRs.  Apply statutory provisions to protect particular form of
IPRs.  Appraise new developments in IPR laws at national and international level

UNIT – I Introduction to Intellectual property: Introduction, types of intellectual property,

international organizations, agencies and treaties, importance of intellectual property rights.

UNIT – II Trade Marks: Purpose and function of trademarks, acquisition of trade mark rights,
protectable matter, selecting, and evaluating trade mark, trade mark registration processes.

UNIT – III Law of copyrights: Fundamental of copyright law, originality of material, rights of
reproduction, rights to perform the work publicly, copyright ownership issues, copyright registration,
notice of copyright, International copyright law. Law of patents: Foundation of patent law, patent
searching process, ownership rights and transfer

UNIT – IV Trade Secrets: Trade secret law, determination of trade secret status, liability for
misappropriations of trade secrets, protection for submission, trade secret litigation. Unfair
competition: Misappropriation right of publicity, false advertising.

UNIT – V New development of intellectual property: new developments in trade mark law; copyright
law, patent law, intellectual property audits. International overview on intellectual property,
international – trade mark law, copyright law, international patent law, and international
development in trade secrets law.

TEXT BOOK: 1. Intellectual property right, Deborah. E. Bouchoux, Cengage learning.

REFERENCE BOOK: 1. Intellectual property right – Unleashing the knowledge economy, prabuddha
ganguli, Tata McGraw Hill Publishing company ltd.