KEC


    Available courses

    KRISHNA ENGINEERING COLLEGE, GHAZIABAD

    Computer Science & Engineering

     

    COPY OF COURSE SYLLABUS

    RCS403: THEORY OF AUTOMATA AND FORMAL LANGUAGES

     

    UNIT I

    Introduction; Alphabets, Strings and Languages; Automata and Grammars, Deterministic finite Automata (DFA)-Formal Definition, Simplified notation: State transition graph, Transition table, Language of DFA, Nondeterministic finite Automata (NFA), NFA with epsilon transition, Language of NFA, Equivalence of NFA and DFA, Minimization of Finite Automata,  Distinguishing one string from other, Myhill-Nerode Theorem

    UNIT II

    Regular expression (RE), Definition, Operators of regular expression and their precedence, Algebraic laws for Regular expressions, Kleen’s Theorem, Regular expression to FA, DFA to Regular expression, Arden Theorem, Non Regular Languages, Pumping Lemma for regular Languages . Application of Pumping Lemma, Closure properties of Regular Languages, Decision properties of Regular Languages, FA with output: Moore and Mealy machine, Equivalence of Moore and Mealy Machine, Applications and Limitation of FA.

    UNIT III

    Context free grammar (CFG) and Context Free Languages (CFL): Definition, Examples, Derivation, Derivation trees, Ambiguity in Grammar, Inherent ambiguity, Ambiguous to Unambiguous CFG, Useless symbols, Simplification of CFGs, Normal forms for CFGs: CNF and GNF, Closure proper ties of CFLs, Decision Properties of CFLs: Emptiness, Finiteness and Membership, Pumping lemma for CFLs.

    UNIT IV

    Push Down Automata (PDA): Description and definition, Instantaneous Description, Language of PDA, Acceptance by Final state, Acceptance by empty stack, Deterministic PDA, Equivalence of PDA and CFG, CFG to PDA and PDA to CFG, Two stack PDA.

    UNIT V

    Turing machines (TM): Basic model, definition and representation, Instantaneous Description, Language acceptance by TM, Variants of Turing Machine, TM as Computerof Integer functions, Universal TM, Church’s Thesis, Recursive and recursively enumerable languages, Halting problem, Introduction to Undecidability, Undecidable problems about TMs. Post correspondence problem (PCP), Modified PCP, Introduction to recursive function theory.

     

     

    References:

    1. Hopcroft, Ullman, “Introduction to Automata Theory, Languages and Computation”, Pearson Education.

    2. KLP Mishra and N. Chandrasekaran, “Theory of Computer Science: Automata, Languages and Computation”, PHI Learning Private Limited, Delhi India.

    3. Peter Linz, "An Introduction to Formal Language and Automata", Narosa Publishing house.

    4. YN Singh “Mathematical Foundation of Computer Science”, New Age International.

    5. Malviya, AK "Theory of Computation and Application", BPaperback Publications

    6. Papadimitrou, C. and Lewis, CL, “Elements of the Theory of Computation”, Pearson Publication.


    Web Technology Syllabus

     

    Unit -1

    IntroductionIntroduction and Web Development Strategies, History of Web and Internet, Protocols Governing Web, Writing Web Projects, Connecting to Internet, Introduction to Internet services and tools, Introduction to client-server computing. Core Java: Introduction, Operator, Data type, Variable, Arrays, Methods & Classes, Inheritance, Package and Interface, Exception Handling, Multithread programming, I/O, Java Applet, String handling, Event handling, Introduction to AWT, AWT controls, Layout managers.

     

    Unit -2

    Web Page Designing: HTML: List, Table, Images, Frames, forms, CSS, Document type definition, XML: DTD, XML schemes, Object Models, presenting and using XML, Using XML Processors: DOM and SAX, Dynamic HTML

     

    Unit -3

    Scripting: Java script: Introduction, documents, forms, statements, functions, objects; introduction to AJAX, Networking : Internet  Addressing,  InetAddress,  Factory  Methods,  Instance  Methods,  TCP/IP  Client Sockets, URL, URL Connection, TCP/IP Server Sockets, Datagram.

     

    Unit -4

    Enterprise Java Bean: Preparing a Class to be a JavaBeans, Creating a JavaBeans, JavaBeans Properties, Types of beans, Stateful Session bean, Stateless Session bean, Entity bean Java  Database  Connectivity  (JDBC): Merging  Data  from  Multiple  Tables:  Joining,  Manipulating, Databases with JDBC, Prepared Statements, Transaction Processing, Stored Procedures

     

    Unit -5

    Servlets:  Servlet  Overview  and  Architecture,  Interface  Servlet  and  the  Servlet  Life  Cycle, Handling HTTP  get  Requests,  Handling  HTTP  post  Requests,  Redirecting  Requests  to  Other Resources,  Session Tracking, Cookies, Session Tracking with Http Session Java Server  Pages  (JSP): Introduction,  Java Server  Pages  Overview, A  First  Java Server  Page Example, Implicit Objects, Scripting, Standard Actions, Directives, Custom Tag Libraries.


    COURSE OUTCOME: At the end of the course, learners should be able to1. Identify and explore the basic features and modalities about Indian constitution. 2. Differentiate and relate the functioning of Indian parliamentary system at the center and state level. 3. Differentiate different aspects of Indian Legal System and its related bodies. 4. Discover and apply different laws and regulations related to engineering practices. 5. Correlate role of engineers with different organizations and governance models

    Image Processing (KCS-062)

    DETAILED SYLLABUS

    Unit

    Topic

     

    I

    DIGITAL IMAGE FUNDAMENTALS: Steps in Digital Image Processing – Components – Elements of Visual Perception – Image Sensing and Acquisition – Image Sampling and Quantization – Relationships between pixels – Color image fundamentals – RGB, HSI models,

    Two-dimensional mathematical preliminaries, 2D transforms – DFT, DCT.

     

     

    II

    IMAGE ENHANCEMENT:

    Spatial Domain: Gray level transformations – Histogram processing – Basics of Spatial Filtering– Smoothing and Sharpening Spatial Filtering, Frequency Domain: Introduction to Fourier Transform– Smoothing and Sharpening frequency domain filters – Ideal, Butterworth and Gaussian

    filters, Homomorphic filtering, Color image enhancement.

     

    III

    IMAGE RESTORATION:

    Image Restoration – degradation model, Properties, Noise models – Mean Filters – Order Statistics

    – Adaptive filters – Band reject Filters – Band pass Filters – Notch Filters – Optimum Notch Filtering – Inverse Filtering – Wiener filtering

     

     

    IV

    IMAGE SEGMENTATION:

    Edge detection, Edge linking via Hough transform – Thresholding – Region based segmentation – Region growing – Region splitting and merging – Morphological processing- erosion and dilation, Segmentation by morphological watersheds – basic concepts – Dam construction – Watershed

    segmentation algorithm.

     

     

    V

    IMAGE COMPRESSION AND RECOGNITION:

    Need for data compression, Huffman, Run Length Encoding, Shift codes, Arithmetic coding, JPEG standard, MPEG. Boundary representation, Boundary description, Fourier Descriptor, Regional Descriptors – Topological feature, Texture – Patterns and Pattern classes – Recognition based on

    matching.


    Unit 1: Introductory Concepts: Goals and applications of networks, Categories of networks, Organization of the Internet, ISP, Network structure and architecture (layering principles, services, protocols and standards), The OSI reference model, TCP/IP protocol suite, Network devices and components. Physical Layer: Network topology design, Types of connections, Transmission media, Signal transmission and encoding, Network performance and transmission impairments, Switching techniques and multiplexing

    Unit 2: Link layer: Framing, Error Detection and Correction, Flow control (Elementary Data Link Protocols, Sliding Window protocols). Medium Access Control and Local Area Networks: Channel allocation, Multiple access protocols, LAN standards, Link layer switches & bridges (learning bridge and spanning tree algorithms).

    Unit 3: Network Layer: Point-to-point networks, Logical addressing, Basic internetworking (IP, CIDR, ARP, RARP, DHCP, ICMP), Routing, forwarding and delivery, Static and dynamic routing, Routing algorithms and protocols, Congestion control algorithms, IPv6.

    Unit 4: Transport Layer: Process-to-process delivery, Transport layer protocols (UDP and TCP), Multiplexing, Connection management, Flow control and retransmission, Window management, TCP Congestion control, Quality of service.

    Unit 5: Application Layer: Domain Name System, World Wide Web and Hyper Text Transfer Protocol, Electronic mail, File Transfer Protocol, Remote login, Network management, Data compression, Cryptography – basic concepts.

    IN THIS COURSE WE WILL STUDY ABOUT VARIOUS TYPES OF ATTACKS THAT CAN OCCOUR IN OUR SYSTEM AND SECURITY MEASURES FOR THOSE ATTACKS

    Design and Analysis of Algorithm syllabus

    UNIT-I

    Introduction: Algorithms, Analyzing Algorithms, Complexity of Algorithms, Growth of Functions, Performance Measurements, Sorting and Order Statistics - Shell Sort, Quick Sort, Merge Sort, Heap Sort, Comparison of Sorting Algorithms, Sorting in Linear Time.

    UNIT-II

    Advanced Data Structures: Red-Black Trees, B – Trees, Binomial Heaps, Fibonacci Heaps, Tries, Skip List

    UNIT III

    Divide and Conquer with Examples Such as Sorting, Matrix Multiplication, Convex Hull and Searching. Greedy Methods with Examples Such as Optimal Reliability Allocation, Knapsack, Minimum Spanning Trees – Prim’s and Kruskal’s Algorithms, Single Source Shortest Paths - Dijkstra’s and Bellman Ford Algorithms

    UNIT IV

    Dynamic Programming with Examples Such as Knapsack. All Pair Shortest Paths – Warshal’s and Floyd’s Algorithms, Resource Allocation Problem. Backtracking, Branch and Bound with Examples Such as Travelling Salesman Problem, Graph Coloring, n-Queen Problem, Hamiltonian Cycles and Sum of Subsets.

    UNIT V

    Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NPCompleteness, Approximation Algorithms and Randomized Algorithms

    Text books: 

    1. Thomas H. Coreman, Charles E. Leiserson and Ronald L. Rivest, “Introduction to Algorithms”, Printice Hall of India.

    2. E. Horowitz & S Sahni, "Fundamentals of Computer Algorithms",

     3. Aho, Hopcraft, Ullman, “The Design and Analysis of Computer Algorithms” Pearson Education, 2008. 

    4. LEE "Design & Analysis of Algorithms (POD)",McGraw Hill 

    5. Richard E.Neapolitan "Foundations of Algorithms" Jones & Bartlett Learning

     6. Jon Kleinberg and Éva Tardos, Algorithm Design, Pearson, 2005. 

    7. Michael T Goodrich and Roberto Tamassia, Algorithm Design: Foundations, Analysis, and Internet Examples, Second Edition, Wiley, 2006. 

    8. Harry R. Lewis and Larry Denenberg, Data Structures and Their Algorithms, Harper Collins, 1997

     9. Robert Sedgewick and Kevin Wayne, Algorithms, fourth edition, Addison Wesley, 2011. 

    10. Harsh Bhasin,”Algorithm Design and Analysis”,First Edition,Oxford University Press. 

    11. Gilles Brassard and Paul Bratley,Algorithmics:Theory and Practice,Prentice Hall,1995.

    The main objective of the course is to expose the students to soft computing, various types of soft computing techniques, and applications of soft computing. .Upon completion of this course, the student should be able to get an idea about Neural Networks, architecture, functions, and various algorithms involved. Also, they will be able to understand Fuzzy Logic, Various fuzzy systems, functions, and Genetic algorithm concepts.

    Distributed System 7 th sem CSE.

    Digital and Social Media Marketing

    Introduction to Digital Marketing: The new digital world - trends that are driving shifts from traditional marketing practices to digital marketing practices, the modern digital consumer and new consumer’s digital journey. Marketing strategies for the digital world-latest practices.
     UNIT-II Social Media Marketing -Introduction to Blogging, Create a blog post for your project. Include headline, imagery, links and post, Content Planning and writing. Introduction to Face book, Twitter, Google +, LinkedIn, YouTube, Instagram and Pinterest; their channel advertising and campaigns
    UNIT-III Acquiring & Engaging Users through Digital Channels: Understanding the relationship between content and branding and its impact on sales, search engine marketing, mobile marketing, video marketing, and social-media marketing. Marketing gamification, Online campaign management; using marketing analytic tools to segment, target and position; overview of search engine optimization (SEO).
    UNIT-IV Designing Organization for Digital Success: Digital transformation, digital leadership principles, online P.R. and reputation management. ROI of digital strategies, how digital marketing is adding value to business, and evaluating cost effectiveness of digital strategies
    UNIT-V Digital Innovation and Trends: The contemporary digital revolution, digital transformation framework; security and privatization issues with digital marketing Understanding trends in digital marketing – Indian and global context, online communities and co-creation,
    Text books: 1. Moutsy Maiti: Internet Mareting, Oxford University Press India 2. Vandana, Ahuja; Digital Marketing, Oxford University Press India (November, 2015).

    Compression Techniques: Loss less compression, Lossy Compression, Measures of performance, Modeling and coding, Mathematical Preliminaries for Lossless compression: A brief introduction to information theory, Models: Physical models, Probability models, Markov models, composite source model, Coding: uniquely decodable codes, Prefix codes. 08

     II The Huffman coding algorithm: Minimum variance Huffman codes, Adaptive Huffman coding: Update procedure, Encoding procedure, Decoding procedure. Golomb codes, Rice codes, Tunstall codes, Applications of Hoffman coding: Loss less image compression, Text compression, Audio Compression. 08 

    III Coding a sequence, Generating a binary code, Comparison of Binary and Huffman coding, Applications: Bi-level image compression-The JBIG standard, JBIG2, Image compression. Dictionary Techniques: Introduction, Static Dictionary: Diagram Coding, Adaptive Dictionary. The LZ77 Approach, The LZ78 Approach, Applications: File Compression-UNIX compress, Image Compression: The Graphics Interchange Format (GIF), Compression over Modems: V.42 bits, Predictive Coding: Prediction with Partial match (ppm): The basic algorithm, The ESCAPE SYMBOL, length of context, The Exclusion Principle, The Burrows-Wheeler Transform: Movetofront coding, CALIC, JPEG-LS, Multi-resolution Approaches, Facsimile Encoding, Dynamic Markoy Compression. 08 

    IV Distortion criteria, Models, Scalar Ouantization: The Quantization problem, Uniform Quantizer, Adaptive Quantization, Non uniform Quantization. 08

    V Advantages of Vector Quantization over Scalar Quantization, The Linde-Buzo-Gray Algorithm, Tree structured Vector Quantizers. Structured VectorQuantizers.

    Computer Networks(KCS- 603)

    Unit-1

    Introductory Concepts: Goals and applications of networks, Categories of networks, Organization of the Internet, ISP, Network structure and architecture (layering principles, services, protocols and standards), The OSI reference model, TCP/IP protocol suite, Network devices and components.

    Physical Layer: Network topology design, Types of connections, Transmission media, Signal transmission and encoding, Network performance and transmission impairments, Switching techniques and multiplexing.

    Unit-2

    Link layer: Framing, Error Detection and Correction, Flow control (Elementary Data Link Protocols, Sliding Window protocols).

    Medium Access Control and Local Area Networks: Channel allocation, Multiple access protocols, LAN standards, Link layer switches & bridges (learning bridge and spanning tree algorithms).

    Unit-3

    Network Layer: Point-to-point networks, Logical addressing, Basic internetworking (IP, CIDR, ARP, RARP, DHCP, ICMP), Routing, forwarding and delivery, Static and dynamic routing, Routing algorithms and protocols, Congestion control algorithms, IPv6.

    Unit-4

    Transport Layer: Process-to-process delivery, Transport layer protocols (UDP and TCP), Multiplexing, Connection management, Flow control and retransmission, Window management, TCP Congestion control, Quality of service.

    Unit-5

    Application Layer: Domain Name System, World Wide Web and Hyper Text Transfer Protocol, Electronic mail, File Transfer Protocol, Remote login, Network management, Data compression, Cryptography – basic concepts.

    Text books and References:

    1.Behrouz Forouzan, “Data Communication and Networking”, McGraw Hill

    2.Andrew Tanenbaum “Computer Networks”, Prentice Hall.

    3.William Stallings, “Data and Computer Communication”, Pearson.

    4.Kurose and Ross, “Computer Networking- A Top-Down Approach”, Pearson.

    5.Peterson and Davie, “Computer Networks: A Systems Approach”, Morgan Kaufmann

    6.W. A. Shay, “Understanding Communications and Networks”, Cengage Learning.

    7.D. Comer, “Computer Networks and Internets”, Pearson.

    8.Behrouz Forouzan, “TCP/IP Protocol Suite”, McGraw Hill.


    Brief Introduction of Computer Networks

    The term telecommunication means communication at a distance. The word data refers to information presented in whatever form is agreed upon by the parties creating and using the data. Data communications are the exchange of data between two devices via some form of transmission medium such as a wire cable.

    A network is a set of devices (often referred to as nodes) connected by communication links. A node can be a computer, printer, or any other device capable of sending and/or receiving data generated by other nodes on the network.

    computer network is a system in which multiple autonomous computers are connected to each other to share information and resources.

    Computer Networks

    The course aims at imparting basic principles of thought process, reasoning and inference to identify the roots and details of some of the contemporary issues faced by our nation and try to locate possible solutions to these challenges by digging deep into our past. It  enables the students to understand the importance of our surroundings and encourage the students to contribute towards sustainable development. 

    Introduction and Web

    Core Java

    Web Page Designing: HTML, CSS, XML

    NetworkingScripting: JavaScript

    Enterprise Java Bean & JDBC

    Servlets & Java Server Pages


    Machine learning is a sub field of artificial intelligence (AI). The goal of machine learning generally is to understand the structure of data and fit that data into models that can be understood and utilised by people.

    Although machine learning is a field within computer science, it differs from traditional computational approaches. In traditional computing, algorithms are sets of explicitly programmed instructions used by computers to calculate or problem solve. Machine learning algorithms instead allow for computers to train on data inputs and use statistical analysis in order to output values that fall within a specific range. Because of this, machine learning facilitates computers in building models from sample data in order to automate decision-making processes based on data inputs.

    In this course we would learn about the machine Learning techniques and algorithms. 


    Unit 1-Introduction: Overview, Database System vs File System, Database System Concept and Architecture, Data Model Schema and Instances, Data Independence and Database Language and Interfaces, Data Definitions Language, DML, Overall Database Structure. Data Modeling Using the Entity Relationship Model: ER Model Concepts, Notation for ER Diagram, Mapping Constraints, Keys, Concepts of Super Key, Candidate Key, Primary Key, Generalization, Aggregation, Reduction of an ER Diagrams to Tables, Extended ER Model, Relationship of Higher Degree.

    Unit 2-Relational data Model and Language: Relational Data Model Concepts, Integrity Constraints, Entity Integrity, Referential Integrity, Keys Constraints, Domain Constraints, Relational Algebra, Relational Calculus, Tuple and Domain Calculus. Introduction on SQL: Characteristics of SQL, Advantage of SQL. SQl Data Type and Literals. Types of SQL Commands. SQL Operators and Their Procedure. Tables, Views and Indexes. Queries and Sub Queries. Aggregate Functions. Insert, Update and Delete Operations, Joins, Unions, Intersection, Minus, Cursors, Triggers, Procedures in SQL/PL SQL

    Unit 3-Data Base Design & Normalization: Functional dependencies, normal forms, first, second, 8 third normal forms, BCNF, inclusion dependence, loss less join decompositions, normalization using FD, MVD, and JDs, alternative approaches to database design

    Unit 4-Transaction Processing Concept: Transaction System, Testing of Serializability, Serializability of Schedules, Conflict & View Serializable Schedule, Recoverability, Recovery from Transaction Failures, Log Based Recovery, Checkpoints, Deadlock Handling. Distributed Database: Distributed Data Storage, Concurrency Control, Directory System

    Unit 5-Concurrency Control Techniques: Concurrency Control, Locking Techniques for Concurrency Control, Time Stamping Protocols for Concurrency Control, Validation Based Protocol, Multiple Granularity, Multi Version Schemes, Recovery with Concurrent Transaction, Case Study of Oracle

    Text books:

    1. Korth, Silbertz, Sudarshan,” Database Concepts”, McGraw Hill 

    2. Date C J, “An Introduction to Database Systems”, Addision Wesley 

    3. Elmasri, Navathe, “ Fundamentals of Database Systems”, Addision Wesley 

    4. O’Neil, Databases, Elsevier Pub. 

    5. RAMAKRISHNAN"Database Management Systems",McGraw Hill 

    6. Leon & Leon,”Database Management Systems”, Vikas Publishing House 

    7. Bipin C. Desai, “ An Introduction to Database Systems”, Gagotia Publications 

    8. Majumdar & Bhattacharya, “Database Management System”, TMH

    This Course contains concepts of Object Oriented Programming like Information hiding ,Abstraction ,Encapsulation, etc. After completing this course Students must be able to perform coding in C++ Programming Language.

    Hard Computing:  In 1996, LA Zadeh (LAZ) introduced the term hard computing. According to LAZ: We term a computing as ”Hard” computing, if

    • Precise result is guaranteed
    • Control action is unambiguous
    • Control action is formally defined (i.e. with  mathematical model
    Example:

    • Solving numerical problems (e.g. Roots of polynomials,  Integration etc.)
    • Searching and sorting techniques
    • Solving ”Computational Geometry” problems (e.g. Shortest  tour in Graph theory, Finding closest pair of points etc.)

    Soft computing: Soft computing was proposed by Lotfi A. Zadeh. First he gave the idea about Fuzzy Logic.

    Soft Computing is a collection of methodologies that aim to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness, and low solution cost.

     • Tolerance of imprecision means result is not precise

    • Uncertainty means different result at different time
    • Tractability means problem solved with in polynomial time
    • Robustness means it can tackle any sort of input including noise

    Soft Computing is a term applied to a field within computer science which is characterized by the use of inexact solutions to computationally hard task such as solution of NP- Complete problems for which an exact solution can not be derived with in polynomial time.

    Characteristics of Soft Computing:

    • It does not require any mathematical modeling of problem  solving
    • It may not yield the precise solution
    • Algorithms are adaptive (i.e. it can adjust to the change of  dynamic environment)
    • Use some biological inspired methodologies such as genetics,  evolution, Ant’s behaviors, human nervous  systems etc.

    Applications using Soft Computing:

    • Handwriting Recognition
    • Automotive systems and manufacturing
    • Image processing and data recognition
    • Decision support System
    • To Power System
    • Neuro Fuzzy System
    • Fuzzy Logic Control
    • Genetic Algorithms
    • Bio Informatics and Biomedicine


    Components of Soft Computing includes:

    • Neural Networks (NN)
    • Fuzzy System or Fuzzy Logic
    • Genetic Algorithm (Evolutionary Computing)

    Books Reference:

    1. S. Rajsekaran & G.A. Vijayalakshmi Pai, “Neural Networks,Fuzzy Logic and Genetic Algorithm:Synthesis and Applications” Prentice Hall of India.

    2. Dr. S.N Sivanandam & Dr. S.N Deepa “Principles of Soft Computing” Wiley



    Compiler Design (KCS-502)

     At the end of course , the student will be able to: 

    CO 1 Acquire knowledge of different phases and passes of the compiler and also able to use the compiler tools like LEX, YACC, etc. Students will also be able to design different types of compiler tools to meet the requirements of the realistic constraints of compilers. 

    CO 2 Understand the parser and its types i.e. Top-Down and Bottom-up parsers and construction of LL, SLR, CLR, and LALR parsing table.  

    CO 3 Implement the compiler using syntax-directed translation method and get knowledge about the synthesized and inherited attributes. 

    CO 4 Acquire knowledge about run time data structure like symbol table organization and different techniques used in that. 

    CO 5 Understand the target machine’s run time environment, its instruction set for code generation and techniques used for code optimization. 

    Unit 1: Introduction to Compiler: Phases and passes, Bootstrapping, Finite state machines and regular expressions and their applications to lexical analysis, Optimization of DFA-Based Pattern Matchers implementation of lexical analyzers, lexical-analyzer generator, LEX compiler, Formal grammars and their application to syntax analysis, BNF notation, ambiguity, YACC. The syntactic specification of programming languages: Context free grammars, derivation and parse trees, capabilities of CFG. 

    UNIT II: Basic Parsing Techniques: Parsers, Shift reduce parsing, operator precedence parsing, top down parsing, predictive parsers Automatic Construction of efficient Parsers: LR parsers, the canonical Collection of LR(0) items, constructing SLR parsing tables, constructing Canonical LR parsing tables, Constructing LALR parsing tables, using ambiguous grammars, an automatic parser generator, implementation of LR parsing tables.

    UNIT III : Syntax-directed Translation: Syntax-directed Translation schemes, Implementation of Syntaxdirected Translators, Intermediate code, postfix notation, Parse trees & syntax trees, three address code, quadruple & triples, translation of assignment statements, Boolean expressions, statements that alter the flow of control, postfix translation, translation with a top down parser. More about translation: Array references in arithmetic expressions, procedures call, declarations and case statements. 

    UNIT IV : Symbol Tables: Data structure for symbols tables, representing scope information. Run-Time Administration: Implementation of simple stack allocation scheme, storage allocation in block structured language. Error Detection & Recovery: Lexical Phase errors, syntactic phase errors semantic errors. 

    UNIT V : Code Generation: Design Issues, the Target Language. Addresses in the Target Code, Basic Blocks and Flow Graphs, Optimization of Basic Blocks, Code Generator. Code optimization: Machine-Independent Optimizations, Loop optimization, DAG representation of basic blocks, value numbers and algebraic laws, Global Data-Flow analysis.

     Text books: 1. K. Muneeswaran,Compiler Design,First Edition,Oxford University Press. 

    2. J.P. Bennet, “Introduction to Compiler Techniques”, Second Edition, Tata McGraw-Hill,2003.

     3. Henk Alblas and Albert Nymeyer, “Practice and Principles of Compiler Building with C”, PHI, 2001.

     4. Aho, Sethi & Ullman, "Compilers: Principles, Techniques and Tools”, Pearson Education 

    5. V Raghvan, “ Principles of Compiler Design”, TMH 

    6. Kenneth Louden,” Compiler Construction”, Cengage Learning. 

    7. Charles Fischer and Ricard LeBlanc,” Crafting a Compiler with C”, Pearson Education

    KCS-503: Design and Analysis of Algorithm

     

     

    UNIT

    TOPIC

    1

    Introduction: Algorithms, Analyzing Algorithms, Complexity of Algorithms, Growth of Functions, Performance Measurements, Sorting and Order Statistics - Shell Sort, Quick Sort, Merge Sort, Heap Sort, Comparison of Sorting Algorithms, Sorting in Linear Time.

    2

    Advanced Data Structures: Red-Black Trees, B – Trees, Binomial Heaps, Fibonacci Heaps, Tries, Skip List

     

    3

    Divide and Conquer with Examples Such as Sorting, Matrix Multiplication, Convex Hull and Searching. Greedy Methods with Examples Such as Optimal Reliability Allocation, Knapsack, Minimum Spanning Trees – Prim’s and Kruskal’s Algorithms, Single Source Shortest Paths - Dijkstra’s and Bellman Ford Algorithms

     

    4

    Dynamic Programming with Examples Such as Knapsack. All Pair Shortest Paths – Warshal’s and Floyd’s Algorithms, Resource Allocation Problem. Backtracking, Branch and Bound with Examples Such as Travelling Salesman Problem, Graph Coloring, n-Queen Problem, Hamiltonian Cycles and Sum of Subsets.

     

    5

    Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NP-Completeness, Approximation Algorithms and Randomized Algorithms

     

    References:

    1. Thomas H. Coreman, Charles E. Leiserson and Ronald L. Rivest, “Introduction to Algorithms”, Printice Hall of India.

    2. E. Horowitz & S Sahni, "Fundamentals of Computer Algorithms",

    3. Aho, Hopcraft, Ullman, “The Design and Analysis of Computer Algorithms” Pearson Education, 2008.

    4. LEE "Design & Analysis of Algorithms (POD)",McGraw Hill

    5. Gajendra Sharma, Design & Analysis of Algorithms, Khanna Publishing House

    6. Richard E.Neapolitan "Foundations of Algorithms" Jones & Bartlett Learning

    7. Jon Kleinberg and Éva Tardos, Algorithm Design, Pearson, 2005.

    8. Michael T Goodrich and Roberto Tamassia, Algorithm Design: Foundations, Analysis, and Internet Examples, Second Edition, Wiley, 2006.

    9. Harry R. Lewis and Larry Denenberg, Data Structures and Their Algorithms, Harper Collins, 1997

    10. Robert Sedgewick and Kevin Wayne, Algorithms, fourth edition, Addison Wesley, 2011.

    11. Harsh Bhasin,”Algorithm Design and Analysis”,First Edition,Oxford University Press.

    12. Gilles Brassard and Paul Bratley,Algorithmics:Theory and Practice,Prentice Hall,1995.

     

     

     

     


    1. Introduction: Overview, Database System vs File System, Database System Concept and Architecture, Data Model Schema and Instances, Data Independence and Database Language and Interfaces, Data Definitions Language, DML, Overall Database Structure. Data Modeling Using the Entity Relationship Model: ER Model Concepts, Notation for ER Diagram, Mapping Constraints, Keys, Concepts of Super Key, Candidate Key, Primary Key, Generalization, Aggregation, Reduction of an ER Diagrams to Tables, Extended ER Model, Relationship of Higher Degree. 

     2.  Relational data Model and Language: Relational Data Model Concepts, Integrity Constraints, Entity Integrity, Referential Integrity, Keys Constraints, Domain Constraints, Relational Algebra, Relational Calculus, Tuple and Domain Calculus. Introduction on SQL: Characteristics of SQL, Advantage of SQL. SQl Data Type and Literals. Types of SQL Commands. SQL Operators and Their Procedure. Tables, Views and Indexes. Queries and Sub Queries. Aggregate Functions. Insert, Update and Delete Operations, Joins, Unions, Intersection, Minus, Cursors, Triggers, Procedures in SQL/PL SQL 

    3.  Data Base Design & Normalization: Functional dependencies, normal forms, first, second, 8 third normal forms, BCNF, inclusion dependence, loss less join decompositions, normalization using FD, MVD, and JDs, alternative approaches to database design.

     4.  Transaction Processing Concept: Transaction System, Testing of Serializability, Serializability of Schedules, Conflict & View Serializable Schedule, Recoverability, Recovery from Transaction Failures, Log Based Recovery, Checkpoints, Deadlock Handling. Distributed Database: Distributed Data Storage, Concurrency Control, Directory System. 

     5.  Concurrency Control Techniques: Concurrency Control, Locking Techniques for Concurrency Control, Time Stamping Protocols for Concurrency Control, Validation Based Protocol, Multiple Granularity, Multi Version Schemes, Recovery with Concurrent Transaction, Case Study of Oracle.

    Hard Computing:  In 1996, LA Zadeh (LAZ) introduced the term hard computing. According to LAZ: We term a computing as ”Hard” computing, if

    • Precise result is guaranteed
    • Control action is unambiguous
    • Control action is formally defined (i.e. with  mathematical model
    Example:

    • Solving numerical problems (e.g. Roots of polynomials,  Integration etc.)
    • Searching and sorting techniques
    • Solving ”Computational Geometry” problems (e.g. Shortest  tour in Graph theory, Finding closest pair of points etc.)

    Soft computing: Soft computing was proposed by Lotfi A. Zadeh. First he gave the idea about Fuzzy Logic.

    Soft Computing is a collection of methodologies that aim to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness, and low solution cost.

     • Tolerance of imprecision means result is not precise

    • Uncertainty means different result at different time
    • Tractability means problem solved with in polynomial time
    • Robustness means it can tackle any sort of input including noise

    Soft Computing is a term applied to a field within computer science which is characterized by the use of inexact solutions to computationally hard task such as solution of NP- Complete problems for which an exact solution can not be derived with in polynomial time.

    Characteristics of Soft Computing:

    • It does not require any mathematical modeling of problem  solving
    • It may not yield the precise solution
    • Algorithms are adaptive (i.e. it can adjust to the change of  dynamic environment)
    • Use some biological inspired methodologies such as genetics,  evolution, Ant’s behaviors, human nervous  systems etc.

    Applications using Soft Computing:

    • Handwriting Recognition
    • Automotive systems and manufacturing
    • Image processing and data recognition
    • Decision support System
    • To Power System
    • Neuro Fuzzy System
    • Fuzzy Logic Control
    • Genetic Algorithms
    • Bio Informatics and Biomedicine

    Components of Soft Computing includes:

    • Neural Networks (NN)
    • Fuzzy System or Fuzzy Logic
    • Genetic Algorithm (Evolutionary Computing)

    Reference books:

    1. S. Rajsekaran & G.A. Vijayalakshmi Pai, “Neural Networks,Fuzzy Logic and Genetic Algorithm:Synthesis and Applications” Prentice Hall of India.

    2. Dr. S.N Sivanandam & Dr. S.N Deepa “Principles of Soft Computing” Wiley



    1. Implementation of Stop and Wait Protocol and Sliding Window Protocol.

    2.Study of Socket Programming and Client – Server model

    3.Write a code simulating ARP /RARP protocols.

    4.Write a code simulating PING and TRACEROUTE commands

    5.Create a socket for HTTP for web page upload and download.

    6.Write a program to implement RPC (Remote Procedure Call)

    7.Implementation of Subnetting .

    8.Applications using TCP Sockets like

    a.Echo client and echo server b. Chat c. File Transfer

    9.Applications using TCP and UDP Sockets like d. DNS e. SNMP f. File Transfer

    10.Study of Network simulator (NS).and Simulation of Congestion Control Algorithms using NS

    11.Perform a case study about the different routing algorithms to select the network path with its optimum andeconomical during data transfer. i. Link State routing ii. Flooding iii. Distance vector

    12.To learn handling and configuration of networking hardware like RJ-45 connector, CAT-6 cable, crimping tool, etc.

    13.Configuration of router, hub, switch etc. (using real devices or simulators)

    14.Running and using services/commands like ping, traceroute, nslookup, arp, telnet, ftp, etc.

    15.Network packet analysis using tools like Wireshark, tcpdump, etc.

    16.Network simulation using tools like Cisco Packet Tracer, NetSim, OMNeT++, NS2, NS3, etc.

    17.Socket programming using UDP and TCP (e.g., simple DNS, data & time client/server, echo client/server, iterative &concurrent servers)


    I

    ntroductory Concepts: Goals and applications of networks, Categories of networks, Organization of the Internet, ISP, Network structure and architecture (layering principles, services, protocols and standards), The OSI reference model, TCP/IP protocol suite, Network devices and components.

    Physical Layer:

    Network topology design, Types of connections, Transmission media, Signal transmission and encoding, Network performance and transmission impairments, Switching techniques and multiplexing.

    II

    Link layer: Framing, Error Detection and Correction, Flow control (Elementary Data Link Protocols, Sliding Window protocols).

    Medium Access Control and Local Area Networks: Channel allocation, Multiple access protocols, LAN standards, Link layer switches & bridges (learning bridge and spanning tree algorithms).

    III

    Network Layer: Point-to-point networks, Logical addressing, Basic internetworking (IP, CIDR, ARP, RARP, DHCP, ICMP), Routing, forwarding and delivery, Static and dynamic routing, Routing algorithms and protocols, Congestion control algorithms, IPv6.

    IV

    Transport Layer: Process-to-process delivery, Transport layer protocols (UDP and TCP), Multiplexing, Connection management, Flow control and retransmission, Window management, TCP Congestion control, Quality of service.

    V

    Application Layer: Domain Name System, World Wide Web and Hyper Text Transfer Protocol, Electronic mail, File Transfer Protocol, Remote login, Network management, Data compression, Cryptography – basic concepts.

    Introduction and Web

    Core Java

    Web Page Designing: HTML, CSS, XML

    Networking & Scripting: JavaScript

    Enterprise Java Bean & JDBC

    Servlets & Java Server Pages


    Object Oriented System Design (KCS-054)

    Course Outcome ( CO)

    Bloom’s Knowledge Level (KL)

    At the end of course , the student will be able to understand

    CO 1

    To Understand the application development and analyze the insights of object oriented programming to implement application

    K2, K4

    CO 2

    To Understand, analyze and apply the role of overall modeling concepts (i.e. System,

    structural)

    K2, K3

    CO 3

    To Understand, analyze and apply oops concepts (i.e. abstraction, inheritance)

    K2, K3, K4

    CO 4

    To learn concepts of C++ for understanding the implementation of object oriented concepts

    K2, K3

    CO 5

    To learn the programming concepts to implement object oriented modeling.

    K2, K3

    DETAILED SYLLABUS

    3-0-0

    Unit

    Topic

    Proposed

    Lecture

     

    I

    Introduction:  The  meaning  of  Object  Orientation,  object  identity,    Encapsulation, information hiding, polymorphism, generosity, importance of modelling, principles of modelling, object oriented

    modelling, Introduction to UML, conceptual model of the UML, Architecture.

     

    08

     

     

     

    II

    Basic Structural Modeling: Classes, Relationships, common Mechanisms, and diagrams. Class &Object Diagrams: Terms, concepts, modelling techniques for Class & Object Diagrams.

    Collaboration Diagrams: Terms, Concepts, depicting a message, polymorphism in collaboration Diagrams, iterated messages, use of self in messages. Sequence Diagrams: Terms, concepts, depicting asynchronous messages with/without priority, call-back mechanism, broadcast messages.

    Basic Behavioural Modeling: Use cases, Use case Diagrams, Activity Diagrams, State Machine , Process and thread, Event and signals, Time diagram, interaction diagram, Package diagram.

    Architectural Modeling: Component, Deployment, Component diagrams and Deployment diagrams.

     

     

     

    08

    III

    Object Oriented Analysis: Object oriented design, Object design, Combining three models, Designing

    08


     

    algorithms, design optimization, Implementation of control, Adjustment of inheritance, Object representation, Physical packaging, Documenting design considerations.

    Structured analysis and structured design (SA/SD), Jackson Structured Development (JSD).Mapping object oriented concepts using non-object oriented language, Translating classes into data structures, Passing arguments to methods, Implementing inheritance, associations encapsulation. Object oriented programming style: reusability, extensibility, robustness, programming in the

    large. Procedural v/s OOP, Object oriented language features. Abstraction and Encapsulation.

     

     

    IV

    C++ Basics : Overview, Program structure, namespace, identifiers, variables, constants, enum, operators, typecasting, control structures

    C++ Functions : Simple functions, Call and Return by reference, Inline functions, Macro Vs. Inline

    functions, Overloading of functions, default arguments, friend functions, virtual functions

     

    08

     

     

    V

    Objects and Classes : Basics of object and class in C++, Private and public members, static data and function members, constructors and their types, destructors, operator overloading, type conversion. Inheritance : Concept of Inheritance, types of inheritance: single, multiple, multilevel, hierarchical, hybrid, protected members, overriding, virtual base class

    Polymorphism : Pointers in C++, Pointes and Objects, this pointer, virtual and pure virtual

    functions, Implementing polymorphism

     

     

    08

    Text Books

    1.     James Rumbaugh et. al, “Object Oriented Modeling and Design”, PHI

    2.     Grady Booch, James Rumbaugh, Ivar Jacobson, “The Unified Modeling Language User Guide”, Pearson Education

    3.     Object Oriented Programming With C++, E Balagurusamy, TMH

    4.     C++ Programming, Black Book, Steven Holzner, dreamtech

    5.     Object Oriented Programming in Turbo C++, Robert Lafore, Galgotia

    6.     Object Oriented Programming with ANSI and Turbo C++, Ashok Kamthane, Pearson

    7.     The Compete Reference C++, Herbert Schlitz, TMH

     


    KCS-503: Design and
    Analysis of Algorithm    

    UNIT

    TOPIC

    1

    Introduction: Algorithms, Analyzing Algorithms, Complexity of Algorithms, Growth of Functions, Performance Measurements, Sorting and Order Statistics - Shell Sort, Quick Sort, Merge Sort, Heap Sort, Comparison of Sorting Algorithms, Sorting in Linear Time.

    2

    Advanced Data Structures: Red-Black Trees, B – Trees, Binomial Heaps, Fibonacci Heaps, Tries, Skip List

     

    3

    Divide and Conquer with Examples Such as Sorting, Matrix Multiplication, Convex Hull and Searching. Greedy Methods with Examples Such as Optimal Reliability Allocation, Knapsack, Minimum Spanning Trees – Prim’s and Kruskal’s Algorithms, Single Source Shortest Paths - Dijkstra’s and Bellman Ford Algorithms

     

    4

    Dynamic Programming with Examples Such as Knapsack. All Pair Shortest Paths – Warshal’s and Floyd’s Algorithms, Resource Allocation Problem. Backtracking, Branch and Bound with Examples Such as Travelling Salesman Problem, Graph Coloring, n-Queen Problem, Hamiltonian Cycles and Sum of Subsets.

     

    5

    Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NP-Completeness, Approximation Algorithms and Randomized Algorithms

     

    References:

    1. Thomas H. Coreman, Charles E. Leiserson and Ronald L. Rivest, “Introduction to Algorithms”, Printice Hall of India.

    2. E. Horowitz & S Sahni, "Fundamentals of Computer Algorithms",

    3. Aho, Hopcraft, Ullman, “The Design and Analysis of Computer Algorithms” Pearson Education, 2008.

    4. LEE "Design & Analysis of Algorithms (POD)",McGraw Hill

    5. Gajendra Sharma, Design & Analysis of Algorithms, Khanna Publishing House

    6. Richard E.Neapolitan "Foundations of Algorithms" Jones & Bartlett Learning

    7. Jon Kleinberg and Éva Tardos, Algorithm Design, Pearson, 2005.

    8. Michael T Goodrich and Roberto Tamassia, Algorithm Design: Foundations, Analysis, and Internet Examples, Second Edition, Wiley, 2006.

    9. Harry R. Lewis and Larry Denenberg, Data Structures and Their Algorithms, Harper Collins, 1997

    10. Robert Sedgewick and Kevin Wayne, Algorithms, fourth edition, Addison Wesley, 2011.

    11. Harsh Bhasin,”Algorithm Design and Analysis”,First Edition,Oxford University Press.

    12. Gilles Brassard and Paul Bratley,Algorithmics:Theory and Practice,Prentice Hall,1995.

           
     
     
     

    • Recognize the feasibility of applying a soft computing methodology for a particular problem
    • Know the concepts and techniques of soft computing and foster their abilities in designing and implementing soft computing based solutions for real-world and engineering problems.
    • Apply  neural  networks  to  pattern  classification  and  regression  problems         and  compare solutions by various soft computing approaches for a given problem.



    CO 4         Apply fuzzy logic and reasoning to handle uncertainty and solve engineering problems                     K3, K4

    CO 5        Apply genetic algorithms to combinatorial optimization problems                                                          

    In this subject we will be discussing about various phases of compiler

    Syllabus

    UNIT I

    Introduction: Algorithms, Analyzing Algorithms, Complexity of Algorithms, Growth of Functions, Performance Measurements, Sorting and Order Statistics - Shell Sort, Quick Sort, Merge Sort, Heap Sort, Comparison of Sorting Algorithms, Sorting in Linear Time.

    UNIT-II

    Advanced Data Structures: Red-Black Trees, B – Trees, Binomial Heaps, Fibonacci Heaps, Tries, Skip List

    UNIT-III

    Divide and Conquer with Examples Such as Sorting, Matrix Multiplication, Convex Hull and Searching. Greedy Methods with Examples Such as Optimal Reliability Allocation, Knapsack, Minimum Spanning Trees – Prim’s and Kruskal’s Algorithms, Single Source Shortest Paths - Dijkstra’s and Bellman Ford Algorithms.

    UNIT IV

    Dynamic Programming with Examples Such as Knapsack. All Pair Shortest Paths – Warshal’s and Floyd’s Algorithms, Resource Allocation Problem. Backtracking, Branch and Bound with Examples Such as Travelling Salesman Problem, Graph Coloring, n-Queen Problem, Hamiltonian Cycles and Sum of Subsets.

    UNIT V

    Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NPCompleteness, Approximation Algorithms and Randomized Algorithms

    Text Books:

    1. Thomas H. Coreman, Charles E. Leiserson and Ronald L. Rivest, “Introduction to Algorithms”, Printice Hall of India. 

    2. E. Horowitz & S Sahni, "Fundamentals of Computer Algorithms",

     3. Aho, Hopcraft, Ullman, “The Design and Analysis of Computer Algorithms” Pearson Education, 2008.

     4. LEE "Design & Analysis of Algorithms (POD)",McGraw Hill

     5. Richard E.Neapolitan "Foundations of Algorithms" Jones & Bartlett Learning

     6. Jon Kleinberg and Éva Tardos, Algorithm Design, Pearson, 2005. 

    7. Michael T Goodrich and Roberto Tamassia, Algorithm Design: Foundations, Analysis, and Internet Examples, Second Edition, Wiley, 2006. 

    8. Harry R. Lewis and Larry Denenberg, Data Structures and Their Algorithms, Harper Collins, 1997 

    9. Robert Sedgewick and Kevin Wayne, Algorithms, fourth edition, Addison Wesley, 2011.

     10. Harsh Bhasin,”Algorithm Design and Analysis”,First Edition,Oxford University Press. 

    11. Gilles Brassard and Paul Bratley,Algorithmics:Theory and Practice,Prentice Hall,1995

    Database Management System (KCS501)

    Course Outcome ( CO)

    Bloom’s Knowledge Level (KL)

    At the end of course , the student will be able to understand

    CO 1

    Apply knowledge of database for real life applications.

    K3

    CO 2

    Apply query processing techniques to automate the real time problems of databases.

    K3, K4

    CO 3

    Identify and solve the redundancy problem in database tables using normalization.

    K2, K3

    CO 4

    Understand the concepts of transactions, their processing so they will familiar with broad range

    of database management issues including data integrity, security and recovery.

    K2, K4

    CO 5

    Design, develop and implement a small database project using database tools.

    K3, K6

    DETAILED SYLLABUS

    3-1-0

    Unit

    Topic

    Proposed

    Lecture

     

     

    I

    Introduction: Overview, Database System vs File System, Database System Concept and Architecture, Data Model Schema and Instances, Data Independence and Database Language and Interfaces, Data Definitions Language, DML, Overall Database Structure. Data Modeling Using the Entity Relationship Model: ER Model Concepts, Notation for ER Diagram, Mapping Constraints, Keys, Concepts of Super Key, Candidate Key, Primary Key, Generalization, Aggregation,

    Reduction of an ER Diagrams to Tables, Extended ER Model, Relationship of Higher Degree.

     

     

    08

     

     

     

    II

    Relational data Model and Language: Relational Data Model Concepts, Integrity Constraints, Entity Integrity, Referential Integrity, Keys Constraints, Domain Constraints, Relational Algebra, Relational Calculus, Tuple and Domain Calculus. Introduction on SQL: Characteristics of SQL, Advantage of SQL. SQl Data Type and Literals. Types of SQL Commands. SQL Operators and Their Procedure. Tables, Views and Indexes. Queries and Sub Queries. Aggregate Functions. Insert, Update and Delete Operations, Joins, Unions, Intersection, Minus, Cursors, Triggers,

    Procedures in SQL/PL SQL

     

     

     

    08

     

    III

    Data Base Design & Normalization: Functional dependencies, normal forms, first, second, 8 third

    normal forms, BCNF, inclusion dependence, loss less join decompositions, normalization using FD, MVD, and JDs, alternative approaches to database design

     

    08

     

    IV

    Transaction Processing Concept: Transaction System, Testing of Serializability, Serializability of Schedules, Conflict & View Serializable Schedule, Recoverability, Recovery from Transaction Failures, Log Based Recovery, Checkpoints, Deadlock Handling. Distributed Database: Distributed

    Data Storage, Concurrency Control, Directory System.

     

    08

     

    V

    Concurrency Control  Techniques:  Concurrency Control, Locking Techniques for  Concurrency

    Control, Time Stamping Protocols for Concurrency Control, Validation Based Protocol, Multiple Granularity, Multi Version Schemes, Recovery with Concurrent Transaction, Case Study of Oracle.

     

    08

    Text books:

    1.      Korth, Silbertz, Sudarshan,” Database Concepts”, McGraw Hill

    2.     Date C J, “An Introduction to Database Systems”, Addision Wesley

    3.     Elmasri, Navathe, “ Fundamentals of Database Systems”, Addision Wesley

    4.     O’Neil, Databases, Elsevier Pub.

    5.     RAMAKRISHNAN"Database Management Systems",McGraw Hill

    6.     Leon & Leon,”Database Management Systems”, Vikas Publishing House

    7.     Bipin C. Desai, “ An Introduction to Database Systems”, Gagotia Publications

    8.     Majumdar & Bhattacharya, “Database Management System”, TMH


    CO 1 Recognize the feasibility of applying a soft computing methodology for a particular problem 

    CO 2 Understand the concepts and techniques of soft computing and foster their abilities in designing and implementing soft computing based solutions for real-world and engineering problems. 

    CO 3 Apply neural networks to pattern classification and regression problems and compare solutions by various soft computing approaches for a given problem. 

    CO 4 Apply fuzzy logic and reasoning to handle uncertainty and solve engineering problems .

    CO 5 Apply genetic algorithms to combinatorial optimization problems 

    • Python is ranked as the 6th popular language by Stack Overflow Developer Survey and ranked as the 4th most wanted technology of the year 2016.
    • It is the 2nd most popular programming language in the world based on the Popularity of Programming Language Index. 
    • Python is used in many domains  fields from web and game development to machine learning, AI, scientific computing and academic research. It is easy to learn as a first language.  Hence, the course covers the basic of Python Programming in detail and the advanced concepts in a lighter way. 
    • The course would definitely kindle the students’ interest for further exploration


    IN THIS COURSE WE WILL DISCUSS ABOUT VARIOUS SECURITY METHODS HOW THE SECURITY HAS BEEN EVOLVED AND VARIOUS TYPES OF ATTACKS.

    Topics include elementary data structures, (including arrays, stacks, queues, and lists), advanced data structures (including trees and graphs), the algorithms used to manipulate these structures, and their application to solving practical engineering problems.

    In this course we will study about all of us. It presents a set of proposals so that we may start exploring our own self and our expanse of living in order to better understand our life - so we can understand what is valuable for us, what is our 'value' in the larger scheme of things we live in. We live in human society, in nature and we want to find out our role in this expanse. 

    SYLLABUS

    Module I: Partial Differential Equations

    Origin of Partial Differential Equations, Linear and Non Linear Partial Equations of first order,

    Lagrange’s Equations, Charpit’s method, Cauchy’s method of Characteristics, Solution of Linear

    Partial Differential Equation of Higher order with constant coefficients, Equations reducible to

    linear partial differential equations with constant coefficients.

    Module II: Applications of Partial Differential Equations:

    Classification of linear partial differential equation of second order, Method of separation of

    variables, Solution of wave and heat conduction equation up to two dimension, Laplace equation

    in two dimensions, Equations of Transmission lines.

    Module III: Statistical Techniques I:

    Introduction: Measures of central tendency, Moments, Moment generating function (MGF) ,

    Skewness, Kurtosis, Curve Fitting , Method of least squares, Fitting of straight lines, Fitting of

    second degree parabola, Exponential curves ,Correlation and Rank correlation, Regression

    Analysis: Regression lines of y on x and x on y, regression coefficients, properties of regressions

    coefficients and non linear regression.

    Module IV: Statistical Techniques II:

    Probability and Distribution: Introduction, Addition and multiplication law of probability,

    Conditional probability, Baye’s theorem, Random variables (Discrete and Continuous Random

    variable) Probability mass function and Probability density function, Expectation and variance,

    Discrete and Continuous Probability distribution: Binomial, Poission and Normal distributions.

    Module V: Statistical Techniques III:

    Sampling, Testing of Hypothesis and Statistical Quality Control: Introduction , Sampling

    Theory (Small and Large) , Hypothesis, Null hypothesis, Alternative hypothesis, Testing a

    Hypothesis, Level of significance, Confidence limits, Test of significance of difference of means,

    T-test, F-test and Chi-square test, One way Analysis of Variance (ANOVA).Statistical Quality

    Control (SQC) , Control Charts , Control Charts for variables ( X and R Charts), Control Charts

    for Variables ( p, np and C charts).

    Text Books

    1. Erwin Kreyszig, Advanced Engineering Mathematics, 9thEdition, John Wiley &

    Sons, 2006.

    2. P. G. Hoel, S. C. Port and C. J. Stone, Introduction to Probability Theory,

    Universal Book Stall, 2003(Reprint).

    3. S. Ross: A First Course in Probability, 6th Ed., Pearson Education India, 2002.

    4. W. Feller, An Introduction to Probability Theory and its Applications, Vol. 1, 3rd

    Ed., Wiley, 1968.

    Reference Books

    1. B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers, 35th Edition, 2000.

    2. T.Veerarajan : Engineering Mathematics (for semester III), Tata McGraw-Hill, New

    Delhi.

    3. R.K. Jain and S.R.K. Iyenger: Advance Engineering Mathematics; Narosa Publishing

    House, New Delhi.

    4. J.N. Kapur: Mathematical Statistics; S. Chand & Sons Company Limited, New Delhi.

    5. D.N.Elhance,V. Elhance & B.M. Aggarwal: Fundamentals of Statistics; Kitab Mahal

    Distributers, New Delhi.

    Unit 1

    Basic Concepts and Automata Theory: Introduction to Theory of Computation- Automata, Computability and Complexity, Alphabet, Symbol, String, Formal Languages, Deterministic Finite Automaton (DFA)- Definition, Representation, Acceptability of a String and Language, Non Deterministic Finite Automaton (NFA), Equivalence of DFA and NFA, NFA with ε-Transition, Equivalence of NFA’s with and without ε-Transition, Finite Automata with output- Moore Machine, Mealy Machine, Equivalence of Moore and Mealy Machine, Minimization of Finite Automata, Myhill-Nerode Theorem, Simulation of DFA and NFA 

    Unit 2

    Regular Expressions and Languages: Regular Expressions, Transition Graph, Kleen’s Theorem, Finite Automata and Regular Expression- Arden’s theorem, Algebraic Method Using Arden’s Theorem, Regular and Non-Regular Languages- Closure properties of Regular Languages, Pigeonhole Principle, Pumping Lemma, Application of Pumping Lemma, Decidability- Decision properties, Finite Automata and Regular Languages, Regular Languages and Computers, Simulation of Transition Graph and Regular language. 

    Unit 3

    Regular and Non-Regular Grammars: Context Free Grammar(CFG)-Definition, Derivations, Languages, Derivation Trees and Ambiguity, Regular Grammars-Right Linear and Left Linear grammars, Conversion of FA into CFG and Regular grammar into FA, Simplification of CFG, Normal Forms- Chomsky Normal Form(CNF), Greibach Normal Form (GNF), Chomsky Hierarchy, Programming problems based on the properties of CFGs. 

    Unit 4

    Push Down Automata and Properties of Context Free Languages: Nondeterministic Pushdown Automata (NPDA)- Definition, Moves, A Language Accepted by NPDA, Deterministic Pushdown Automata(DPDA) and Deterministic Context free Languages(DCFL), Pushdown Automata for Context Free Languages, Context Free grammars for Pushdown Automata, Two stack Pushdown Automata, Pumping Lemma for CFL, Closure properties of CFL, Decision Problems of CFL, Programming problems based on the properties of CFLs. 

    Unit 5

    Turing Machines and Recursive Function Theory : Basic Turing Machine Model, Representation of Turing Machines, Language Acceptability of Turing Machines, Techniques for Turing Machine Construction, Modifications of Turing Machine, Turing Machine as Computer of Integer Functions, Universal Turing machine, Linear Bounded Automata, Church’s Thesis, Recursive and Recursively Enumerable language, Halting Problem, Post’s Correspondance Problem, Introduction to Recursive Function Theory.

    In this course we will study about all of us. It presents a set of proposals so that we may start exploring our own self and our expanse of living in order to better understand our life - so we can understand what is valuable for us, what is our 'value' in the larger scheme of things we live in. We live in human society, in nature and we want to find out our role in this expanse. 

    IN THIS COURSE WE WILL DISCUSS ABOUT VARIOUS TYPE OF SECURITY METHODS AND HOW THEY EVOLVED

    In this course we will study about all of us. It presents a set of proposals so that we may start exploring our own self and our expanse of living in order to better understand our life - so we can understand what is valuable for us, what is our 'value' in the larger scheme of things we live in. We live in human society, in nature and we want to find out our role in this expanse. 

    Subject:- Mathematics-IV ( KAS-302)

    SYLLABUS

    Unit-I( Partial differential equations)

    Origin of Partial Differential Equations, Linear and Non Linear Partial Equations of first order, Lagrange’s Equations, Charpit’s method, Cauchy’s method of Characteristics, Solution of Linear Partial Differential Equation of Higher order with constant coefficients, Equations reducible to linear partial differential equations with constant coefficients.

    Unit-II (Applications of Partial differential equations)

    Classification of linear partial differential equation of second order, Method of separation of variables, Solution of wave and heat conduction equation up to two dimension, Laplace equation in two dimensions, Equations of Transmission lines.

     

    Unit-III (Statistical Techniques-I)

     Introduction: Measures of central tendency, Moments, Moment generating function (MGF) , Skewness, Kurtosis, Curve Fitting , Method of least squares, Fitting of straight lines, Fitting of second degree parabola, Exponential curves ,Correlation and Rank correlation, Regression Analysis: Regression lines of y on x and x on y, regression coefficients, properties of regressions coefficients and non linear regression

    Unit-IV(Statistical Techniques-II)

    Probability and Distribution: Introduction, Addition and multiplication law of probability, Conditional probability, Baye’s theorem, Random variables (Discrete and Continuous Random variable) Probability mass function and Probability density function, Expectation and variance, Discrete and Continuous Probability distribution: Binomial, Poission and Normal distributions.

    Unit-V (Statistical Techniques-III)

    Introduction , Sampling Theory (Small and Large) , Hypothesis, Null hypothesis, Alternative hypothesis, Testing a Hypothesis, Level of significance, Confidence limits, Test of significance of difference of means, T-test, F-test and Chi-square test, One way Analysis of Variance (ANOVA).Statistical Quality

    Control (SQC) , Control Charts , Control Charts for variables ( X and R Charts), Control Charts for Variables ( p, np and C charts).

    Text Books

    1. Erwin Kreyszig, Advanced Engineering Mathematics, 9thEdition, John Wiley & Sons, 2006.

    2. P. G. Hoel, S. C. Port and C. J. Stone, Introduction to Probability Theory, Universal Book Stall, 2003(Reprint).

    3. S. Ross: A First Course in Probability, 6th Ed., Pearson Education India, 2002.

    4. W. Feller, An Introduction to Probability Theory and its Applications, Vol. 1, 3rd Ed., Wiley, 1968.

     

    Reference Books

    1. B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers, 35th Edition, 2000. 2.T.Veerarajan : Engineering Mathematics (for semester III), Tata McGraw-Hill, New Delhi.

    3. R.K. Jain and S.R.K. Iyenger: Advance Engineering Mathematics; Narosa Publishing House, New Delhi.

    4. J.N. Kapur: Mathematical Statistics; S. Chand & Sons Company Limited, New Delhi.

    5. D.N.Elhance, V. Elhance & B.M. Aggarwal: Fundamentals of Statistics; Kitab Mahal Distributers, New Delhi.

     

     

     

     


    OBJECTIVE                                                                                                                              The objective of the course is four-fold:                                                                              Development of a holistic perspective based on self-exploration about themselves (human being), family, society, and nature/existence.                                                             Understanding (or developing clarity) of the harmony in the human being, family, society, and nature/existence                                                                                                Strengthening of self-reflection.                                                                                          Development of commitment and courage to act

    IN THIS COURSE WE WILL DISCUSS ABOUT VARIOUS SECURITY METHODS HOW THEY EVOLVED AND VARIOUS TYPES OF ATTACKS

    In this course we will study about all of us. It presents a set of proposals so that we may start exploring our own self and our expanse of living in order to better understand our life - so we can understand what is valuable for us, what is our 'value' in the larger scheme of things we live in. We live in human society, in nature and we want to find out our role in this expanse. 

    Subject:- Mathematics-IV ( KAS-302)

    SYLLABUS

    Unit-I( Partial differential equations)

    Origin of Partial Differential Equations, Linear and Non Linear Partial Equations of first order, Lagrange’s Equations, Charpit’s method, Cauchy’s method of Characteristics, Solution of Linear Partial Differential Equation of Higher order with constant coefficients, Equations reducible to linear partial differential equations with constant coefficients.

    Unit-II (Applications of Partial differential equations)

    Classification of linear partial differential equation of second order, Method of separation of variables, Solution of wave and heat conduction equation up to two dimension, Laplace equation in two dimensions, Equations of Transmission lines.

     

    Unit-III (Statistical Techniques-I)

     Introduction: Measures of central tendency, Moments, Moment generating function (MGF) , Skewness, Kurtosis, Curve Fitting , Method of least squares, Fitting of straight lines, Fitting of second degree parabola, Exponential curves ,Correlation and Rank correlation, Regression Analysis: Regression lines of y on x and x on y, regression coefficients, properties of regressions coefficients and non linear regression

    Unit-IV(Statistical Techniques-II)

    Probability and Distribution: Introduction, Addition and multiplication law of probability, Conditional probability, Baye’s theorem, Random variables (Discrete and Continuous Random variable) Probability mass function and Probability density function, Expectation and variance, Discrete and Continuous Probability distribution: Binomial, Poission and Normal distributions.

    Unit-V (Statistical Techniques-III)

    Introduction , Sampling Theory (Small and Large) , Hypothesis, Null hypothesis, Alternative hypothesis, Testing a Hypothesis, Level of significance, Confidence limits, Test of significance of difference of means, T-test, F-test and Chi-square test, One way Analysis of Variance (ANOVA).Statistical Quality

    Control (SQC) , Control Charts , Control Charts for variables ( X and R Charts), Control Charts for Variables ( p, np and C charts).

    Text Books

    1. Erwin Kreyszig, Advanced Engineering Mathematics, 9thEdition, John Wiley & Sons, 2006.

    2. P. G. Hoel, S. C. Port and C. J. Stone, Introduction to Probability Theory, Universal Book Stall, 2003(Reprint).

    3. S. Ross: A First Course in Probability, 6th Ed., Pearson Education India, 2002.

    4. W. Feller, An Introduction to Probability Theory and its Applications, Vol. 1, 3rd Ed., Wiley, 1968.

     

    Reference Books

    1. B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers, 35th Edition, 2000. 2.T.Veerarajan : Engineering Mathematics (for semester III), Tata McGraw-Hill, New Delhi.

    3. R.K. Jain and S.R.K. Iyenger: Advance Engineering Mathematics; Narosa Publishing House, New Delhi.

    4. J.N. Kapur: Mathematical Statistics; S. Chand & Sons Company Limited, New Delhi.

    5. D.N.Elhance, V. Elhance & B.M. Aggarwal: Fundamentals of Statistics; Kitab Mahal Distributers, New Delhi.


    Topics include elementary data structures, (including arrays, stacks, queues, and lists), advanced data structures (including trees and graphs), the algorithms used to manipulate these structures, and their application to solving practical engineering problems.

    OBJECTIVE: The objective of the course is four-fold:                                                      Development of a holistic perspective based on self-exploration about themselves (human being), family, society, and nature/existence.                                                              Understanding (or developing clarity) of the harmony in the human being, family, society, and nature/existence                                                                                                    Strengthening of self-reflection.                                                                                      Development of commitment and courage to act.

    UNIT I: Introduction [08]

    Introduction: Functional units of digital system and their interconnections, buses, bus architectureTypes of buses and bus arbitration, Register, bus and memory transfer, Processor organization, General registers organization, stack organization and addressing modes.

    UNIT II: Arithmetic and Logic Unit [08]

    Arithmetic and logic unit: Look ahead carries adders. Multiplication: Signed operand multiplication, Booths algorithm and array multiplier, Division and logic operations, floating point arithmetic operation, Arithmetic & logic unit design, IEEE Standard for Floating Point Numbers.

    UNIT III: Control Unit [08]

    Control Unit: Instruction types, formats, instruction cycles and sub cycles (Fetch and execute etc.), micro-operations, execution of a complete instruction, Program Control, Reduced Instruction Set Computer, Pipelining, Hardwired and micro programmed control: microprogrammed sequencing, concept of horizontal and vertical microprogramming.

    UNIT IV: Memory [08]

    Memory: Basic concept and hierarchy, semiconductor RAM memories, 2D & 2 1/2D memory organization. ROM memories, Cache memories: concept and design issues performance, address mapping and replacement, Auxiliary memories: magnetic disk, magnetic tape and optical disks, Virtual memory: concept implementation.

    UNIT V: Input/Output [08]

    Input / Output: Peripheral devices, I/O interface, I/O ports, Interrupts: interrupt hardware, types of interrupts and exceptions, Modes of Data Transfer: Programmed I/O, interrupt initiated I/O and Direct Memory Access, I/O channels and processors, Serial Communication: Synchronous & asynchronous communication, standard communication interfaces.


    TEXT BOOK:

    1. Computer System Architecture - M. Mano

    2. Carl Hamacher, Zvonko Vranesic, Safwat Zaky Computer Organization, McGraw-Hill, Fifth Edition, Reprint 2012

    3. John P. Hayes, Computer Architecture and Organization, Tata McGraw Hill, Third Edition, 1998. Reference books

    4. William Stallings, Computer Organization and Architecture-Designing for Performance, Pearson Education, Seventh edition, 2006.

    5. Behrooz Parahami, “Computer Architecture”, Oxford University Press, Eighth Impression, 2011.

    6. David A. Patterson and John L. Hennessy, “Computer Architecture-A Quantitative Approach”, Elsevier, a division of reed India Private Limited, Fifth edition, 2012

    7. Structured Computer Organization, Tannenbaum(PHI)

    ROE081 DIGITAL AND SOCIAL MEDIA MARKETING L T P 3 0 0 

     UNIT-I Introduction to Digital Marketing: The new digital world - trends that are driving shifts from traditional marketing practices to digital marketing practices, the modern digital consumer and new consumer’s digital journey. Marketing strategies for the digital world-latest practices. 

     UNIT-II Social Media Marketing -Introduction to Blogging, Create a blog post for your project. Include headline, imagery, links and post, Content Planning and writing. Introduction to Face book, Twitter, Google +, LinkedIn, YouTube, Instagram and Pinterest; their channel advertising and campaigns. 

     UNIT-III Acquiring & Engaging Users through Digital Channels: Understanding the relationship between content and branding and its impact on sales, search engine marketing, mobile marketing, video marketing, and social-media marketing. Marketing gamification, Online campaign management; using marketing analytic tools to segment, target and position; overview of search engine optimization (SEO). 

    UNIT-IV Designing Organization for Digital Success: Digital transformation, digital leadership principles, online P.R. and reputation management. ROI of digital strategies, how digital marketing is adding value to business, and evaluating cost effectiveness of digital strategies. 

     UNIT-V Digital Innovation and Trends: The contemporary digital revolution, digital transformation framework; security and privatization issues with digital marketing Understanding trends in digital marketing – Indian and global context, online communities and co-creation, 

    Text books: 

     1. Moutsy Maiti: Internet Mareting, Oxford University Press India 

     2. Vandana, Ahuja; Digital Marketing, Oxford University Press India (November, 2015). 

     3. Eric Greenberg, and Kates, Alexander; Strategic Digital Marketing: Top Digital Experts Share the Formula for Tangible Returns on Your Marketing Investment; McGraw-Hill Professional (October, 2013). 

     4. Ryan, Damian; Understanding Digital Marketing: marketing strategies for engaging the digital generation; Kogan Page (3rd Edition, 2014). 

     5. Tracy L. Tuten & Michael R. Solomon: Social Media Marketing (Sage Publication)

    UNIT – 1:

    Introduction to security attacks, services and mechanism, Classical encryption techniques- substitution ciphers and transposition ciphers, cryptanalysis, steganography, Stream and block ciphers. Modern Block Ciphers: Block ciphers principles, Shannon’s theory of confusion and diffusion, fiestal structure, Data encryption standard (DES), Strength of DES, Idea of differential cryptanalysis, block cipher modes of operations, Triple DES

     

    UNIT – 2:

    Introduction to group, field, finite field of the form GF(p), modular arithmetic, prime and relative prime numbers, Extended Euclidean Algorithm, Advanced Encryption Standard (AES) encryption and decryption, Fermat’s and Euler’s theorem, Primarily testing, Chinese Remainder theorem, Discrete Logarithmic Problem, Principals of public key crypto systems, RSA algorithm, security of RSA.

     

    UNIT – 3:

    Message Authentication Codes: Authentication requirements, authentication functions, message authentication code, hash functions, birthday attacks, security of hash functions, Secure hash algorithm (SHA) Digital Signatures: Digital Signatures, Elgamal Digital Signature Techniques, Digital signature standards (DSS), proof of digital signature algorithm,

    UNIT – 4:

    Key Management and distribution: Symmetric key distribution, Diffie-Hellman Key Exchange, Public key distribution, X.509 Certificates, Public key Infrastructure. Authentication Applications: Kerberos, Electronic mail security: pretty good privacy (PGP), S/MIME.

    UNIT – 5:

    IP Security: Architecture, Authentication header, Encapsulating security payloads, combining security associations, key management. Introduction to Secure Socket Layer, Secure electronic, transaction (SET) System Security: Introductory idea of Intrusion, Intrusion detection, Viruses and related threats, firewalls.


    Unit 1 Introduction: Introduction to Artificial Intelligence, Foundations and History of Artificial Intelligence, Applications of Artificial Intelligence, Intelligent Agents, Structure of Intelligent Agents. Computer vision, Natural Language Possessing. 

    Unit 2 Introduction to Search : Searching for solutions, Uniformed search strategies, Informed search strategies, Local search algorithms and optimistic problems, Adversarial Search, Search for games, Alpha - Beta pruning 

    Unit 3 Knowledge Representation & Reasoning: Propositional logic, Theory of first order logic, Inference in First order logic, Forward & Backward chaining, Resolution, Probabilistic reasoning, Utility theory, Hidden Markov Models (HMM), Bayesian Networks. 

    Unit 4 Machine Learning : Supervised and unsupervised learning, Decision trees, Statistical learning models, Learning with complete data - Naive Bayes models, Learning with hidden data - EM algorithm, Reinforcement learning, 

    Unit 5 Pattern Recognition : Introduction, Design principles of pattern recognition system, Statistical Pattern recognition, Parameter estimation methods - Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA), Classification Techniques – Nearest Neighbor (NN) Rule, Bayes Classifier, Support Vector Machine (SVM), K – means clustering. 

    Text books: 1. Stuart Russell, Peter Norvig, “Artificial Intelligence – A Modern Approach”, Pearson Education 2. Elaine Rich and Kevin Knight, “Artificial Intelligence”, McGraw-Hill 3. E Charniak and D McDermott, “Introduction to Artificial Intelligence”, Pearson Education 4. Dan W. Patterson, “Artificial Intelligence and Expert Systems”, Prentice Hall of India,

    In this Course we would be studying the the features of Blockchain and the algorithms associated to it. 

    Application of Soft Computing is an elective subject for IT 7th Sem students.

    Object Oriented Programming (OOP)

    B.TECH. (INFORMATION TECHNOLOGY AND CSI)
    SIXTH SEMESTER (DETAILED SYLLABUS)
    Software Engineering (KCS-601)
    Course Outcome ( CO)
    At the end of course , the student will be able to
    CO 1:Explain various software characteristics and analyze different software Development Models
    CO 2:Demonstrate the contents of a SRS and apply basic software quality assurance practices to ensure that design, development meet or exceed applicable standards
    CO 3:Compare and contrast various methods for software design.
    CO 4:Formulate testing strategy for software systems, employ techniques such as unit testing, Test driven development and functional testing

    CO 5:Manage software development process independently as well as in teams and make use of Various software management tools for development, maintenance and analysis.


    DETAILED SYLLABUS
    3-1-0
    Unit 1
    Introduction: Introduction to Software Engineering, Software Components, Software Characteristics, Software Crisis, Software Engineering Processes, Similarity and Differences from Conventional Engineering Processes, Software Quality Attributes. Software Development Life Cycle (SDLC) Models: Water Fall Model, Prototype Model, Spiral Model, Evolutionary Development Models, Iterative Enhancement Models.
    08

    Unit II
    Software Requirement Specifications (SRS): Requirement Engineering Process: Elicitation, Analysis, Documentation, Review and Management of User Needs, Feasibility Study, Information Modelling, Data Flow Diagrams, Entity Relationship Diagrams, Decision Tables, SRS Document, IEEE Standards for SRS. Software Quality Assurance (SQA): Verification and Validation, SQA Plans, Software Quality Frameworks, ISO 9000 Models, SEI-CMM Model.
    08
    Unit III
    Software Design: Basic Concept of Software Design, Architectural Design, Low Level Design: Modularization, Design Structure Charts, Pseudo Codes, Flow Charts, Coupling and Cohesion Measures, Design Strategies: Function Oriented Design, Object Oriented Design, Top-Down and Bottom-Up Design. Software Measurement and Metrics: Various Size Oriented Measures: Halestead’s Software Science, Function Point (FP) Based Measures, Cyclomatic Complexity Measures: Control Flow Graphs.
    08
    Unit IV
    Software Testing: Testing Objectives, Unit Testing, Integration Testing, Acceptance Testing, Regression Testing, Testing for Functionality and Testing for Performance, TopDown and Bottom-Up Testing Strategies: Test Drivers and Test Stubs, Structural Testing (White Box Testing), Functional Testing (Black Box Testing), Test Data Suit Preparation, Alpha and Beta Testing of Products. Static Testing Strategies: Formal Technical Reviews (Peer Reviews), Walk Through, Code Inspection, Compliance with Design and Coding Standards.
    08
    Unit V
    Software Maintenance and Software Project Management: Software as an Evolutionary Entity, Need for Maintenance, Categories of Maintenance: Preventive, Corrective and Perfective Maintenance, Cost of Maintenance, Software Re- Engineering, Reverse Engineering. Software Configuration Management Activities, Change Control Process, Software Version Control, An Overview of CASE Tools. Estimation of Various Parameters such as Cost, Efforts, Schedule/Duration, Constructive Cost Models (COCOMO), Resource Allocation Models, Software Risk Analysis and Management.
    08

    Text books:
    1.RS Pressman, Software Engineering: A Practitioners Approach, McGraw Hill.
    2.Pankaj Jalote, Software Engineering, Wiley
    3.Rajib Mall, Fundamentals of Software Engineering, PHI Publication.
    4.KK Aggarwal and Yogesh Singh, Software Engineering, New Age International Publishers.
    5.Ghezzi, M. Jarayeri, D. Manodrioli, Fundamentals of Software Engineering, PHI Publication.
    6.Ian Sommerville, Software Engineering, Addison Wesley.
    7.Kassem Saleh, “Software Engineering”, Cengage Learning.
    8.P fleeger, Software Engineering, Macmillan Publication

    Unit 1-Introduction: Overview, Database System vs File System, Database System Concept and Architecture, Data Model Schema and Instances, Data Independence and Database Language and Interfaces, Data Definitions Language, DML, Overall Database Structure. Data Modeling Using the Entity Relationship Model: ER Model Concepts, Notation for ER Diagram, Mapping Constraints, Keys, Concepts of Super Key, Candidate Key, Primary Key, Generalization, Aggregation, Reduction of an ER Diagrams to Tables, Extended ER Model, Relationship of Higher Degree.

    Unit 2-Relational data Model and Language: Relational Data Model Concepts, Integrity Constraints, Entity Integrity, Referential Integrity, Keys Constraints, Domain Constraints, Relational Algebra, Relational Calculus, Tuple and Domain Calculus. Introduction on SQL: Characteristics of SQL, Advantage of SQL. SQl Data Type and Literals. Types of SQL Commands. SQL Operators and Their Procedure. Tables, Views and Indexes. Queries and Sub Queries. Aggregate Functions. Insert, Update and Delete Operations, Joins, Unions, Intersection, Minus, Cursors, Triggers, Procedures in SQL/PL SQL

    Unit 3-Data Base Design & Normalization: Functional dependencies, normal forms, first, second, 8 third normal forms, BCNF, inclusion dependence, loss less join decompositions, normalization using FD, MVD, and JDs, alternative approaches to database design

    Unit 4-Transaction Processing Concept: Transaction System, Testing of Serializability, Serializability of Schedules, Conflict & View Serializable Schedule, Recoverability, Recovery from Transaction Failures, Log Based Recovery, Checkpoints, Deadlock Handling. Distributed Database: Distributed Data Storage, Concurrency Control, Directory System

    Unit 5-Concurrency Control Techniques: Concurrency Control, Locking Techniques for Concurrency Control, Time Stamping Protocols for Concurrency Control, Validation Based Protocol, Multiple Granularity, Multi Version Schemes, Recovery with Concurrent Transaction, Case Study of Oracle

    Text books:

    1. Korth, Silbertz, Sudarshan,” Database Concepts”, McGraw Hill 

    2. Date C J, “An Introduction to Database Systems”, Addision Wesley 

    3. Elmasri, Navathe, “ Fundamentals of Database Systems”, Addision Wesley 

    4. O’Neil, Databases, Elsevier Pub. 

    5. RAMAKRISHNAN"Database Management Systems",McGraw Hill 

    6. Leon & Leon,”Database Management Systems”, Vikas Publishing House 

    7. Bipin C. Desai, “ An Introduction to Database Systems”, Gagotia Publications 

    8. Majumdar & Bhattacharya, “Database Management System”, TMH


    Syllabus Description

    KCS-402: Theory of Automata & Formal Languages


    UNIT – 1:

     

    Basic Concepts and Automata Theory: Introduction to Theory of Computation- Automata, Computability and Complexity, Alphabet, Symbol, String, Formal Languages, Deterministic Finite Automaton (DFA)- Definition, Representation, Acceptability of a String and Language, Non Deterministic Finite Automaton (NFA), Equivalence of DFA and NFA, NFA with ε-Transition, Equivalence of NFA’s with and without ε-Transition, Finite Automata with output- Moore Machine, Mealy Machine, Equivalence of Moore and Mealy Machine, Minimization of Finite Automata, Myhill-Nerode Theorem, Simulation of DFA and NFA.

     

    UNIT – 2:

    Regular Expressions and Languages: Regular Expressions, Transition Graph, Kleen’s Theorem, Finite Automata and Regular Expression- Arden’s theorem, Algebraic Method Using Arden’s Theorem, Regular and Non-Regular Languages- Closure properties of Regular Languages, Pigeonhole Principle, Pumping Lemma, Application of Pumping Lemma, Decidability- Decision properties, Finite Automata and Regular Languages, Regular Languages and Computers, Simulation of Transition Graph and Regular language.

     

    UNIT – 3:

    Regular and Non-Regular Grammars: Context Free Grammar(CFG)-Definition, Derivations, Languages, Derivation Trees and Ambiguity, Regular Grammars-Right Linear and Left Linear grammars, Conversion of FA into CFG and Regular grammar into FA, Simplification of CFG, Normal Forms- Chomsky Normal Form(CNF), Greibach Normal Form (GNF), Chomsky Hierarchy, Programming problems based on the properties of CFGs.

     

    UNIT – 4:

    Push Down Automata and Properties of Context Free Languages: Nondeterministic Pushdown Automata (NPDA)- Definition, Moves, A Language Accepted by NPDA, Deterministic Pushdown Automata(DPDA) and Deterministic Context free Languages(DCFL), Pushdown Automata for Context Free Languages, Context Free grammars for Pushdown Automata, Two stack Pushdown Automata, Pumping Lemma for CFL, Closure properties of CFL, Decision Problems of CFL, Programming problems based on the properties of CFLs.

     

    UNIT – 5:

    Turing Machines and Recursive Function Theory : Basic Turing Machine Model, Representation of Turing Machines, Language Acceptability of Turing Machines, Techniques for Turing Machine Construction, Modifications of Turing Machine, Turing Machine as Computer of Integer Functions, Universal Turing machine, Linear Bounded Automata, Church’s Thesis, Recursive and Recursively Enumerable language, Halting Problem, Post’s Correspondence Problem, Introduction to Recursive Function Theory.


    Syllabus Description

    KCS-303: Discrete Structures & Theory of Logic

    UNIT – 1:

    Set Theory: Introduction, Combination of sets, Multisets, Ordered pairs. Proofs of some general identities on sets. Relations: Definition, Operations on relations, Properties of relations, Composite Relations, Equality of relations, Recursive definition of relation, Order of relations. Functions: Definition, Classification of functions, Operations on functions, Recursively defined functions. Growth of Functions.

    Natural Numbers: Introduction, Mathematical Induction, Variants of Induction, Induction with Nonzero Base cases. Proof Methods, Proof by counter – example, Proof by contradiction.

    UNIT – 2:

    Algebraic Structures: Definition, Groups, Subgroups and order, Cyclic Groups, Cosets, Lagrange's theorem, Normal Subgroups, Permutation and Symmetric groups, Group Homomorphisms, Definition and elementary properties of Rings and Fields.

    UNIT – 3:

    Lattices: Definition, Properties of lattices – Bounded, Complemented, Modular and Complete lattice. Boolean Algebra: Introduction, Axioms and Theorems of Boolean algebra, Algebraic manipulation of Boolean expressions. Simplification of Boolean Functions, Karnaugh maps, Logic gates, Digital circuits and Boolean algebra.

     

    UNIT – 4:

    Propositional Logic: Proposition, well formed formula, Truth tables, Tautology, Satisfiability, Contradiction, Algebra of proposition, Theory of Inference.

    Predicate Logic: First order predicate, well formed formula of predicate, quantifiers, Inference theory of predicate logic.

    UNIT – 5:

    Trees: Definition, Binary tree, Binary tree traversal, Binary search tree.

    Graphs: Definition and terminology, Representation of graphs, Multigraphs, Bipartite graphs, Planar graphs, Isomorphism and Homeomorphism of graphs, Euler and Hamiltonian paths, Graph coloring, Recurrence Relation & Generating function: Recursive definition of functions, Recursive algorithms, Method of solving recurrences.

    Combinatorics: Introduction, Counting Techniques, Pigeonhole Principle


    1. Students will be enabled to understand the nature and objective of Technical Communication relevant for the work place as Engineers.

    2. Students will utilize the technical writing for the purposes of Technical Communication and its exposure in various dimensions.

    3. Students would imbibe inputs by presentation skills to enhance confidence in face of diverse audience.

    4. Technical communication skills will create a vast know-how of the application of the learning to promote their technical competence.

    5. It would enable them to evaluate their efficacy as fluent & efficient communicators by learning the voice-dynamics.


    CO-1

    The student will be able to fabricate and design MOS transistors using Layout design rules, types & characteristics of MOS Inverters.

    CO-2

    The student will be able to understand the different models of delay estimation and power dissipation

    CO-3

    The student will understand the different sources of power dissipation in CMOS circuit.

    CO-4

    The student will learn to design Lower power CMOS Logic circuits through various scheme and able to design logic circuits layouts for both static and dynamic clocked CMOS circuits.

    Co-5

    The student will learn to design low power CMOS logic circuits through various scheme.


    UNIT-1 Course Introduction - Need, Basic Guidelines, Content and Process for Value Education Understanding the need, basic guidelines, content and process for Value Education, Self-Exploration–what is it? - its content and process; ‘Natural Acceptance’ and Experiential Validation- as the mechanism for self exploration, Continuous Happiness and Prosperity- A look at basic Human Aspirations, Right understanding, Relationship and Physical Facilities- the basic requirements for fulfillment of aspirations of every human being with their correct priority, Understanding Happiness and Prosperity correctly- A critical appraisal of the current scenario, Method to fulfill the above human aspirations: understanding and living in harmony at various levels.

    UNIT-2 Understanding Harmony in the Human Being - Harmony in Myself Understanding human being as a co-existence of the sentient ‘I’ and the material ‘Body’, Understanding the needs of Self (‘I’) and ‘Body’ - Sukh and Suvidha, Understanding the Body as an instrument of ‘I’ (I being the doer, seer and enjoyer), Understanding the characteristics and activities of ‘I’ and harmony in ‘I’, Understanding the harmony of I with the Body: Sanyam and Swasthya; correct appraisal of Physical needs, meaning of Prosperity in detail, Programs to ensure Sanyam and Swasthya.

    UNIT-3 Understanding Harmony in the Family and Society- Harmony in Human-Human Relationship Understanding harmony in the Family- the basic unit of human interaction , Understanding values in human-human relationship; meaning of Nyaya and program for its fulfillment to ensure Ubhay-tripti; Trust (Vishwas) and Respect (Samman) as the foundational values of relationship, Understanding the meaning of Vishwas; Difference between intention and competence, Understanding the meaning of Samman, Difference between respect and differentiation; the other salient values in relationship, Understanding the harmony in the society (society being an extension of family): Samadhan, Samridhi, Abhay, Sah-astitva as comprehensive Human Goals, Visualizing a universal harmonious order in society- Undivided Society (AkhandSamaj), Universal Order (Sarvabhaum Vyawastha )-from family to world family!.

    UNIT-4 Understanding Harmony in the Nature and Existence - Whole existence as Co-existence Understanding the harmony in the Nature, Interconnectedness and mutual fulfillment among the four orders of nature- recyclability and self-regulation in nature, Understanding Existence as Co-existence (Sah-astitva) of mutually interacting units in all-pervasive space, Holistic perception of harmony at all levels of existence.

    UNIT-5 Implications of the above Holistic Understanding of Harmony on Professional Ethics Natural acceptance of human values, Definitiveness of Ethical Human Conduct, Basis for Humanistic Education, Humanistic Constitution and Humanistic Universal Order, Competence in Professional Ethics: a) Ability to utilize the professional competence for augmenting universal human order, b) Ability to identify the scope and characteristics of people-friendly and eco-friendly production systems, technologies and management models, Case studies of typical holistic technologies, management models and production systems, Strategy for transition from the present state to Universal Human Order: a) At the level of individual: as socially and ecologically responsible engineers, technologists and managers, b) At the level of society: as mutually enriching institutions and organizations.

    1. Students will be enabled to understand the nature and objective of Technical Communication relevant for the work place as Engineers.

    2. Students will utilize the technical writing for the purposes of Technical Communication and its exposure in various dimensions.

    3. Students would imbibe inputs by presentation skills to enhance confidence in face of diverse audience.

    4. Technical communication skills will create a vast know-how of the application of the learning to promote their technical competence.

    5. It would enable them to evaluate their efficacy as fluent & efficient communicators by learning the voice-dynamics.

    SENSOR & INSTRUMENTATION (KOE-034)

    ELECTRONIC DEVICES (KEC 301)