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IN THIS COURSE WE WILL STUDY ABOUT VARIOUS TYPES OF ATTACKS THAT CAN OCCOUR IN OUR SYSTEM AND SECURITY MEASURES FOR THOSE ATTACKS
 Teacher: Mr. Manish Kumar CSE FACULTY
Design and Analysis of Algorithm syllabus
UNITI
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.
UNITII
Advanced Data Structures: RedBlack 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, nQueen 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.
 Teacher: Mr. Pramod Kr. Sethy CSE FACULTY
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.
 Teacher: Ms. Sandhya Avasthi CSE FACULTY
Distributed System 7 th sem CSE.
 Teacher: Mr. Rahul Chaturvedi CSE FACULTY
DISTRIBUTED SYSTEM
DETAILED SYLLABUS 310
Unit Topic Proposed
Lecture
Characterization of Distributed Systems: Introduction, Examples of distributed Systems, Resource
sharing and the Web Challenges. Architectural models, Fundamental Models. Theoretical
Foundation for Distributed System: Limitation of Distributed system, absence of global clock,
shared memory, Logical clocks ,Lamport’s & vectors logical clocks. Concepts in Message Passing
Systems: causal order, total order, total causal order, Techniques for Message Ordering, Causal
ordering of messages, global state, termination detection.
Distributed Mutual Exclusion: Classification of distributed mutual exclusion, requirement of
mutual exclusion theorem, Token based and non token based algorithms, performance metric for
distributed mutual exclusion algorithms. Distributed Deadlock Detection: system model, resource
Vs communication deadlocks, deadlock prevention, avoidance, detection & resolution, centralized
dead lock detection, distributed dead lock detection, path pushing algorithms, edge chasing
algorithms.
Agreement Protocols: Introduction, System models, classification of Agreement Problem,
Byzantine agreement problem, Consensus problem, Interactive consistency Problem, Solution to
Byzantine Agreement problem, Application of Agreement problem, Atomic Commit in Distributed
Database system. Distributed Resource Management: Issues in distributed File Systems,
Mechanism for building distributed file systems, Design issues in Distributed Shared Memory,
Algorithm for Implementation of Distributed Shared Memory.
Failure Recovery in Distributed Systems: Concepts in Backward and Forward recovery, Recovery in
Concurrent systems, Obtaining consistent Checkpoints, Recovery in Distributed Database Systems.
Fault Tolerance: Issues in Fault Tolerance, Commit Protocols, Voting protocols, Dynamic voting
protocols
Transactions and Concurrency Control: Transactions, Nested transactions, Locks, Optimistic
Concurrency control, Timestamp ordering, Comparison of methods for concurrency control.
Distributed Transactions: Flat and nested distributed transactions, Atomic Commit protocols,
Concurrency control in distributed transactions, Distributed deadlocks, Transaction recovery.
Replication: System model and group communication, Fault  tolerant services, highly available
services, Transactions with replicated data.
Text books:
1. Singhal&Shivaratri, "Advanced Concept in Operating Systems", McGraw Hill
2. Ramakrishna,Gehrke,” Database Management Systems”, McGraw Hill
3. Vijay K.Garg Elements of Distributed Compuitng , Wiley
4. Coulouris, Dollimore, Kindberg, "Distributed System: Concepts and Design”, Pearson Education 5. Tenanuanbaum,
Steen,” Distributed Systems”, PHI
 Teacher: Mr. Suraj Pal Singh CSE FACULTY
 Teacher: Mr. Suraj Pal Singh CSE FACULTY
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.
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 decisionmaking processes based on data inputs.
In this course we would learn about the machine Learning techniques and algorithms.
 Teacher: Ms. Aanchal Yadav IT FACULTY
Unit 1Introduction: 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 2Relational 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 3Data 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 4Transaction 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 5Concurrency 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
 Teacher: Mr. Bhimsingh Bohara CSE FACULTY
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.
 Teacher: Ms. Shaili Singhal CSE FACULTY
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
 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
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.
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
 Teacher: Mr. Deepak Aneja CSE FACULTY
Compiler Design (KCS502)
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. TopDown and Bottomup parsers and construction of LL, SLR, CLR, and LALR parsing table.
CO 3 Implement the compiler using syntaxdirected 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 DFABased Pattern Matchers implementation of lexical analyzers, lexicalanalyzer 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 : Syntaxdirected Translation: Syntaxdirected 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. RunTime 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: MachineIndependent Optimizations, Loop optimization, DAG representation of basic blocks, value numbers and algebraic laws, Global DataFlow analysis.
Text books: 1. K. Muneeswaran,Compiler Design,First Edition,Oxford University Press.
2. J.P. Bennet, “Introduction to Compiler Techniques”, Second Edition, Tata McGrawHill,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
 Teacher: Ms. Aditi Sharma CSE FACULTY
KCS503: 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: RedBlack 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, nQueen Problem, Hamiltonian Cycles and Sum of Subsets. 
5 
Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NPCompleteness, 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 Hill5. Gajendra Sharma, Design & Analysis of Algorithms, Khanna Publishing House6. Richard E.Neapolitan "Foundations of Algorithms" Jones & Bartlett Learning7. 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, 199710. 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. 
 Teacher: Mr. Vinay Singh CSE FACULTY
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.
 Teacher: Ms. Pavi Saraswat CSE FACULTY
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
 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
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.
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
 Teacher: Mr. Deepak Aneja CSE FACULTY
Object Oriented System Design (KCS054) 

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 
300 

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, callback 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 nonobject 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 
 Teacher: Ms. Shikha Saxena CSE FACULTY
KCS503: 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: RedBlack 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, nQueen Problem, Hamiltonian Cycles and Sum of Subsets. 
5 
Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NPCompleteness, Approximation Algorithms and Randomized Algorithms 
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 Hill5. Gajendra Sharma, Design & Analysis of Algorithms, Khanna Publishing House6. Richard E.Neapolitan "Foundations of Algorithms" Jones & Bartlett Learning7. 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, 199710. 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. 
 Teacher: Mr. Vinay Singh CSE FACULTY
 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 realworld 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 Teacher: Ms. Krista Chaudhary CSE FACULTY
 Teacher: Mr. Prashant Naresh CSE FACULTY
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.
UNITII
Advanced Data Structures: RedBlack Trees, B – Trees, Binomial Heaps, Fibonacci Heaps,
Tries, Skip List
UNITIII
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, nQueen 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
 Teacher: Mr. Pramod Kr. Sethy CSE FACULTY
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 
310 

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 
 Teacher: Ms. Shikha Saxena CSE FACULTY
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 realworld 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
 Teacher: Ms. Ruchi Goel CSE FACULTY
IN THIS COURSE WE WILL DISCUSS ABOUT VARIOUS SECURITY METHODS HOW THE SECURITY HAS BEEN EVOLVED AND VARIOUS TYPES OF ATTACKS.
 Teacher: Mr. Manish Kumar CSE FACULTY
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.
 Teacher: Ms. Vaishali Puranik CSE FACULTY
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.
 Teacher: Ms. Shipra Gautam CSE FACULTY
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,
Ttest, Ftest and Chisquare 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 McGrawHill, 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.
 Teacher: Dr. Deepa Arora CSE FACULTY
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.
 Teacher: Ms. Shipra Gautam CSE FACULTY
IN THIS COURSE WE WILL DISCUSS ABOUT VARIOUS TYPE OF SECURITY METHODS AND HOW THEY EVOLVED
 Teacher: Mr. Manish Kumar CSE FACULTY
 Teacher: Dr. Manu Singh CSE FACULTY
 Teacher: Dr. Manu Singh CSE FACULTY
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.
 Teacher: Ms. Shipra Gautam CSE FACULTY
Subject: MathematicsIV ( KAS302)
SYLLABUS
UnitI( 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.
UnitII (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.
UnitIII (Statistical TechniquesI)
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
UnitIV(Statistical TechniquesII)
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.
UnitV (Statistical TechniquesIII)
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, Ttest, Ftest and Chisquare 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 McGrawHill, 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.
 Teacher: Dr. RAM BHARAT SINGH ME FACULTY
OBJECTIVE The objective of the course is fourfold: Development of a holistic perspective based on selfexploration 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 selfreflection. Development of commitment and courage to act
 Teacher: Ms. Rashmi Sharma CSE FACULTY
IN THIS COURSE WE WILL DISCUSS ABOUT VARIOUS SECURITY METHODS HOW THEY EVOLVED AND VARIOUS TYPES OF ATTACKS
 Teacher: Mr. Manish Kumar CSE FACULTY
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.
 Teacher: Ms. Shipra Gautam CSE FACULTY
Subject: MathematicsIV ( KAS302)
SYLLABUS
UnitI( 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.
UnitII (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.
UnitIII (Statistical TechniquesI)
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
UnitIV(Statistical TechniquesII)
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.
UnitV (Statistical TechniquesIII)
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, Ttest, Ftest and Chisquare 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 McGrawHill, 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.
 Teacher: Dr. RAM BHARAT SINGH ME FACULTY
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.
 Teacher: Ms. Vaishali Puranik CSE FACULTY
OBJECTIVE:
The objective of the course is fourfold: Development of a holistic perspective based on selfexploration 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 selfreflection. Development of commitment and courage to act.
 Teacher: Ms. Rashmi Sharma CSE FACULTY
UNIT I: Introduction [08]
Introduction: Functional units of digital system and their interconnections, buses, bus architecture, Types 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.), microoperations, 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, McGrawHill, 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 ArchitectureDesigning 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 ArchitectureA Quantitative Approach”, Elsevier, a division of reed India Private Limited, Fifth edition, 2012
7. Structured Computer Organization, Tannenbaum(PHI)
 Teacher: Mr. Aditya Tandon CSE FACULTY
 Teacher: Ms. Neha Chandela IT FACULTY
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, DiffieHellman 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.
 Teacher: Mr Bharat Bhardwaj IT FACULTY
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”, McGrawHill
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,
 Teacher: Ms. Honey Jindal IT FACULTY
 Teacher: Ms. Aanchal Yadav IT FACULTY
Application of Soft Computing is an elective subject for IT 7th Sem students.
 Teacher: Dr Jay Shankar Prasad HOD IT
Unit 1Introduction: 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 2Relational 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 3Data 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 4Transaction 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 5Concurrency 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
 Teacher: Mr Ayush Aggarwal IT FACULTY
Syllabus Description
KCS303: 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
 Teacher: Mr. Ravindra Chauhan IT FACULTY
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 knowhow 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 voicedynamics.
CO1 
The student will be able to fabricate and design MOS transistors using Layout design rules, types & characteristics of MOS Inverters. 
CO2 
The student will be able to understand the different models of delay estimation and power dissipation 
CO3 
The student will understand the different sources of power dissipation in CMOS circuit. 
CO4 
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. 
Co5 
The student will learn to design low power CMOS logic circuits through various scheme. 
 Teacher: Dr. R. Sharmila ECE FACULTY
DCN REC701
 Teacher: Ms Malti Gautam ECE FACULTY
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 knowhow 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 voicedynamics.
SENSOR & INSTRUMENTATION (KOE034)
 Teacher: Ms Bhawna Tiwari ECE FACULTY
ELECTRONIC DEVICES (KEC 301)
 Teacher: Ms Neha Raheja ECE FACULTY
 Teacher: Mr. Ashutosh Kumar ME FACULTY
 Teacher: Mr. Ashutosh Kumar ME FACULTY
UNITI:
Principles of Computer Graphics:
Point plotting, drawing of lines, Bresenham’s circle algorithm.
Transformation in Graphics:
Coordinate system used in Graphics and windowing, view port, views.
2D transformations – rotation, scaling, translation, mirror, reflection, shear  homogeneous transformations – concatenation.
3D Transformation – Perspective Projection – Technique (Description of techniques only).
Geometric Modelling:
Classification of Geometric Modelling – Wire frame, Surface and Solid Modelling, applications –
representation of curves and surfaces – Parametric form.
Design of curved shapes Cubic spline – Bezier curve – Bspline – Design of Surfaces  features of
Surface Modelling Package – Solid Primitives, CSG.
Brep and description of other modelling techniques like Pure primitive instancing, cell decomposition,
spatial occupancy enumeration, Boolean Operations (join, cut, intersection), Creating 3D objects from
2D profiles (extrusion, revolving etc).
UNITII:
Graphics standard & Data storage:
Standards for computer graphics GKS, PHIGS. Data exchange standards – IGES, STEP  Manipulation
of the model  Model storage.
Finite Element Modelling:
Introduction, Mesh Generation – mesh requirements.
SemiAutomatic Methods Nodebased approach, Region based approach, Solidmodellingbased methods.
Fully Automatic Methods Elementbased approach, Application, Mesh Refinements using Isoperimetric Finite Elements, Meshing in high gradient areas, Transition Regions. Sub modelling Concept.
An overview of modelling software’s like PROE, CATIA, IDEAS, SOLID EDGE etc.
UNITIII:
CAM:
Scope and applications – NC in CAM – Principal types of CNC machine tools and their construction features – tooling for CNC – ISO designation for tooling – CNC operating system – FANUC, SINUMERIK – LINUMERIK.
Programming for CNC machining – coordinate systems – manual part programming – computer assisted part programming – CNC part programming with CAD system.
Material handling in CAM environment:
Types – AGVS – AS/RS – Swarf handling and disposal of wastes – single and mixed mode assembly lines – quantitative analysis of assembly systems.
UNITIV:
Robotics:
Classification and specification – drive and controls – sensors  end effectors  grippers tool handling and work handling – machine vision – robot programming concepts – case studies in assembly.
Quality Function Deployment:
Process Planning – CAPP – Variant and Generative systems Concurrent Engineering and Design for Manufacturing.
Advanced manufacturing Planning Computer Aided Production Planning and Control – Aggregate production planning and master production schedule – MRP – MRP II – ERP  Capacity planning.
UNITV:
Rapid prototyping:
Need for rapid prototyping, Basic principles and advantages of RP, General features and classifications of different RP techniques with examples.
Introduction to three representative RP techniques: Fusion Deposition Modelling, Laminated Object Manufacturing and Stereolithography.
Flexible manufacturing cells:
Systems – characteristics – economics and technological justification – planning, installation, operation and evaluation issues – role of group technology and JIT in FMS – typical case studies future prospects.
Books and References:
1. Chris Mcmahon and  CAD/CAM – Principle Practice and Manufacturing Management,Jimmie Browne Addision Wesley England, Second Edition,2000.
2. Dr.Sadhu Singh  Computer Aided Design and Manufacturing, khanna Publishers, NewDelhi, Second Edition,2000.
3. P.Radhakrishnan,  CAD/CAM/CIM, New Age International (P) Ltd., New Delhi.S.Subramanayanand V.Raju.
4. Groover M.P. and  CAD/CAM; Computer Aided Design and Manufacturing, Prentice HallZimmers EW. International, New Delhi, 1992.
5. Ibrahim Zeid  CAD/CAM theory and Practice, Tata McGraw Hill Publishing Co. Ltd.,Company Ltd., New Delhi, 1992.
6. Mikell P.Groover  Automation , Production Systems and Computer IntegratedManufacturing, Second edition, Prentice Hall of India, 2002.
7. S.Kant Vajpayee  Principles of Computer Integrated Manufacturing, Prentice Hall ofIndia, 1999.
8. David Bed worth  Computer Integrated Design and Manufacturing, TMH, 1998.
 Teacher: Mr. Ujjwal ME FACULTY
The strength of materials deals with strength,stability & rigidity of various structural or machine members such as beams,columns,shafts,springs,couplings,cylinders e.t.c.
 Teacher: Mr. Satyajeet Kumar ME FACULTY
Unit‐I:
Overview of Industrial Engineering: Types of production systems, concept of productivity, productivity measurement in manufacturing and service organizations, operations strategies, liability and process design.
Facility location and layout: Factors affecting facility location; principle of plant layout design, types of plant layout; computer aided layout design techniques; assembly line balancing; materials handling principles, types of material handling systems, methods of process planning, steps in process selection, production equipment and tooling selection, group technology, and flexible manufacturing.
Unit II:
Production Planning and control: Forecasting techniques – causal and time series models, moving average, exponential smoothing, trend and seasonality; aggregate production planning; master production scheduling; materials requirement planning (MRP) and MRP‐II; routing, scheduling and priority dispatching, concept of JIT manufacturing system
Project Management: Project network analysis, CPM, PERT and Project crashing.
Unit III:
Engineering economy and Inventory control: Methods of depreciation; break‐even analysis, techniques for evaluation of capital investments, financial statements, time‐cost trade‐off, resource levelling; Inventory functions, costs, classifications, deterministic inventory models, perpetual and periodic inventory control systems, ABC analysis, and VED analysis.
Queuing Theory: Basis of Queuing theory, elements of queuing theory, Operating characteristics of a queuing system, Classification of Queuing models.
Unit IV
Work System Design: Taylor’s scientific management, Gilbreths’s contributions; work study: method study, micro‐motion study, principles of motion economy; work measurement –time study, work sampling, standard data, Predetermined motion time system (PMTS); ergonomics; job evaluation, merit rating, incentive schemes, and wage administration.
Product Design and Development: Principles of product design, tolerance design; quality and cost considerations; product life cycle; standardization, simplification, diversification, value engineering and analysis, and concurrent engineering.
Unit V:
Operational Analysis: Formulation of LPP, Graphical solution of LPP, Simplex Method, Sensitivity Analysis, degeneracy and unbound solutions. transportation and assignment models; Optimality test: the stepping stone method and MODI method, simulation.
Books and References:
1. Industrial Engineering and Production Management by Martand T Telsang S. Chand Publishing
2. Industrial Engineering and Production Management by M. Mahajan Dhanpat Rai & Co. (P) Limited
3. Industrial Engineering and Management by Ravi Shankar, Galgotia Publications Pvt Ltd
4. Production and Operations Management by Adam, B.E. & Ebert, R.J., PHI
5. Product Design and Manufacturing by Chitale A.V. and Gupta R.C., PHI
6. Operations Research Theory & Applications by J K Sharma, Macmillan India Ltd,
7. Production Systems Analysis and Control by J.L.Riggs, John Wiley & Sons
8. Automation, Production Systems & Computer Integrated Manufacturing by Groover, M.P. PHI
9. Operations Research, by A.M. Natarajan, P. Balasubramani, A. Tamilarasi, Pearson Education
10. Operations Research by P. K. Gupta and D. S. Hira, S. Chand & Co.
 Teacher: Mr. Ujjwal ME FACULTY
The internal combustion engines which are the subject of sparkignition
engines (sometimes called Otto engines, or gasoline or petrol engines, though
other fuels can be used) and compressionignition or diesel engines.
 Teacher: Mr. Vikas ME FACULTY
The strength of materials deals with strength,stability & rigidity of various structural or machine members such as beams,columns,shafts,springs,couplings,cylinders e.t.c.
 Teacher: Mr. Satyajeet Kumar ME FACULTY
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 knowhow 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 voicedynamics.
CIVIL 4TH YEAR DESIGN OF STEEL STRUCUTRES
 Teacher: Mr. Ashish Kush CIVIL FACULTY
CIVIL 3RD YEAR CONCRETE TECHNOLOGY