M. S. RAMAIAH INSTITUTE OF TECHNOLOGY
BANGALORE-54
(Autonomous Institute, Affiliated to VTU)
Computer Science and Engineering
Outcomes Based Education Curricula
(Academic Year 2015 – 2016)
III & IV Semester
History of the Institute
M. S. Ramaiah Institute of Technology was started in 1962 by the late Dr. M.S. Ramaiah, our
Founder Chairman who was a renowned visionary, philanthropist, and a pioneer in creating
several landmark infrastructure projects in India. Noticing the shortage of talented
engineering professionals required to build a modern India, Dr. M.S. Ramaiah envisioned
MSRIT as an institute of excellence imparting quality and affordable education. Part of
Gokula Education Foundation, MSRIT has grown over the years with significant
contributions from various professionals in different capacities, ably led by Dr. M.S. Ramaiah
himself, whose personal commitment has seen the institution through its formative years.
Today, MSRIT stands tall as one of India’s finest names in Engineering Education and has
produced around 35,000 engineering professionals who occupy responsible positions across
the globe.
History of Department of Computer Science and Engineering
Year of Establishment
Names of the Programmes
offered
1984
1. UG: B.E. in Computer science and Engineering
2. PG: M.Tech. in Computer Science and Engineering
3. PG: M.Tech. in Computer Networks and Engineering
4. Ph.D
5. M.Sc(Engg.) by research
2
Faculty
Name
Sl. No.
Qualification
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
Dr. K G Srinivasa
M.E, Ph.D
Dr. R. Srinivasan
D.Sc.
Dr .S Ramani
Ph.D
Nagabhushan A.M
M.Tech
Dr. Anita Kanavalli
M.E., Ph.D
Dr. Seema S
M.S., Ph.D
Dr. Annapurna P. Patil
M. Tech, Ph.D
Jagadish S Kallimani
M.Tech, (Ph.D)
Jayalakshmi D S
M.Sc(Engg), (Ph.D)
Dr. Monica R Mundada
M.Tech, Ph.D
Sanjeetha R
M.Tech
A Parkavi
M.E. (Ph.D)
Veena G S
M.Tech (Ph.D)
J Geetha
M.Tech, (Ph.D)
Dr. T N R Kumar
M. Tech Ph.D
Mamatha Jadav V
M.Tech
Chethan C T
B.E.
Sini Anna Alex
M.E, (Ph.D)
Vandana Sardar
M.E.
Meera Devi
M.Tech
Mallegowda M
M.Tech
Divakar Harekal
M.E.
Chandrika Prasad
M.Tech
S Rajarajeswari
M.E, (Ph.D)
Sowmyarani C N
M.E. (Ph.D)
Pramod S Sunagar
M.Tech
Sowmya B J
M.Tech
Pradeep Kumar D
M.Tech
Ganeshayya I Shidaganti
M.Tech
Chetan
M.Tech
Darshana A Naik
M.Tech
Srinidhi H
M.Tech
Aparna R
B.E, M.Tech
Hanumantha Raju R
B.E, M.Tech
Visiting Faculty Members from Industry
35.
Dr. Ramamurthy Badrinath
Ph.D
36.
N. Pramod
B.E.
37.
Jayasimha Rao
38.
Sriram Kashyap
M.S. in Machine Learning
and Data Mining from
Aalto University School of
Science
MTech from IIT Madras
3
Designation
HOD, Professor
Emeritus Professor
Emeritus Professor
Emeritus Professor
Professor
Associate Professor
Associate Professor
Associate Professor
Associate Professor
Associate Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
AICTE-INAE
distinguished Visiting
Professor
Application Engineering
at Thoughtworks Pvt.
Ltd.
Entrepreneur
Intel, Bangalore
Vision and Mission of the Institute
Vision
To evolve into an autonomous institution of International standards for imparting quality
Technical Education
Mission
MSRIT shall deliver global quality technical education by nurturing a conducive learning
environment for a better tomorrow through continuous improvement and customization.
Quality Policy
“We at M. S. Ramaiah Institute of Technology, Bangalore strive to deliver comprehensive,
continually enhanced, global quality technical and management education through an
established Quality Management system complemented by the synergistic interaction of the
stake holders concerned”.
Vision and Mission of the Department
Vision
To build a strong learning and research environment in the field of Computer Science and
Engineering that responds to the challenges of 21 st century.

Mission
To produce computer science graduates who, trained in design and implementation of
computational systems through competitive curriculum and research in collaboration
with industry and other organizations.

To educate students in technology competencies by providing professionally
committed faculty and staff.

To inculcate strong ethical values, leadership abilities and research capabilities in the
minds of students so as to work towards the progress of the society.
4
Process for Defining the Vision and the Mission of the Department
Programme Educational Objectives (PEOs)
A B.E. (Computer Science & Engineering) graduate of M. S. Ramaiah Institute of
Technology should, within three to five years of graduation
1. Pursue a successful career in the field of Computer Science & Engineering or a
related field utilizing his/her education and contribute to the profession as an excellent
employee, or as an entrepreneur
2. Be aware of the developments in the field of Computer Science & Engineering,
continuously enhance their knowledge informally or by pursuing graduate studies
3. Be able to work effectively in multidisciplinary environments and be responsible
members/leaders of their communities
5
PEOs Derivation Process
Programme Outcomes (POs)
The outcomes of the Bachelor of Engineering in Computer Science & Engineering
Programme are as follows:
A B.E. (Computer Science & Engineering) graduate must demonstrate
1. An ability to apply knowledge of mathematics, science, and engineering as it applies to
Computer Science & Engineering
2. An ability to identify, formulate, study, and analyze and solve complex computing
problems
3. An ability to design a computer-based system, component, software or process to meet
the desired needs
4. An ability to design and conduct experiments, evaluate results and provide valid
conclusions
5. An ability to use modern computing techniques, technologies and tools necessary for
computing engineering practice.
6
6. An ability to understand and assess the societal, legal and security issues related to the
practice of computer science and engineering.
7. An ability to understand the impact of computing solutions in an economic,
environmental and societal context.
8. An understanding of professional and ethical responsibilities in professional
engineering practice.
9. An ability to function effectively individually and in team, and in multi-disciplinary
environment.
10. An ability to communicate effectively.
11. An understanding of the engineering and management principles required for project
and finance management.
12. Recognition of the need for, and an ability to engage in life-long learning.
PO Derivation Process
7
Mapping of PEOs and POs
Sl.
No.
1
2
3
Programme
Educational
Objectives
Excel in
career
Life-long
learning
Work in
diverse
teams and
show
Leadership
Programme Outcomes
PO1
PO2
PO3
PO4
PO5
PO6
PO7
PO8
PO9
PO10
PO11
PO12
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Curriculum Breakdown Distribution
Sl. No.
1
Courses
Basic Science Core Courses
Weightage
13%
2
Basic Engineering Science Core Courses
13%
3
Humanities and Social Science Core Courses
3%
4
Professional Courses and Electives
62%
5
Major Project
9%
6
Mandatory Learning Courses
0%
8
x
x
x
x
Board of Studies for the Term 2015-2016
1. Head of the Department concerned:
Dr. K G Srinivasa
Chairperson
2. At least five faculty members at different
levels covering different specializations
constituting nominated by the Academic
Council
Dr. Anita Kanavalli
Prof. Jagadish S Kallimani
Prof. Jayalakshmi D S
Prof. H V Divakar
Prof. Sanjeetha R
Prof. Parkavi
Prof. Chandrika Prasaad
Member
Member
Member
Member
Member
Member
Member
3. Special invitees
Dr. R. Srinivasan
Dr. S. Ramani
Prof. Nagabhushan A M
Member
Member
Member
4. Two experts in the subject from outside
the college
Dr. Kavi Mahesh, Professor, PESIT
Dr. G Varaprasad Associate Professor, BMSCE
Member
Member
5. One expert from outside the college,
nominated by the Vice Chancellor
Dr. N.K. Srinath, Professor, RVCE
Member
6. One representative from
industry/corporate sector allied area
relating to placement nominated by the
Academic Council
Mr. Rajesh Vijayarajan, Hewlett-Packard
Member
7. One postgraduate meritorious alumnus
to be nominated by the Principal
Sriram Kashyap, Intel Corporation
Member
9
Department Advisory Board for the term 2015-2016
1. Head of the Department concerned
Dr. K G Srinivasa
Member
2. Experts from other organizations for
Department Advisory Board
Dr. Satish Vadhiyar, SERC, IISC Bangalore
Dr. Srinivasaraghavan, IIIT Bangalore
Dr. K Sangeeta Iyer
Member
Member
Member
Industry Advisory Board for the Term 2015-2016
1. Head of the Department concerned
Dr. K G Srinivasa
Member
2. Experts from industry constituting
the Industry Advisory Board
Dr. Badrinath Ramamurthy, HP Labs, India
Dr. N.C. Narendra, CTS
Dr. Yogesh Simhan, SERC, IISC
Mr. Sreekanth Iyer, IBM
Mr. Nishant Kulkarni, IBM
Mr. Muthuraman Ranganath, SAP Technologies
Mr. K Murali, Amazon
Member
Member
Member
Member
Member
Member
Member
10
Scheme of Studies for Second Year B.E. (CSE) for the batch 2014-2018
III Semester
Code
CSMAT301
CS1531
CS1532
CS1533
CS1534
CSL1531
CSL1532
CSL1533
Total Credits: 25
Subject
Engineering Mathematics III
Analog and Digital Design
Data Structures with C
Discrete Mathematical Structures
Theory of Computation
Analog and Digital Design
Laboratory
C++ Laboratory
Advanced Programming with C
IV Semester
Code
CSMAT401
CS1541
CS1542
CS1543
CS1544
CSL1541
CSL1542
CSL1543
L
4
4
4
3
3
0
T
0
0
0
1
1
0
P
0
0
0
0
0
2
Credit
4
4
4
4
4
2
0
0
1
0
1 2
1 1
Total Credits: 25
Subject
Engineering Mathematics IV
Computer Organization
Design and Analysis of
Algorithms
Introduction to
Microprocessors
Data Communication
Python Laboratory
Algorithms Laboratory
Microprocessor and CO Lab
L
4
4
3
T
0
0
1
P
0
0
0
Credit
4
4
4
4
0
0 4
3
0
0
0
1
1
0
0
0
1
1
2
4
2
1
2
Course Title: Engineering Mathematics – III
Course Code: CSMAT301
Credits (L:T:P) : 4:0:0
Core/ Elective: Core
Type of course: Lecture
Total Contact Hours: 56
Prerequisites: Nil
Course Objectives:
The students will
1. Learn to solve algebraic, transcendental and ordinary differential equations numerically.
2. Learn to fit a curve, correlation, regression for a statistical data.
3. Learn to represent a periodic function in terms of sines and cosines.
4. Understand the concepts of continuous and discrete integral transforms in the form of Fourier and Ztransforms.
5. Learn the concepts of consistency, methods of solution for linear system of equations and eigen value
problems.
6. Learn the concepts of linear transformation through matrix algebra.
Course Contents:
Unit 1
Numerical solution of Algebraic and Transcendental equations: Method of false position, Newton Raphson method.
Numerical solution of Ordinary differential equations: Taylor series method, Euler and modified Euler
method, fourth order Runge-Kutta method.
Statistics: Curve fitting by the method of least squares, Fitting a linear curve, fitting a parabola, fitting a
Geometric curve, Correlation and Regression.
Unit 2
Fourier Series: Convergence and divergence of infinite series of positive terms. Periodic functions, Dirchlet
conditions, Fourier series of periodic functions of period 2π and arbitrary period, Half range Fourier series,
Practical harmonic analysis.
Unit 3
Fourier Transforms: Infinite Fourier transform, Fourier sine and cosine transform, Properties, Inverse
transform.
Z-Transforms: Definition, Standard Z-transforms, Single sided and double sided, Linearity property, Damping
rule, Shifting property, Initial and final value theorem, Inverse Z-transform, Application of Z-transform to solve
difference equations.
Unit 4
Linear Algebra: Elementary transformations on a matrix, Echelon form of a matrix, rank of a matrix,
Consistency of system of linear equations, Gauss elimination and Gauss – Seidal method to solve system of
linear equations, eigen values and eigen vectors of a matrix, Rayleigh power method to determine the dominant
eigen value of a matrix, diagonalization of a matrix, system of ODEs as matrix differential equations
Unit 5
Linear Transformations: Introduction to Linear transformations, Composition of matrix transformations,
Rotation about the origin, Dilation, Contraction and Reflection, Kernel and Range, Change of basis.
Text Books:
1. Erwin Kreyszig-Advanced Engineering Mathematics-Wiley-India publishers- 10th edition-2015.
2. B.S.Grewal - Higher Engineering Mathematics - Khanna Publishers – 42nd edition-2012.
3. Gareth Williams – Linear Algebra with Applications – Jones and Bartlett Press – 6th edition – 2008.
Reference Books:
1.
2.
3.
Peter V. O’Neil – Advanced Engineering Mathematics – Thomson Brooks/Cole – 7th edition – 2011.
B. V. Ramana – Engineering Mathematics – Tata McGraw Hill Pub. Co. Ltd. – New Delhi – 2008.
David C. Lay – Linear Algebra and its Applications – Pearson-3rd edition-2011
Course Outcomes:
Students are expected to do the following
1. Should be able to solve the problems of algebraic, transcendental and ordinary differential equations
using numerical methods.
2. Fit a suitable curve by the method of least squares and determine the lines of regression for a set of
statistical data.
3. Find the Fourier series expansion of a function in both full range and half range values of the variable
and obtaining the various harmonics of the Fourier series expansion for the given numerical data.
4. Find Fourier transforms, Fourier sine and Fourier cosine transforms of functions and solving difference
equations using Z-transforms.
5. Find the rank of a matrix, test the consistency and the solution by Gauss elimination and Gauss Siedel
iteration methods.
6. Find the Kernel and Range of Linear transformations.
Course Title: Analog and Digital design
Course Code: CS1531
Credits (L:T:P) : 4:0:0
Core/ Elective: Core
Type of course: Lecture
Total Contact Hours: 56
Prerequisites:
Basic Electronics
Course Contents:
Unit 1
Op-amps: inside of the op-amp, ideal op-amp versus practical op-amp, performance parameters, Op-amp
Application circuits: Inverting amplifier, non-inverting amplifier, voltage follower, summing amplifier,
Relaxation Oscillator, R-2R ladder network circuits, binary weighted circuits and Schmitt trigger circuits.
Synthesis of logic circuits logic circuits with SOP and POS, K-map, strategy of minimization, minimization of
SOP, POS forms, incompletely specified functions
Unit 2
Wave shaping circuits: Basic RC low pass circuits, RC low pass circuit as integrator, Basic RC high pass circuit,
RC high pass as differentiator.
Tabular method for minimization of Boolean functions, Combinational circuits: Half adder, full
adder(realization using NAND gates), adder-sub tractor unit, ripple and fast adders, multiplexers, decoders,
encoders, code converters, arithmetic comparison circuits.
Unit 3
Wave shaping circuits, diode clipper circuits , diode clamper circuit, integrated circuit multivibrators using 555
(Timer IC) (astable, monostable circuits).
Basic latch, gated SR latch, gated D latch, T FF, JK FF, truth table, characteristics equation and excitation tables
of all the four types of FFs. Registers: Shift registers, parallel access registers.
Unit 4
Feedback amplifiers: Classification of amplifiers, amplifiers with negative feedback, and advantages of negative
feedback. Series and shunt linear regulators, linear IC voltage regulators.
Study of asynchronous counters: Up, down counters, reset synchronization, decade counter, Ring counter,
Johnson counter, truncated counters.
Unit 5
Study of synchronous sequential circuits: Basic design steps, Mealy state model, Mealy type FSM for serial
adder. Design of a counter using sequential circuits approach using different FFs for different modulo values
and design of random counters.
Text Books:
1. Stephen Brown, ZvonkoVranesic: Fundamentals of Digital Logic Design with VHDL, Tata McGraw
Hill, 3rd Edition, 2012.
2. Anant Agarwal JefferyLang: Foundations of Analog and Digital Electronic Circuits 2005 by Elsevier
Inc.
3. Anil K Maini, Varsha Agarwal: Electronic Devices and Circuits, Wiley, First Edition, 2009
Reference Books:
1. Robert L Boylestad, Louis Nashelsky: Electronic devices and circuit theory, 9th edition. 2007.
2. Albert Malvino& David J Bates: Electronic Principles, TMH, 7th edition, 2007.
3. David A Bell: Electronic devices and Circuits, PHI,4th edition, 2006.
Course Delivery: Black board teaching, power point presentations
Course Assessment and Evaluation
What
When/ Where
(Frequency in the
course)
Thrice(Average of
the best two will be
computed)
Twice(Summation
of the two will be
computed)
To
Whom
Direct & Indirect Assessment Methods
Internal
Assessment Tests
CIE
SEE
Class-room
Surprise Quiz
Standard
Examination
Students
End of Course
Survey
End of Course
(Answering
5 of 10 questions)
End of the course
Max
Marks
Evidence
Collected
Contribution to
Course Outcomes
30
Blue Books
1,2 3,4,5 & 6
20
Quiz papers
100
Answer scripts
1,2 3,4,5 & 6
Questionnaire
1,2 3,4,5 & 6
Effectiveness of
Delivery of
instructions &
Assessment
Methods
-
1,2 3,4,5 & 6
Course Outcomes:
At the end of the course the students should be able to:
1.
2.
3.
4.
5.
6.
Describe the working of different analog circuits like op-amp, wave shaping, feedback amplifiers and
regulator circuits.
Describe the working of different digital combinational and sequential circuits.
Explain the various techniques used for Boolean function minimization.
Construct analog wave shaping circuits and digital ALU circuits.
Examine the characteristics of flip flops and amplifier circuits
Design asynchronous and synchronous sequential circuits.
Mapping Course Outcomes with Programme Outcomes:
Programme Outcomes
Course Outcomes
1
2
Describe the working of different analog circuits like
op-amp, wave shaping, feedback amplifiers and
regulator circuits.
x
x
Describe the working of different
combinational and sequential circuits
x
x
x
x
digital
Explain the various techniques used for Boolean
function minimization.
Construct analog wave shaping circuits and digital
ALU circuits.
x
Examine the characteristics of flip flops and
amplifier circuits
x
Design asynchronous and synchronous sequential
circuits.
x
x
3
4
5
x
x
6
7
8
9
10
11
12
Course Title: Data Structures with C
Course Code: CS1532
Credits (L:T:P) : 4:0:0
Core/ Elective: Core
Type of course: Lecture
Total Contact Hours: 56
Prerequisites:
Fundamentals of Computing
Course Contents:
Unit 1
Basic Concepts: Pointers and Dynamic Memory Allocation, Algorithm Specification, Data Abstraction. Arrays
and Structures: Arrays, Dynamically Allocated Arrays, Structures and Unions, Polynomials, Sparse Matrices,
Representation of Multidimensional Arrays, Strings.
Unit 2
Stacks And Queues: Stacks, Stacks Using Dynamic Arrays, Queues, Circular Queues Using Dynamic Arrays,
Evaluation of Expressions, Multiple Stacks and Queues
Unit 3
Linked Lists: Singly Linked lists and Chains, Representing Chains in C, Linked Stacks and Queues,
Polynomials, Additional List operations, Sparse Matrices, Doubly Linked Lists.
Unit 4
Trees: Introduction, Binary Trees, Binary Tree Traversals, Additional Binary Tree Operations, Threaded Binary
Trees, Heaps, Binary Search Trees, Selection Trees, Forests, Representation of Disjoint Sets, Counting Binary
Trees.
Unit 5
Graphs: The Graph Abstract Data Type, Elementary Graph Operations. Priority Queues: Single- and DoubleEnded Priority Queues, Leftist Trees. Efficient Binary Search Trees: AVL Trees.
Text Books:
1.
Horowitz, Sahni, Anderson-Freed: Fundamentals of Data Structures in C, 2nd Edition, Universities
Press, 2008.
Reference Books:
1.
2.
1.
Yedidyah, Augenstein, Tannenbaum: Data Structures Using C and C++, 2nd Edition, Pearson
Education, 2003.
Data Structures, Seynour Lipschutz and GAV Pai, Schaum’s Outlines, McGraw Hill, 2008.
Richard F. Gilberg and Behrouz A. Forouzan: Data Structures A Pseudocode Approach with C,
Cengage Learning, 2005
Course Delivery:
The course will be delivered through lectures, class room interaction and programming exercises
Course Assessment and Evaluation:
What
Direct & Indirect Assessment
Methods
C
I
E
S
E
E
To Whom
Internal
Assessment
Tests
Practical
Assignment
Standard
Examination
Students
End of Course
Survey
When/ Where
(Frequency in
the course)
Thrice(Average
of the best two
will
be
computed)
Once/
Laboratory
End of Course
(Answering
5
of
10
questions)
End
of
Course
the
Evidence
Collected
Contribution to
Course
Outcomes
30
Blue Books
1,2,3,4,5,6,7 & 8
20
Report
1,2,3,4,5,6,7 & 8
100
Answer
scripts
1,2,3,4,5,6,7 & 8
-
Questionnaire
1,2,3,4,5,6,7 & 8
Delivery of the
course
Max
Marks
Course Outcomes:
At the end of course, students will be able to:
1.
2.
3.
4.
5.
6.
7.
8.
Identify the purposes of dynamic memory in applications
Illustrate arrays and structures with programming solutions for real time problems
Quote the implication of stacks and queues for different problems
Propose programming solutions using variations of stacks and queues
Manage data set operations using variations of linked list
Appraise the purposes of Trees to represent data sets
Devise application to solve tree oriented problems
Develop solutions for problems based on graphs
Mapping Course Outcomes with Programme Outcomes:
Programme Outcomes
Course Outcomes
1
2
3
4
×
×
×
×
Illustrate arrays and structures with programming
solutions for real time problems
×
×
×
×
Quote the implication of stacks and queues for
different problems
×
×
×
×
Propose programming solutions using variations of
stacks and queues
×
×
×
×
×
Manage data set operations using variations of
linked list
×
×
×
×
×
Appraise the purposes of Trees to represent data
sets
×
×
×
×
Devise application to solve tree oriented problems
×
×
×
×
×
×
Develop solutions for problems based on graphs
×
×
×
×
×
×
Identify the purposes of dynamic memory
applications
in
5
6
7
8
9
10
11
12
×
×
×
×
Course Title: Discrete Mathematical Structures
Course Code: CS1533
Credits (L:T:P) : 3:1:0
Core/ Elective: Core
Type of course: Lecture, Tutorial
Total Contact Hours: 70
Prerequisites:
Basic maths
Course Contents:
Unit 1
Logics and Proofs: The laws of Logic, Logical implication, Rules of inference, Quantifiers, Proofs of theorems.
Unit 2
Relations: Relations, Properties of relations, Computer Recognition- Zero-one Matrices and directed Graphs,
Equivalence Relations and partitions. POSETS, Hasse Diagrams, Lattices..
Unit 3
Combinatorics: Fundamentals of counting, permutation, combination, Combination with repetition, Binomial
Coefficient, Principle of inclusion and exclusion, Pigeon hole principle. The Principle of Inclusion and
Exclusion: The Principle of Inclusion and Exclusion, Generalizations of the Principle, Derangements – Nothing
is in its Right Place, Rook Polynomials.
Unit 4
Graph Theory: Introduction to Graph theory- Definitions, subgraphs, complements, and graph isomorphism,
Euler’s trails and circuits, Hamilton paths and Cycles. Planar graphs, Euler’s Theorem, Graph Coloring.
Unit 5
Trees: Definitions, Properties, and Examples, Routed Trees, Trees and Sorting, Weighted Trees and Prefix
Codes. Number theory: Divisibility and modular arithmetic, generating prime numbers, solving congruences,
applications of congruences.
Text Books:
1. Ralph P. Grimaldi: Discrete and Combinatorial mathematics, 5th Edition, PHI/ Pearson Education,
2004.
2. Kenneth H. Rosen: Discrete Mathematics and its Applications.
Reference Books:
1. Thomas Koshy: Discrete Mathematics with Applications.
2. Kenneth H. Rosen: Discrete Mathematics and its Applications
Course Delivery:
The course will be delivered through lectures, presentations, classroom discussions, and practical
implementations. Questions for CIE and SEE are designed in accordance with the Bloom’s taxonomy.
Course Assessment and Evaluation:
Direct & Indirect Assessment
Methods
What
CIE
To
Whom
Internal
Assessment Tests
Quiz/OnlineCourse
SEE
Standard
Examination
Students
When/ Where
(Frequency in
the course)
Thrice(Average
of the best two
will be
computed)
Once
End of Course
(Answering
5 of 10
questions)
End of Course
Survey
Max
Marks
Evidence
Collected
Contribution to
Course Outcomes
30
Blue Books
1,2,3,4 & 5
20
Quiz Papers
1,2,3,4 & 5
100
Answer
scripts
1,2,3,4 & 5
Questionnaire
1,2,3,4 & 5
Effectiveness of
Delivery of
instructions &
Assessment
Methods
End of the
course
-
Course Outcomes:
At the end of the course, students should be able to:
1. Understand the notion of mathematical logic & proofs and be able to apply them in problem solving.
2. Solve problems which involve discrete data structures such as relations and discrete functions.
3. Apply basic counting techniques and combinatorics in the context of discrete probability.
4. Demonstrate knowledge of fundamental concepts in graphs, trees and its properties using various
modeling techniques.
5. Solve problems on number theory and its applications.
Mapping Course Outcomes with Programme Outcomes:
Course Outcomes
Programme Outcomes
1
2
3
4
Understand the notion of mathematical logic &
proofs and be able to apply them in problem
solving.
x
x
x
Solve problems which involve discrete data
structures such as relations and discrete functions.
x
x
x
x
x
Apply
basic
counting
techniques
and
combinatorics in the context of discrete
probability.
x
x
x
x
Demonstrate knowledge of fundamental concepts
in graphs, trees and its properties using various
modeling techniques.
x
x
x
x
Solve problems on number theory and its
applications.
x
x
x
5
6
7
8
9
10
11
12
Course Title: Theory of Computation
Credits (L:T:P) : 3:1:0
Type of course: Lecture, Tutorial
Course Code: CS1534
Core/ Elective: Core
Total Contact Hours: 70
Prerequisites : Nil
Course Contents:
Unit 1
Introduction to Finite Automata, structural representations, automata and complexity, the central concepts of
automata theory; deterministic finite automata, nondeterministic finite automata, an application of finite
automata, finite automata with epsilon transitions.
Unit 2
Regular Expressions, finite automata and regular expressions, applications of regular expressions, proving
languages not to be regular, closure properties of regular languages, equivalence and minimization of automata.
Unit 3
Context–free grammars, parse trees, applications, ambiguity in grammars and languages, definition of the
pushdown automata, the languages of a PDA, equivalence of PDAs and CFGs.
Unit 4
Deterministic Pushdown Automata, normal forms for CFGs, the pumping lemma for CFGs, closure properties
of CFLs.
Unit 5
The Turing machine, Programming techniques for Turing Machines. Undecidability- A Language that is not
recursively enumerable, extensions to the basic turing machine, restricted turing machines, turing machine and
computers
Text Book:
1. John E. Hopcroft, Rajeev Motwani, Jeffrey D.Ullman: Introduction to Automata Theory, Languages and
Computation, 3rd Edition, Pearson Education, 2011.
Reference Books:
1. John C Martin: Introduction to Languages and Automata Theory, 3rd Edition, Tata McGraw-Hill, 2007.
2. Michael Sipser: Introduction to the Theory of Computation, 3rd Edition, Thompson Course Technology,
Boston, MA and Cengage Learning India Pvt. Ltd.,2014.
Course Delivery:
The course will be delivered through lectures, class room interaction, group discussion and problem solving
intutorials.
Course Assessment and Evaluation:
Direct & Indirect
Assessment Methods
What
CIE
To
Whom
Internal
Assessment Tests
Quiz
SEE
Standard
Examination
End of Course
Survey
Students
When/ Where
(Frequency in the
course)
Thrice(Average of
the best two will be
computed)
2 quizzes of 10
marks each
End of Course
(Answering
5 of 10 questions)
End of the course
Max
Marks
Evidence
Collected
30
Blue Books
1,2,3 & 4
20
Quiz Answer
sheets
1,2,3 & 4
100
Answer scripts
1,2,3 & 4
online survey
responses
1,2,3 & 4
Effectiveness of
course delivery of
& Assessment
Methods
-
Contribution to
Course Outcomes
Course Outcomes:
At the end of the course the student will be able to:
1. Explain the basic concepts of formal languages and finite automata.
2. Construct automata to accept strings from a specified language.
3. Convert among equivalently powerful notations for a language, including among DFAs, NFAs,
and regular expressions, between PDAs,CFGs and normal forms of CFGs
4. Prove the various closure and decision properties of formal languages.
Mapping Course Outcomes with ProgrammeOutcomes:
Course
Outcomes
Explain the basic
concepts of formal
languages and finite
automata
Construct automata to
accept strings from a
specified language.
Convert among
equivalently powerful
notations for a
language, including
among DFAs, NFAs,
and regular
expressions, between
PDAs,CFGs and
normal forms of CFGs
Prove the various
closure and decision
properties of formal
languages.
PO1
PO2
PO3
x
x
x
x
x
x
x
x
x
x
x
x
PO4
ProgrammeOutcomes
PO5 PO6 PO7 PO8 PO9
PO10
PO11
PO12
Course Title: Analog and Digital Design Laboratory
Course Code: CSL1531
Credits (L:T:P) : 0:0:2
Core/ Elective: Core
Type of course: practicals
Total Contact Hours: 56
Prerequisites: Circuit analysis techniques, Linear components, non linear components ,Using
KVL, KCL, Thevenins method, node method, Norton method.
Course Contents:
Experiments that are to be conducted as a part of the course
Experiments to be conducted with hardware as well as simulation using multisim and modelsim software’s
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Design and implement an inverting amplifier for a given pass band gain . and plot the frequency
response of the same.
Given a set of minterms write a circuit to genetate the logic f(x,y,z,a)= m1+m5+m10+m15
Write a full adder circuit using only NAND gates.
Design a Low pass filter and plot the frequency response
Design and implement the Clamper circuits
Building a multiplexer 4: 1
Building a decoder 2:4/ 3:8
Design and Implement Relaxation oscillator for a given frequency using opamp
Shift register with serial input and parallel input using IC
Implement a 4 bit R/2 R ladder
Design a astable multivibrator for a given frequency using 555 timer
Design 8 V voltage regulator using IC 7805 and evaluate the line and load regulation.
Design a 3bit counter using with irregular counter
JK flip flop used as D flip-flop and toggle flipflop
Ring counter and Johnsons counter.
Text Books:
1. Stephen Brown, Zvonko Vranesic: Fundamentals of Digital Logic Design with VHDL, Tata McGraw
Hill, 3rd Edition, 2012.
2. Anant Agarwal J e f f r e y h . lang: Foundations of Analog and Digital Electronic Circuits 2005 by
Elsevier Inc.
3. Anil K Maini, Varsha Agarwal: Electronic Devices and Circuits, Wiley, First Edition, 2009
Reference Books:
1. Robert L Boylestad, Louis Nashelsky: Electronic devices and circuit theory, 9th edition. 2007.
2. Albert Malvino & David J Bates: Electronic Principles, TMH, 7th edition, 2007.
3. David A Bell: Electronic devices and Circuits, PHI,4th edition, 2006.
Course Delivery:
Experiments using Hardware and simulation in the laboratory
Course Assessment and Evaluation:
To
Whom
Direct & Indirect
Assessment Methods
What
CIE
Internal
Assessment Tests
SEE
Standard
Examination
When/ Where
(Frequency in
the course)
Twice
End of Course
(Answering
5 of 10 questions)
Max
Marks
Evidence
Collected
Contribution to
Course Outcomes
25M x
2=50M
Data Sheets
1,2 3,4,5 & 6
100
Answer
scripts
1,2,3,4,5 & 6
Questionnaire
1,2 3,4,5 & 6
8Effectiveness of
Delivery of
instructions &
Assessment
Methods
Students
End of Course
Survey
End of the course
-
Course Outcomes:
At the end of the course the students should be able to :
1.
2.
3.
4.
5.
6.
Design various Opamp circuits
Demonstrate wave shaping circuits
Design of logical circuits using Kmap , SOP, POS concepts
Evaluate counter circuits
Develop a voltage regulator and study for its line and load regulation
Design code convertor circuits and multi vibrator circuits
Mapping Course Outcomes with Programme Outcomes:
Course Outcomes
Design various Opamp circuits
Demonstrate wave shaping circuits
Design of logical circuits using K-map , SOP, POS
concepts
Evaluate counter circuits
Develop a voltage regulator and study for its line
and load regulation
Design code convertor circuits and multi vibrator
circuits
Programme Outcomes
1
2
x
x
x
x
x
x
x
x
x
x
3
4
x
x
x
x
x
x
x
5
6
7
8
9
10
11
12
Course Title: : C++ Laboratory
Course Code: CSL1532
Credits (L:T:P) : 0:1:1
Type of course: Tutorials, Practicals
Core/ Elective: Core
Total Contact Hours: 56 Hrs
Prerequisites: Fundamentals of Computing
Course Contents:
At the end of the course the student will be able to:
1. To demonstrate the paradigm of OOP through Classes & objects.
2. To introduce the concept of Constructors, destructors & static data members.
3. Familiarize the utilities of Friend functions & Inline functions.
4. Recognize the need for Operator overloading.
5. To apply the concept of Inheritance -protected members, protected base class inheritance, inheriting
multiple base classes.
6. To demonstrate the concept of Polymorphism.
7. To illustrate Formatted I/O, I/O manipulators.
8. To illustrate File operations.
9. To illustrate Exception handling.
10. To implement using Standard Template Library.
Reference Books:
1.
2.
Stanley B.Lippmann, JoseeLajoie: C++ Primer, 4th Edition, Addison Wesley, 2012
Herbert Schildt: The Complete Reference C++, 4th Edition, Tata McGraw Hill, 2011
Course Delivery:
The course will be delivered through lectures in the laboratory with exercises.
Course Assessment and Evaluation:
Direct & Indirect Assessment
Methods
What
To Whom
When/ Where
(Frequency in
the course)
Max
Marks
Evidence
Collected
Contribution to
Course Outcomes
CIE
Internal
Assessment
Tests
Twice
50
Data Sheets
1,2 3,4,5
SEE
Standard
Examination
End of Course
(Answering 5
of 10
questions)
50
Answer
scripts
1,2,3,4 &5
Questionnaire
1, 2,3,4 & 5
Effectiveness of
Delivery of
instructions &
Assessment
Methods
Students
End of Course
Survey
End of the
course
-
Course Outcomes:
At the end of the course, a student should be able to:
1. Develop classes incorporating object-oriented techniques.
2. Design and implement object-oriented concepts of inheritance.
3. Design and implement object-oriented concepts of polymorphism.
4. Illustrate and implement STL class of containers (Vectors, stacks, queues, lists) using object oriented
programming.
5. Demonstrate the need for exceptions to handle errors for object oriented programs.
Mapping Course Outcomes with Programme Outcomes:
Course Outcomes
Develop classes incorporating object-oriented
techniques.
Design and implement object-oriented concepts
of inheritance
Design and implement object-oriented concepts
of polymorphism.
Illustrate and implement STL class of containers
(Vectors, stacks, queues, lists) using object
oriented programming
Demonstrate the need for exceptions to handle
errors for object oriented programs.
Programme Outcomes
1
2
3
x
4
5
6
7
8
9
10
11
12
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Course Title: Advanced Programming with C
Course Code: CSL1533
Credits (L:T:P) : 0:0:1
Core/ Elective: Core
Type of course: Practical
Total Contact Hours: 28
Prerequisites:
Fundamentals of Computing Lab
Course Contents:
1.
2.
3.
4.
5.
6.
7.
8.
9.
Illustrating Pointers for data operations
Examining Dynamic memory allocations
Composing Arrays in programs
Managing Structures in applications
Organizing Stacks in programs
Constructing Queues for applications
Setting up Linked lists for data set operations
Formulating Trees for data set maintenance
Developing applications to solve Graph based problems
Text Books:
1. Horowitz, Sahni, Anderson-Freed: Fundamentals of Data Structures in C, 2nd Edition, Universities
Press, 2008.
Reference Books:
1.
2.
3.
Yedidyah, Augenstein, Tannenbaum: Data Structures Using C and C++, 2nd Edition, Pearson
Education, 2003.
Data Structures, Seynour Lipschutz and GAV Pai, Schaum’s Outlines, McGraw Hill, 2008.
Richard F. Gilberg and Behrouz A. Forouzan: Data Structures A Pseudocode Approach with C,
Cengage Learning, 2005
Course Delivery:
The course will be delivered using software tools in Laboratory
Course Assessment and Evaluation:
Direct
& Indirect
Assessment Methods
What
CIE
Internal
Assessment
Tests
SEE
Standard
Examination
Max
When/ Where
(Frequency in
the course)
To Whom
Marks
Once / End of
course
50
Program
Answer scripts
50
Program
Answer scripts
End of Course
Students
End of Course
Survey
Contribution to
Course
Outcomes
Evidence
Collected
1,2,3,4,5 & 6
1,2,3,4,5 & 6
1,2,3,4,5 & 6,
Delivery of the
course
End of the
course
Course Outcomes:
At the end of the course, students will be able to:
1.
2.
3.
4.
5.
6.
Illustrate dynamic memory usage in applications
Manage arrays and structures with programming solutions for real time problems
Prepare programming solutions using variations of stacks and queues
Develop data set operations using variations of linked list
Devise applications to solve tree based problems
Formulate solutions for problems based on graphs
Mapping Course Outcomes with Programme Outcomes:
Course Outcomes
Programme Outcomes
1
2
3
4
5
6
7
Illustrate dynamic memory in applications
×
×
×
×
Manage arrays and structures with programming
solutions for real time problems
×
×
×
×
×
Prepare programming solutions using variations
of stacks and queues
×
×
×
×
×
Develop data set operations using variations of
linked list
×
×
×
×
×
Devise application to solve tree based problems
×
×
×
×
×
×
Formulate solutions for problems based on
graphs
×
×
×
×
×
×
8
9
10
11
12
×
Course Title: Engineering Mathematics - IV
Course Code: CSMAT401
Credits (L:T:P) : 4:0:0
Core/ Elective: Core
Type of course: Lecture
Total Contact Hours: 56 Hrs
Prerequisites: Nil
Course Objectives:
The students will
1. Learn the concepts of finite differences, interpolation and its applications.
2. Understand the concepts of PDE and its applications to engineering.
3. Learn the concepts of Random variables and probability distributions.
4. Learn the concepts of probability distributions involving two random variables.
5. Learn the concepts of stochastic process, Markov chain and queuing theory.
6. Construct the various tests essentially needed for the testing of small samples for the testing of hypothesis.
Unit 1
Finite Differences and Interpolation: Forward, Backward differences, Interpolation, Newton-Gregory
Forward and Backward Interpolation, formulae, Lagrange interpolation formula and Newton divided difference
interpolation formula (no proof).
Numerical Differentiation and Numerical Integration: Derivatives using Newton-Gregory forward and
backward interpolation formulae, Newton-Cotes quadrature formula, Trapezoidal rule, Simpson 1/3rd rule,
Simpson 3/8th rule.
Partial Differential Equations - I: Introduction to PDE, Solution of PDE – Direct integration, Method of
separation of variables.
Unit 2
Random Variables: Random Variables (Discrete and Continuous), Probability density function, Cumulative
distribution function, Mean, Variance, Moment generating function..
Probability Distributions: Binomial distribution, Poisson distribution, Normal distribution, Exponential
distribution and Uniform distribution.
Unit 3
Joint probability distribution: Joint probability distribution (both discrete and continuous), Conditional
expectation, Simulation of random variable.
Stochastic Processes: Introduction, Classification of stochastic processes, Discrete time processes, Stationary,
Ergodicity, Autocorrelation, Power spectral density.
Unit 4
Markov Chain: Probability Vectors, Stochastic matrices, Regular stochastic matrices, Markov chains, Higher
transition probabilities, Stationary distribution of Regular Markov chains and absorbing states, Markov and
Poisson processes.
Queuing theory: Introduction, Concepts and M/G/1 and M/M/1 queuing systems with numerical illustration.
Unit 5
Sampling Theory : Sampling, Sampling distributions, Standard error, Weak law of large numbers(without
proof), Central limit theorem, Test of Hypothesis for means, Confidence limits for means, Student’s tdistribution, F-distribution, Chi-Square distribution as a test of goodness of fit.
Text Books :
1.
2.
3.
Erwin Kreyszig - Advanced Engineering Mathematics-Wiley-India publishers- 10th edition-2015.
B.S.Grewal - Higher Engineering Mathematics - Khanna Publishers - 40th edition-2007.
R.E. Walpole, R. H. Myers, R. S. L. Myers and K. Ye – Probability and Statistics for Engineers and
Scientists – Pearson Education – Delhi – 8th edition – 2007.
Reference Books :
1.
2.
3.
Sheldon M. Ross – Probability models for Computer Science – Academic Press – 2009.
Murray R Spiegel, John Schiller & R. Alu Srinivasan – Probability and Statistics – Schaum’s outlines 2nd edition.
Kishor S. Trivedi – Probability & Statistics with reliability, Queuing and Computer Science
Applications – PHI – 2nd edition – 2002.
Course Outcomes :
Students are expected to do the following:
1.
2.
3.
4.
5.
6.
To be able to find a polynomial from the given data for estimation, finding extreme values of a function,
radius of curvature, arc length, surface area etc. using numerical differentiation and integration.
Solution of partial differential equations by direct integration method and separation of variables.
Should be able to express the probability distribution arising in the study of engineering problems and their
applications.
Should be able to apply the stochastic process and Markov Chain in prediction of future events.
Should be able to calculate the various parameters of the queuing models.
Use the concepts of sampling to enable a student to take a decision about the hypothesis.
Course Title: Computer Organization
Course Code: CS1541
Credits (L:T:P) : 4:0:0
Core/ Elective: Core
Type of course: Lecture
Total Contact Hours: 56
Prerequisites:
Basics of Computers.
Course Contents:
Unit 1
Language of the Compuer: Operation of the computer hardware, Operands of the Computer Hardware, Signed
and Unsigned numbers, Representing Instructions in the Computer, Logical Operations, Instructions for making
Decisions, Supporting procedures in the computer hardware, compiling a string copy procedure, showing how to
use C strings, ARM addressing for 32-bit immediates and more complex addressing modes.
Unit 2
Arithmetic unit: Multiplication of two numbers, A signed operand multiplication, Booth algorithm, Bit pair
recoding and CSA – integer division, IEEE standard for floating point numbers, Operations, Guard bits and
truncation.
Unit 3
The Processor: Introduction, A basic MIPS Implementation, Logic Design Conventions: Clocking
methodology, Building a datapath. An overview of pipelining: Designing instruction sets for pipelining,
Pipeline hazards, Pipelined datapath and control: Graphically representing pipelines.
Unit 4
Memory unit: Introduction, The basics of Caches: Accessing a cache, Handling cache misses, Handling
writes, Designing the memory system to support caches, Measuring and improving cache performance:
Reducing cache misses by more flexible placement of blocks, Locating a block in the cache, choosing which
block to replace, Reducing the miss penalty using multilevel caches. Virtual memory: Placing a page and
finding it again, Page faults, TLB.
Unit 5
Input Output Unit: Introduction, Dependability, Reliability, and availability, Disk storage, Flash memory,
Connecting processors, memory, and I/O devices, Interfacing I/O devices to the processor, memory, and
operating system, I/O performance measures, Designing an I/O system, parallelism and I/O.
Text Books:
1. David A. Petterson, John L. Hennessy: Computer Organization and Design, M.K Publishers, 4th
edition, 2010
2. C Hamacher, Z Vranesic, S Zaky: Computer Organization, Tata McGraw Hill, 5th edition, 2011.
Reference Books:
1. John L. Hennessey and David A. Patterson: Computer Architecture, A Quantitative Approach, 5th
Edition,
Elsevier, 2012.
2. W. Stallings: Computer Organization and Architecture: Designing For Performance, 8th edition,
Prentice hall, 2012.
Course Delivery: Through lectures, practicals and presentation
Course Assessment and Evaluation:
Direct & Indirect Assessment Methods
What
CIE
To whom
Thrice(Average
of the best two
will be
computed)
Internal
assessment
tests
Online
course/Quiz
SEE
Standard
examination
End of course
survey
When/ Where
(Frequency in
the course)
Once
Students
End of course
(Answering 5 of
10 questions)
End of course
Max
marks
Evidence
collected
Contributing
to Course
Outcomes
30
Blue books
1, 2,3,4,5,6 & 7
20
Certificates/Quiz
Marks
1, 2,3,4,5,6 & 7
100
Answer scripts
1, 2,3,4,5,6 & 7
Questionnaire
1, 2,3,4,5,6 & 7
Effectiveness of
Delivery of
instructions &
Assessment
Methods
-
Course Outcomes:
At the end of the course, the student must be able to:
1. Identify the operations & operands of a digital computer also summarize ARM instruction set and
addressing modes.
2. Discuss various techniques that have proven useful in design a circuit to perform fast multiplication
and division.
3. Use a standard IEEE format to convert floating-point number into binary format along with the
methods to remove guard bits.
4. Organize a datapath for MIPS architecture using design principles and techniques.
5. Compare the parallelism over sequential instruction stream by using pipelining concept.
6. Examine the cache memory performance including the advantages of using virtual memory technique.
7. Describe the interface of I/O devices with the system including I/O performance measures.
Mapping Course Outcomes with Programme Outcomes:
Course Outcomes
Identify the operations & operands of a digital computer
also summarize ARM instruction set and addressing
modes.
Discuss various techniques that have proven useful in
design a circuit to perform fast multiplication and
division.
Use a standard IEEE format to convert floating-point
number into binary format along with the methods to
remove guard bits.
Organize a datapath for MIPS architecture using design
principles and techniques.
Compare the parallelism over sequential instruction
stream by using pipelining concept.
Examine the cache memory performance including the
advantages of using virtual memory technique
Describe the interface of I/O devices with the system
including I/O performance measures.
Programme Outcomes
1
x
2
x
x
3
4
x
5
x
6
7
8
9
10
11
12
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Course Title: Design and Analysis of Algorithms
Course Code: CS1542
Credits (L:T:P): 3:1:0
Core/ Elective: Core
Type of Course: Lecture
Total Contact Hours: 70 hrs
Prerequisites: Nil
Course Contents:
Unit 1
Asymptotic Bounds and Representation problems of Algorithms: Computational Tractability: Some Initial
Attempts at Defining Efficiency, Worst-Case Running Times and Brute-Force Search, Polynomial Time as a
Definition of Efficiency, Asymptotic Order of Growth: Properties of Asymptotic Growth Rates, Asymptotic
Bounds for Some Common Functions, Implementing the Stable Matching Algorithm, Using Lists and Arrays:
Arrays and Lists, Implementing the Stable Matching Algorithm, A Survey of Common Running Times: Linear
Time, O(n log n) Time, Quadratic Time, Cubic Time, O(nk) Time, Beyond Polynomial Time, Sub linear Time.
Some Representative Problems, A First Problem: Stable Matching: The Problem, Designing the Algorithm,
Analyzing the Algorithm, Extensions, Five Representative Problems: Interval Scheduling, Weighted Interval
Scheduling, Bipartite Matching, Independent Set, Competitive Facility Location
Unit 2
Graphs & Divide and Conquer: Graph Connectivity and Graph Traversal, Breadth-First Search: Exploring a
Connected Component, Depth-First Search, Implementing Graph Traversal Using Queues and Stacks:
Implementing Breadth-First Search, Implementing Depth-First Search, An Application of Breadth-First Search:
The Problem, Designing the Algorithm, Directed Acyclic Graphs and Topological Ordering: The Problem,
Designing and Analyzing the Algorithm, A First Recurrence: The Merge sort Algorithm: Unrolling the Merge
sort Recurrence, Counting Inversions: The Problem, Designing and Analyzing the Algorithm.
Unit 3
Greedy Algorithms: Interval Scheduling: The Greedy Algorithm Stays Ahead: Designing a Greedy Algorithm,
Analyzing the Algorithm, Scheduling to Minimize Lateness: An Exchange Argument: The Problem, Designing
the Algorithm, Optimal Caching: A More Complex Exchange Argument: The Problem, Designing and
Analyzing the Algorithm, Extensions: Caching under Real Operating Conditions, Shortest Paths in a Graph: The
Problem, Designing the Algorithm, Analyzing the Algorithm, The Minimum Spanning Tree Problem: The
Problem, Designing Algorithms, Analyzing the Algorithms, Huffman Codes and Data Compression: The
Problem, Designing the Algorithm.
Unit 4
Dynamic Programming: Weighted Interval Scheduling: A Recursive Procedure: Designing a Recursive
Algorithm, Subset Sums and Knapsacks: Adding a Variable: The Problem, Designing the Algorithm, Shortest
Paths in a Graph: The Problem, Designing the Algorithm, The Maximum-Flow Problem and the Ford-Fulkerson
Algorithm: The problem, Designing the Algorithm, Survey Design: The problem, Designing the Algorithm,
Analyzing the Algorithm, Airline Scheduling: The problem, Designing the Algorithm, Analyzing the Algorithm.
Unit 5
NP and Computational Intractability: Polynomial-Time Reductions A First Reduction: Independent Set and
Vertex Cover, Reducing to a More General Case: Vertex Cover to Set Cover, NP-Complete Problems: Circuit
Satisfiability: A First NP-Complete Problem, General Strategy for Proving New Problems NP-Complete,
Sequencing Problems: The Traveling Salesman Problem, The Hamiltonian Cycle Problem.
Text Books
1. Algorithm Design - Jon Kleinberg and Eva Tardos, Pearson ,1st Edition (2013).
Reference Books
1. AnanyLevitin: Introduction to The Design & Analysis of Algorithms, 2nd Edition, Pearson Education,
2007.
Course Delivery:
The course will be delivered through lectures in the classroom.
Course Assessment and Evaluation :
To
Whom
Direct & Indirect Assessment
Methods
What
CIE
Internal
Assessment
Test
SEE
Standard
Examination
Students
End of Course
Survey
When/ Where
(Frequency in
the course)
Thrice (Average
of the best two
will
be
computed)
End of Course
(Answering
5
of
10
questions)
End
of
course
the
Max
Marks
Evidence
Collected
Contribution
to
Course Outcomes
30
Blue Books
1, 2, 3, 4,5 & 6
100
Answer
scripts
1, 2, 3, 4,5 & 6
Questionnaire
1, 2, 3, 4,5 & 6
Effectiveness
of
Delivery
of
instructions
&
Assessment Methods
-
Course Outcomes
At the end of the course the students should be able to:
1. Define the basic concepts and analyze worst-case running times of algorithms using asymptotic
analysis.
2. Recognize the design techniques for graph traversal using representative algorithms.
3. Identify how divide and conquer works and analyse complexity of divide and conquer methods by
solving recurrence.
4. Illustrate Greedy paradigm and Dynamic programming paradigm using representative algorithms.
5. Describe the classes P, NP, and NP-Complete and be able to prove that a certain problem is NPComplete.
6. Examine the techniques of proof by contradiction, mathematical induction and recurrence relation, and
apply them to prove the correctness of the running time of algorithms.
Mapping Course Outcomes with Programme Outcomes
Course Outcomes
Define the basic concepts and analyze worst-case running
times of algorithms using asymptotic analysis.
Recognize the design techniques for graph traversal using
representative algorithms.
Identify how divide and conquer works and analyse
complexity of divide and conquer methods by solving
recurrence.
Illustrate Greedy paradigm and Dynamic programming
paradigm using representative algorithms.
Describe the classes P, NP, and NP-Complete and be able to
prove that a certain problem is NP-Complete.
Examine the techniques of proof by contradiction,
mathematical induction and recurrence relation, and apply
them to prove the correctness of the running time of
algorithms.
1
2
3
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Programme Outcomes
4 5 6 7 8 9 10
x
x
x
x
11
12
Course Title: Introduction to Microprocessors
Course Code: CS1543
Credits (L:T:P) : 4:0:0
Core/ Elective: Core
Type of course: Lecture
Total Contact Hours: 56
Prerequisites:
Nil
Course Contents:
Unit 1
Introduction to Microprocessors: Internal Microprocessor Architecture (8086 to Pentium), Flag register of 8086,
Real mode memory addressing, Pin outs and Pin functions of 8086, Bus buffering and latching, Bus timing,
Ready and Wait state, Addressing modes: Data, Program memory, Stack memory.
Unit 2
Instruction set of 8086: Data move, Arithmetic and Logic, Program control. Assembler directives, Assembly
language programming, Programs using BIOS and DOS interrupts, assembly language programming with
C/C++ for 16 bit applications.
Unit 3
Memory interfacing: Address decoding, Static memory interfacing with 8086. Introduction to dynamic memory
interfacing. Introduction to I/O interface, I/O port address decoding (8 bit and 16 bit). Simple programs related
to I/O interface.
Unit 4
PPI: Study of 8255: control word, different modes of operation. Study of 8279. Interfacing programs with:
Stepper motor, Keyboard, Display, Timer and ADC/DAC interfaces.
Unit 5
Basic Interrupt processing, Hardware interrupts, expanding the interrupt structure, interrupt examples. Basic
DMA operations, study of 8237 DMA controller. Introduction to MMX technology.
Text Book:
1. Barry B Brey: The Intel Microprocessors-Architecture, Programming and Interfacing, Eighth Edition,
Pearson Education, 2009.
Reference Books:
1. A.K Ray, K.M.Bhurchandi : Advanced Microprocessors and Peripherals, 2nd edition, TMH, 2004
2. Uffen Beck: 8086:Architecture and Interfacing, 2nd edition, John Wiley, 2005.
Course Delivery:
The course will be delivered through lectures, class room interaction, group discussion and exercises and selfstudy cases.
Course Assessment and Evaluation:
Direct & Indirect Assessment Methods
What
To
Whom
Internal
Assessment Tests
CIE
When/ Where
(Frequency in
the course)
Thrice(Average
of the best two
will be
computed)
Standard
Examination
Students
End of Course
Survey
Evidence
Collected
Contribution to
Course Outcomes
30
Blue Books
1, 2, 3, 4,5 & 6
Data Sheets
1, 2, 3, 4,5 & 6
Answer
scripts
1, 2, 3, 4,5 & 6
Questionnaire
1, 2, 3, 4,5 & 6
Effectiveness of
Delivery of
instructions &
Assessment
Methods
Twice
20
End of Course
(Answering
5 of 10 questions)
100
Quiz
SEE
Max
Marks
End of the course
-
Course Outcomes:
At the end of the course the students should be able to:
1. Explain the Intel 8086 architecture, pin functions and bus timing diagrams.
2. Develop 8086 assembly language programs for different applications.
3. Design memory and I/O interfacing circuits with the help of PPI to the 8086 processor.
4. Test the 8086 assembly language programs on different interfacing boards.
5. Formulate interrupt programs with 8086 hardware and software interrupt methods.
6. Explain the MMX technology used in processors.
Mapping Course Outcomes with Programme Outcomes:
Course Outcomes
Explain the Intel 8086 architecture, pin functions
and bus timing diagrams.
Develop 8086 assembly language programs for
different applications.
Programme Outcomes
1
x
Design memory and I/O interfacing circuits with the
help of PPI to the 8086 processor.
Test the 8086 assembly language programs on
different interfacing boards.
Formulate interrupt programs with 8086 hardware
and software interrupt methods.
Explain the MMX technology used in processors.
x
2
3
4
5
6
7
8
9
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
10
11
12
x
x
Course Title: Data Communication
Course Code: CS1544
Credits (L:T:P) : 3:1:0
Core : Core
Type of Course: Lecture
Total Contact Hours: 70 Hrs
Prerequisites: Nil
Course Contents:
Unit 1
Data Communications, Networks, Network Types, Network Models – Protocol layering, TCP/IP Protocol
Suite, The OSI Model, Physical layer: Transmission impairment, Date Rate Limits, Performance.
Unit 2
Digital Transmissions – Digital to Digital Conversion, Analog to Digital Conversion, Transmission Modes.
Analog Transmission- Digital to Analog conversion, Analog to Analog conversion. Multiplexing and Spectrum
Spreading-Multiplexing,, Spread Spectrum.
Unit 3
Switching:- Introduction, Circuit switched networks, Packet Switching, Structure of a Switch. Error Detection
and Correction-Introduction, Block Coding, Cyclic Codes – CRC, Polynomials, Cyclic code encoder using
Polynomials, Cyclic code analysis, Advantages of cyclic codes. Checksum, Forward Error Correction
Unit 4
Data Link Layer: Data Link Control –DLC services, Data link layer protocols , HDLC , Point to Point Protocol.
Multiple Access Control – Random Access, Controlled access, Channelization Network Interface Adaptors:
NIC Functions, NIC Features: Full Duplex, Bus Mastering, Parallel Tasking, Wake on LAN IEEE 802.p.
Unit 5
Wired LAN’s Ethernet Protocol, Standard Ethernet, Fast Ethernet, Gigabit Ethernet, 10 Gigabit Ethernet,
Wireless LANs- Introduction, IEEE 802.11- Bluetooth , Connecting Devices and Virtual LANs–Connecting
Devices, Virtual LANs
Text Book:
1. Data Communication and Networking, Behrouz A.Forouzan, McGraw Hill, 5th Edition, 2008.
2. The Complete Reference Networking Craig Zacker McGraw-Hill Twelfth reprint 2008
Reference Books:
1. Data and Computer Communication, William Stallings, 8th Edition, Pearson Education, 2007.
2. Introduction to Data Communications and Networking – Wayne Tomasi, Pearson Education, 2005.
Course Delivery:
The Course will be delivered through classroom teaching, interactions with the students, discussing interesting
electronic systems in the class room where the subsystems are being used, providing guest lectures and
practical sessions by distinguished network resource persons.
Course Assessment and Evaluation:
Direct & Indirect Assessment Methods
What
To
Whom
Internal
Assessment Tests
CIE
Assignment,
Practical
Implementation
SEE
Standard
Examination
Students
End of Course
Survey
When/ Where
(Frequency in
the course)
Thrice(Average
of the best two
will be
computed)
Max
Marks
Evidence
Collected
Contribution to
Course Outcomes
30
Blue Books
1,2,3,4,5,6 & 7
once
20
Assignment
& Lab
Answer
Sheets
1,2,3,4,5,6 & 7
End of Course
(Answering
5 of 10 questions)
100
Answer
scripts
1,2,3,4,5,6 & 7
End of the course
-
Questionnaire
1,2,3,4,5,6 & 7
Effectiveness of
Delivery of
instructions &
Assessment
Methods
Course Outcomes:
At the end of the course, the students will be able to:
1. Identify the different types of network topologies and protocols
2. Summarize the layers and functions of OSI and TCP/IP models.
3. Classify the different types of data transmissions and networks based on their working principle
4. Solve problems in Error detection and corrections carried at Data Link Layer.
5. Assess algorithms for the different ARQ protocols and frame formats of HDLC and PPP.
6. Describe the principles of access control to shared media
7. Identify the different internetworking devices and their functions.
Mapping Course Outcomes with Programme Outcomes:
Course Outcomes
Identify the different types of network topologies and
protocols
Summarize the layers and functions of OSI and
TCP/IP models.
Classify the different types of data transmissions and
networks based on their working principle
Solve problems in Error detection and corrections
carried at Data Link Layer.
Assess algorithms for the different ARQ protocols
and frame formats of HDLC and PPP.
Describe the principles of access control to shared
media
Identify the different internetworking devices and
their functions.
Programme Outcomes
1
2
3
4
5
x
x
x
x
x
x
6
7
x
x
x
x
x
x
x
x
x
x
8
9
10
11
12
Course Title: Python Laboratory
Course Code: CSL1541
Credits (L:T:P) : 0:1:1
Core/ Elective: Core
Type of course: Tutorial, Practical
Total Contact Hours: 56
Prerequisites: No explicit prerequisite, but students are expected to have a fundamental understanding of basic
computer principles.
Course Contents:
There shall be a minimum of 2 exercises conducted on each of the following topics.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
Python Basics
Control Structures
Functions
Strings, lists, list comprehensions
Tuples and dictionaries
modules and packages
Object Oriented Concepts
Regular Expression
Programs on File I/O
Exceptions
Network Programming
GUI Programming
Design a simple game application using pygame
Game application Demo.
Reference Books:
1. Mark Lutz: Learning Python, 5th Edition, Orielly Publications.
2. John Zelle : Python Programming: An Introduction to Computer Science, 2nd Ed.ition.
3. Pygame 1.5.5 Reference Manual
Course Delivery:
The course will be delivered through lectures in the laboratory with exercises.
Course Assessment and Evaluation:
To
Whom
What
Direct & Indirect Assessment Methods
Lab Test
Max
Marks
Evidence
Collected
Contribution to
Course Outcomes
20
Data sheets
1,2,3 & 4
miniproject
Demo at the end
of semester
20
code
1,2,3 & 4
Viva
Every
Week(Average of
the total score will
be computed)
10
Viva Result
Sheets
Recollection Skills
End of Course
(Executing
2
programs)
50
CIE
Students
SEE
When/
Where
(Frequency in the
course)
1Lab Test
Lab
Examination
End of Course
Survey
End of the course
-
Answer
scripts
1,2,3 & 4
Questionnaire
1,2,3 & 4
Effectiveness of
Delivery of
instructions &
Assessment
Course Outcomes:
At the end of the course, students should be able to:
1. Analyze the principles of object-oriented programming and the interplay of algorithms and data
structures in well-written modular code.
2. Design well-documented programs in the Python language, including use of the logical constructs of
that language.
3. Use python modules and packages to get significant experience with the Python programming
environment.
4. Develop game application using Python
Mapping Course Outcomes with ProgrammeOutcomes:
Course Outcomes
Analyze the principles of object-oriented
programming and the interplay of algorithms
and data structures in well-written modular code
Design
well-documented programs in the
Python language, including use of the logical
constructs of that language
use python modules and packages to gain
significant experience with the Python
programming environment
Develop game application using Python
ProgrammeOutcomes
1
2
3
4
5
6
7
8
9
10
11
12
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Course Title: : Algorithms Laboratory
Course Code: CSL1542
Credits (L:T:P) : 0:0:1
Core/ Elective: Core
Type of course: Practical
Total Contact Hours: 28
Prerequisites: Knowledge of Data Structures and any one programming language.
Course Contents:
1.
2.
3.
4.
5.
6.
7.
8.
Brute force techniques.
Stable matching
Graph traversing using BFS and DFS.
Divide and Conquer Techniques
Greedy algorithms
Dynamic Programming algorithms.
Network Flow algorithms.
NP problems.
Reference Books:
1.
2.
Algorithm Design - Jon Kleinberg and Eva Tardos, Pearson Publications, 1st edition (2013).
AnanyLevitin: Introduction to The Design & Analysis of Algorithms, 2nd Edition, Pearson Education,
2007.
Course Delivery:
The course will be delivered through algorithmic concepts to confirm the learnt concepts by simulating
some simple exercises.
Course Assessment and Evaluation:
Direct & Indirect Assessment
Methods
What
To Whom
When/ Where
(Frequency in
the course)
Max
Marks
Evidence
Collected
Contribution to
Course Outcomes
CIE
Internal
Assessment
Tests
Twice
50
Data Sheets
1,2 3,4,5
SEE
Standard
Examination
End of Course
(Answering 5
of 10
questions)
50
Answer
scripts
1,2,3,4 &5
Questionnaire
1, 2,3,4 & 5
Effectiveness of
Delivery of
instructions &
Assessment
Methods
Students
End of Course
Survey
End of the
course
-
Course Outcomes:
At the end of the course, student should be able to:
1. Illustrate the methodologies of Graph Traversing
2. Illustrate the methodologies of Divide and conquer and evaluate the complexity.
3. Solve the problems using Network flow algorithms.
4. Formulate the time-complexity analysis for Dynamic programming and greedy techniques.
5. Examine and Design NP problems for a given case study.
Mapping Course Outcomes with ProgrammeOutcomes:
ProgrammeOutcomes
Course Outcomes
Illustrate the methodologies of Graph
Traversing
Illustrate the methodologies of Divide and
conquer and evaluate the complexity
Solve the problems using Network flow
algorithms
Formulate the time-complexity analysis
for Dynamic programming and greedy
techniques.
Examine and Design NP problems for a
given case study.
1
2
3
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
4
5
6
7
8
9
10
11
12
Course Title: Microprocessor and CO Lab
Course Code: CSL1543
Credits (L:T:P) : 0:0:2
Core/ Elective: Core
Type of course: Practical
Total Contact Hours: 56
Prerequisites: Nil
Course Contents:
Computer Organization Lab:
1. Demonstrating instruction execution stages using Simulator
2. Executing an ARM programs using simulator
3. Designing an ALU to perform various functions using simulator.
4. Implementing different multiplication algorithms using simulator.
5. Implementing CPU functions using simulator.
6. Designing memory system operations using simulator.
7. Designing associative and direct mapped cache memory.
Microprocessor Lab:
1. Assembly language program to perform basic arithmetic operations on 16-bit & 32-bit registers.
2. Assembly language program to perform various searching and sorting techniques on array of numbers.
3. Assembly language program to perform basic operations on strings
4. Assembly language program to demonstrate the working of functions and recursive functions.
5. Assembly language program to create interrupt driven programs.
6. Assembly language program to interface the 8086 with Logical controller unit.
7. Assembly language program to interface the 8086 with Stepper motor.
8. Assembly language program to interface the 8086 with I/O devices.
Course Assessment and Evaluation:
Direct & Indirect Assessment Methods
What
CIE
To whom
Lab test
When/ Where
(Frequency in
the course)
Max
marks
Evidence
collected
Twice
40
Data sheets
1, 2,3,4,5,6,7 & 8
Project
report/Viva
Marks
1, 2,3,4,5,6,7 & 8
10
50
Answer scripts
1, 2,3,4,5,6,7 & 8
Questionnaire
1,2, 3,4,5,6,7 & 8
Effectiveness of
Delivery of
instructions &
Assessment
Methods
Once
Project/Viva
SEE
Standard
examination
End of course
survey
Students
End of course
(Executing Two
Programs)
End of course
Course Delivery:
The course will be delivered through practical exercises.
-
Contributing to
Course Outcomes
Course Outcomes:
At the end of the course the student should be able to:
1. Examine instruction execution stages using simulator
2. Formulate ARM programs with simulator
3. Design ALU to perform Arithmetic and Logical operations using simulator
4. Design CPU and memory functions using simulator
5. Prepare 8086 assembly language programs to perform basic arithmetic operations.
6. Devise 8086 assembly programs using searching and sorting techniques.
7. Test assembly language programs with I/O devices connected to 8086 processor.
8. Develop interrupt driven programs using hardware and software interrupt methods of 8086 processor.
Mapping Course Outcomes with ProgrammeOutcomes:
Course Outcomes
ProgrammeOutcomes
4
5
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Devise 8086 assembly programs using searching
and sorting techniques.
x
x
x
Test assembly language programs with I/O
devices connected to 8086 processor.
x
x
x
x
x
x
Examine instruction execution stages using
simulator
Formulate ARM programs with simulator
Design ALU to perform Arithmetic and Logical
operations using simulator
Design CPU and memory functions using
simulator
Prepare 8086 assembly language programs to
perform basic arithmetic operations.
Develop interrupt driven programs using
hardware and software interrupt methods of
8086 processor.
1
2
x
3
6
7
8
9
10
11
12
Course Exit Survey Form
Dept of CSE, MSRIT, Bangalore
Name & USN of the student:
Contact details:
Sl
No.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
Question
Quality of the course content
For the number of credits, the course workload
was
Relevance of the textbook to this course
Ideas/Concepts that you have found difficult to
grasp
Concepts/topics that should be removed from the
syllabus
New inclusions in the syllabus
Were the lectures clear/well organized and
presented at a reasonable pace?
Did the lectures stimulate you intellectually?
What approaches/aids would facilitate your
learning? You can check multiple options.
Did the problems worked out in the classroom
help you to understand how to solve questions on
your own?
Is the grading scheme clearly outlined and
reasonable/fair?
Are the assignment/lab experiment procedures
clearly explained?
Attainment level of CO1
Attainment level of CO2
Attainment level of CO3
Attainment level of CO4
Attainment level of CO5 ..COn
Excellent
Very Good
Course code:
Course name:
Responses
Good
Satisfactory
Poor
List
List
List
Yes/No
Yes/No
Lectures/ Programming Assignments/ Presentations/ Tutorials/ Demonstrations/ Practical Exercises/
Mini projects/ Group discussions/ Student seminars/ Expert guest lectures
Yes/No
Yes/No
Yes/No
Signature of the student with date