SYLLABUS

FOR

M. Sc. COMPUTER SCIENCE

(2019-2021)

MAHARAJA SRIRAM CHANDRA BHANJA DEO UNIVERSITY

(ERSTWHILE NORTH ORISSA UNIVERSITY)

SRIRAM CHANDRA VIHAR, TAKATPUR,

BARIPADA, ODISHA, PIN-757003

(Dr.S.S.Basa) (Dr.P.S.Mishra) (Dr.M.Sahu)

Syllabus CS

2

Course Outcomes:

The Master degree program in Computer Science provides the students with the knowledge,

general competence, and analytical skills on an advanced level, needed in academics, industry,

research.

The syllabus for M.Sc. Computer Science programme is designed to attain the following

broad objectives. After completion of the course the student shall:

Be technology-oriented with the knowledge and ability to develop creative solutions, and

better understand the effects of future developments of computer systems and technology

on people and society.

Use research-based knowledge and research methods including design of experiments,

analysis, and interpretation of data, and synthesis of the information to provide valid

conclusions.

Get some development experience within a specific field of Computer Science, through

project work.

Develop skills to learn new technology.

Apply computer science theory and software development concepts to construct

computing-based solutions.

Design and develop computer programs/computer-based systems in the areas related to

algorithms, networking, web design, cloud computing, etc.

Create, select, and apply appropriate techniques, resources, and modern engineering and

IT tools including prediction and modeling to complex computational activities with an

understanding of the limitations.

Function effectively as an individual, and as a member or leader in diverse teams, and a

multidisciplinary setting

Demonstrate knowledge and understanding of the computer science and management

principles and apply these to one’s work, as a member and leader in a team, to manage

projects and in multidisciplinary environments.

Able to initiate and lead projects within the scientific field and be responsible for the

work of individuals and groups.

Syllabus CS

3

Course Specific Outcomes:

In terms of course specific context of M.Sc. Computer Science the outcomes are as follows.

Design and develop computer programs/computer-based systems in the areas related to

algorithms, networking, web design, cloud computing, IoT and data analytics of varying

complexity.

Acquaint with the contemporary trends in industrial/research settings and there by

innovate novel solutions to existing problems. After completing M.Sc. Computer Science

students will be able to enrich the knowledge in the areas like Artificial Intelligence, Web

Services, Cloud Computing, Paradigm of Programming language, Design and Analysis of

Algorithms, Database Technologies Advanced Operating System, Mobile Technologies,

Software Project Management, and core computing subjects. Students understand all

dimensions of the concepts of software application and projects.

Students understand the computer subjects with a demonstration of all programming and

theoretical concepts with the use of ICT. To make them employable according to the

current demand of IT Industry and responsible citizen.

Developed in-house applications in terms of projects. Aware them to publish their work

in reputed journals. Apply standard Software Engineering practices and strategies in real-

time software project development using an open-source programming environment or

commercial environment to deliver quality products for the organization success.

Syllabus CS

4

CONTENTS

Semester Pages First Semester 7-14

Second Semester 15-22

Third Semester 23-32

Fourth Semester 33-37

Syllabus CS

5

M. Sc Computer Science 2016-2018

FIRST YEAR

Semester-1st

Paper

No Subject Title of the Paper Credit

Max. Marks

Internal Univ. Exam Total

CS-401 Core Programming in C 4 20 80 100

CS-403 Core Computer System Architecture 4 20 80 100

CS-405 Core Internet and Web Technology 4 20 80 100

CS-407 Core Discrete Mathematics 4 20 80 100

CS-409 Core Operating System 4 20 80 100

CS-411 Practical Programming Lab-I(Using C) 4 100

CS-413 Practical Programming Lab-II(IWT) 4 100

Total 28 700

Semester-2

nd

Paper

No Subject Title of the Paper Credit

Max. Marks

Internal Univ. Exam Total

CS-402 Core Theory of Computation 4 20 80 100

CS-404 Core Advanced Data Structures 4 20 80 100

CS-406 Core Distributed Database Systems 4 20 80 100

CS-408 Core Object Oriented Software Engineering 4 20 80 100

CS-410

Elective-I

Digital Image Processing &

Multimedia

OR Optimization Techniques

4

20

80

100

CS-412 Practical Programming Lab-III(Advanced Data Structure)

4

100

CS-414 Practical Programming Lab-IV (Distributed Database Systems)

4

100

Total 28 700

Syllabus CS

6

SECOND YEAR

Semester-3rd

Paper

No Subject Title of the Paper Credit

Max. Marks

Internal Univ. Exam Total

CS-501 Core Numerical Computing 4 20 80 100

CS-503 Core Advanced Computer Networks 4 20 80 100

CS-505 Core Systems Programming & Compiler Design

4 20 80 100

CS-507 Core Concept of Core & Advanced JAVA 4 20 80 100

CS-509 Elective-II Bioinformatics

OR Data Mining & Warehousing

4 20 80 100

CS-511 Practical Programming Laboratory- V (Computer Networks)

4 100 100

CS-513 Practical Programming Laboratory- VI (Based on JAVA)

4 100 100

Total 28 700

Semester-4

th

Paper

No Subject Title of the Paper Credit

Max. Marks

Internal Univ. Exam Total

CS-502 Core Design and Analysis of Algorithms 4 20 80 100

CS-504 Elective-

III

Computational Intelligence

OR Pattern Recognition

4 20 80 100

CS-506 Dissertation & Viva Voce 8 200

Total 16 400

Syllabus CS

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FIRST YEAR

Semester-1ST

Paper

No Subject Title of the Paper Credit

Max. Marks

Internal Univ. Exam Total

CS-401 Core Programming in C 4 20 80 100

CS-403 Core Computer System Architecture 4 20 80 100

CS-405 Core Internet and Web Technology 4 20 80 100

CS-407 Core Discrete Mathematics 4 20 80 100

CS-409 Core Operating System 4 20 80 100

CS-411 Practical Programming Lab-I(Using C) 4 100

CS-413 Practical Programming Lab-II(IWT) 4 100

Total 28 700

Syllabus CS

8

SEMETSER-I

CS-401 PROGRAMMING IN C Credit: 04

Course Outcome: Upon completion of this course Students will acquire the knowledge to implement the

algorithms and draw flowcharts for solving mathematical and engineering problems.The student

will understand the importance of basic principles of C Programming, acquire decision making

and looping concepts and ability to design and develop modular programming. Also students will

explore usage of Arrays, Strings, Structures and Files. Students will be able to utilize the

pointers, preprocessor directives and various data structures efficiently. Develop confidence for

self-education and ability for life-long learning needed for Computer language to solve real

world problems.

Unit I Fundamentals of Disk Operating System, Linux commands and editor, Introduction to

programming and programming languages: Evolution of programming languages; algorithm,

flow charts, structured programming, the compilation process: object code, source code,

executable code; operating system: types, evolution, translators.

Unit II C Language Fundamentals: Character set, Identifiers, Keywords, Data Types, Constant and

Variables, Statements, Expressions, Operators, Precedence of operators, Input-output

Assignments, Control structures, Decision making and Branching, Decision making & looping.

Unit III Arrays, Strings & Functions: One dimensional & Multidimensional array and their applications,

Declarations, Manipulation. & String- handling functions. Modular programs, User defined

predefined functions, formal vs Actual arguments, Functions category, function prototypes,

parameter passing, Recursion, Storage Classes: Auto, Extern, Global, and Static.

Unit IV Pointers: Pointer variable and its importance, Pointer Arithmetic, passing parameters by

reference, Structures, Union and File handling: Declaration of structures, pointer to structure,

pointer to function, unions, Dynamic memory allocations, unions, file management.

Recommended Books:

1. Brian W. Kernighan & Dennis M. Ritchie, The C Programming Language, Prentice Hall of India, 2nd

Edition, 1988.

2. Byron S. Gottfried, Programming in C, Tata McGraw-Hill, 2nd Edition, 1998.

3. S. Dehuri, P. S. Mishra, B. Dinda, and N. Padhy, Programming in C, India-Tech,

New Delhi, 2011.

4 V. Rajaraman , Computer Programming in C, Prentice Hall of India, 2002.

5 Yashavant Kanetkar, Exploring C, 2nd Edition, BPB Publications.

Syllabus CS

9

SEMETSER-I

CS-403 COMPUTER SYSTEM ARCHITECTURE Credit: 04

Course Outcome:

After the course, the students can able to explain the organization and architecture of a

basic computer, classify and compute the performance of machines and their instructions.

Describe the operations and language of the register transfer micro-operations and input-output

organization. Students can also able to identify and compare different methods for computer I/O,

describe various data transfer techniques in digital computers and the I/O interfaces, understand

the organization of memory with memory management hardware and explain the function of

each element of a memory hierarchy. And finally, they were able to describe advanced concepts

of computer architecture like Parallel Processing, pipelined architectures, interprocessor

communication, and synchronization, etc.

Unit I

Register transfer and Micro Operations: Register Transfer Language, Arithmetic, Logic and Shift

Micro Operations. Basic Computer Organization and Design : Instruction Codes, ,Computer

Instructions, Timing and Control, Instruction Cycle, Memory-Reference Instructions, Input-

Output and Interrupt.

Programming the Basic Computer: Machine Language, Assembly Language, The Assembler,

Subroutines.

Unit II Micro Programmed Control: Control Memory, Address sequencing, Design of Control Unit.

Input-Output Organization: Peripheral Devices, Input-Output Interface, Modes of Transfer,

Priority interrupt, Direct Memory Access, Input Output Processor, Serial Communication.

Unit III

Memory Organization: Memory Hierarchy, Main Memory, Auxillary Memory, Associative

Memory, Cache Memory, Virtual Memory

Unit IV

Pipeline and Vector Processing: Pipelining, Arithmetic Pipeline, Instruction Pipeline, RISC

Pipeline, Vector Processing.. Multiprocessors: Characteristics of Multiprocessors,

Interconnection Structures, Interprocessor Communication and Synchronization.

Recommended Books:

1. Computer System Architecture by M. Morris Mano.

2. Computer Organization and Architecture by William Stallings.

Syllabus CS

10

SEMETSER-I

CS- 405 INTERNET AND WEB TECHNOLOGY Credit: 04

Course Outcome:

The goal is to understand the basics of computer networks and HTTP protocol and also

get familiar with basics of the Internet Programming. The student will understand the web

technologies to create web-pages for web application. And learn about how HTML works, and

then will proceed to more advanced and complicated structures and concepts of web design, such

as CSS. One will know how to use web programming languages and be capable of construction

demanding web application on their own.

Unit-I

Internet Overview, Evolution of Internet: Internet component – Types of network, Internet

component- Network Hardware, Network Software, Packet Switching Fundamentals and Circuit

Switching, Efficiency, Packet Switching : Datagram Switched Network, Virtual Circuit-switched

Network, Efficiency Packet Switching versus Circuit Switching, Internet Standards : IETF, ITU

IEEE, ATM Forum, Access Methods and Internet working, Access Network architectures and

characteristics, Differences between Access Networks, Local Area Networks and Wide Area

Networks

Unit-II

Internet Protocol:IP format, IPv4, IP Addressing, Subnet and Subnet Mask, Class-less Address,

Superneting, IPv6 Datagram Format, IPv4 vs. IPv6, TCP Fundamentals: TCP 3-way Hand

shaking

TCP/IP: routing, Networking protocols: Network Protocol Overview: Networking protocols in

TCP/IP, ARP-RARP-BGP-EGP, NAT, DHCP, Voice grade modems, ADSL Cable Modems,

Frame Relay, DNS: Domain Names, Resolving Domain Names to IP addresses (DNS operation),

Registering Domain Names and solving Domain name disputes.

Unit-III

HTML Fundamentals: Basic HTML tools, Terminology, Creating a HTML document, including

whitespace Hyperlinks & Anchors, Working with Lists, Working with Images: Adding images,

including image links, creating image maps Working with Tables: creating tables, spanning rows

and columns, Table captions, table formatting, advanced table tags. Working with Forms:

Navigating through form, access keys, processing forms, design issues Working with Frames:

Creating framed documents, formatting frame, Communicating between frames, Inline frames,

Working with Style Sheets: Associating style sheets with HTML documents, Cascading Style

Sheets (CSS), Style Sheet properties

Unit- IV

Internet applications: FTP, FTP implementation, Internet applications: Telnet, Email, Chat,

World Wide Web: HTTP protocol, HTTP protocol Implementation and issues, Search Engines,

E-Commerce and security, Security: symmetric and asymmetric key, Encryption and digital

signature, authentication, Internet telephony, Virtual reality over the web etc. Intranet and

extranet, firewall.

Syllabus CS

11

Recommended Books:

1. Data & Computer Communications, By William Stallings

2. Internetworking with TCP / IP, Principles, Protocols & Architecture, By Douglas E.Comer.

3. Computer Networking Kurose and Ross.

4. Computer Networks, A system approach by Larry L.Peterson, Bruce S. Davie.

5. Data Communications and Networking by Behrouz A.Forouzan.

6. William Stallings, Cryptography and Network Security: Principles and Practices, Pearson Education,

2006.

Syllabus CS

12

SEMETSER-I

CS-407 DISCRETE MATHEMATICAL STRUCTURE Credit: 04

Course Outcome: Upon completion of this course Students will acquire the knowledge to write an argument

using logical notation and determine if the argument is or is not valid. Demonstrate the ability to

write and evaluate a proof or outline the basic structure of and give examples of each proof

technique described. Understand the basic principles of sets and operations in sets. Prove basic

set equalities. Demonstrate the ability to solve problems using counting techniques and

combinations. Demonstrate an understanding of relations and functions and be able to determine

their properties. Determine whether a function is one-to-one and "onto". Demonstrate different

traversal methods for trees and graphs. Develop problems in Computer Science using graphs and

trees. Demonstrate abstraction, notations & critical thinking related to CSE.

Unit I

Sets, combination of sets, finite and infinite sets, uncountable sets, cardinality, Ordered pairs and

Cartesian product, Computer representation of sets, Fuzzy sets, Relations, Composition of

relations, function as a relation, injection, surjection, bijection, composition of function, inverse

of function, Characteristic functions, Mathematical Induction .

Unit II

Graph Theory: Directed and undirected graphs, basic terminology, paths and circuits, Biprite

graph, Eulerian and Hamiltonian graph, Trees; definition and properties, rooted trees, binary

trees, spanning trees, minimal spanning trees, Shortest path problems.

Unit III

Matrices and Combinatorics: Matrices and its types, Transpose of a Matrix, Boolean Matrix,

Determinants, Determinants of a Matrix, Elementary Transformations, Solution of linear

equations by Matrix methods, Rank of a Matrix, Eigen values and Eigen vectors. Basics of

Counting, Pigeonhole Principle, Permutation and Combination.

Unit IV

Mathematical logic and Lattices: Propositions statements, compound propositions, proposition

and Truth tables, logical equivalence, Bi-conditional statements, Negation of Compound

statements, tautologies and Contradictions, Boolean algebra, Logic gates, Normal forms, Lattice,

Lattice as Algebraic system, sub lattices, Finite Boolean algebra.

Recommended Books:

1. C.L lieu, "elements of Discrete mathematics", Me Graw Hill international Student edition.

2. Mott: “Discrete Mathematics” Rosen, ”Discrete Mathematics and its Applications”

Syllabus CS

13

SEMETSER-I

CS-409 OPERATING SYSTEM Credit: 04

Course Outcomes:

After the course, the students are expected to be able to understand the basics of

operating systems like history, types, and views of operating systems. Can describe the various

CPU scheduling algorithms with their usage and synchronization concepts. Explain various

memory management techniques and concepts of thrashing. Able to apply various page

replacement policies for dynamic memory management. Understand the concepts of a File

system, Input/output systems, and system protection of various operating systems and various

related algorithms. Use disk management and disk scheduling algorithms for better utilization of

external memory and also able to understand the concepts of deadlock, its avoidance, prevention,

and various related algorithms.

Unit I

Introduction: What is an Operating System, History of Operating Systems, Type of Operating

System. Different views of Operating System, Operating System concepts and structures.

Processes: The process concept, systems programmer's views of processes. The operating system

view of processes, Operating system services for process management, Scheduling algorithms,

performance evaluation.

Inter process Communication and Synchronization: The need for inter process synchronization,

mutual exclusion, Semaphores, classical problems in concurrent programming, critical region,

monitors, and messages.

Unit II

Memory Management: Memory management without swapping or paging Swapping, virtual

memory, page replacement algorithms, modeling paging algorithms, design issues for paging

systems, segmentation.

File Systems: File systems, directories, file system implementation, security protection

mechanisms.

Unit III

Input/output: Principles of I/O Hardware: I/O devices, devices controllers, Direct Memory

Access (DMA), Principles of I/O software, User space I/O software.

Disks: Disk hardware, Disk Arm scheduling algorithms, error handling, Track at time caching

RAM Disks.

Clocks: Clock hardware, clock software.

Unit IV

Dead Locks: Resources, Dead locks, The Ostrich Algorithm, Deadlock Detection and Recovery,

Deadlock Avoidance, Deadlock Prevention.

Terminals: Terminals hardware, memory mapped terminals, I/O software.

Syllabus CS

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Recommended Books:

1. Andrew S. Tanenbaum "Modem Operating Systems, Prentice Hall of India Pvt. Ltd.l995.

2. Abraham Silberschatz and Galvin P. B., Operating System Concepts". Addition Wesley 1989.

3. Ri. Milan Milenkovic "Operating Systems-Concepts and Design”, McGraw Hill International Edition-

Computer Sciences series 1992.

4. R2. Harvey M.Deital, "An introduction to operating Systems", Addison Wesley 1994.

Syllabus CS

15

Semester-2ND

Paper

No Subject Title of the Paper Credit

Max. Marks

Internal Univ. Exam Total

CS-402 Core Theory of Computation 4 20 80 100

CS-404 Core Advanced Data Structures 4 20 80 100

CS-406 Core Distributed Database Systems 4 20 80 100

CS-408 Core Object Oriented Software Engineering 4 20 80 100

CS-410

Elective-I

Digital Image Processing &

Multimedia

OR Optimization Techniques

4

20

80

100

CS-412 Practical Programming Lab-III(Advanced Data Structure)

4

100

CS-414 Practical Programming Lab-IV (Distributed Database Systems)

4

100

Total 28 700

Syllabus CS

16

SEMETSER-II

CS-402 THEORY OF COMPUTATION Credit: 04

Course Outcome:

Upon successful completion of this course, students will be able to discuss key notions of

computation such as algorithm, computability, decidability, reducibility, and complexity through

problem solving. The students will be capable of explaining the models of computation including

formal languages, grammars and automata, and their connections. Also they will be able to state

and explain the Church-Turing thesis and its significance. They will also analyze and design

finite automata, pushdown automata, Turing machines, formal languages, and grammars. At last

they will be able to solve computational problems regarding their computability and complexity

and prove the basic results of the theory of computation.

Unit I

Fundamentals of automata theory, Strings, Alphabet, Language, Operations, Finite state

machine, minimisation of FSM, Moore and Mealy machines. Finite automaton model, DFA and

NFA, NFA to DFA conversion, transition diagrams, Language recognizers.

Unit II

Regular Languages & Grammars: Regular sets, regular expressions, identity rules, Constructing

finite Automata for a given regular expressions, Conversion of Finite Automata to Regular

expressions. Pumping lemma for regular sets, closure properties of regular sets. right linear and

left linear grammars, equivalence between regular linear grammar and FA, inter conversion.

Unit III Context free grammar, derivation trees & derivation of strings. Ambiguity in CFGs.

Minimization of CFG. Chomsky normal form, Pumping Lemma for CFLs. Push Down Automata

(PDA) : definition, model, acceptance of CFL, Acceptance by final state and acceptance by

empty state and their equivalence. Equivalence of CFL and PDA.

Unit IV Turing Machine: definition, model, Representation of TMs, Types of TMs , Language

acceptability by TMs, design of TM, Computable functions, recursively enumerable languages,

Universal TMs, Halting problem, NP-Completeness.

Recommended Books:

1. Hopcroft H.E. and Ullman J. D.Pearson Education, Introduction to Automata Theory Languages and

Computation, Pearson Education India.

2. K.L.P Mishra and N.Chandra Sekaran ,Theory of computer Science, PHI (2001)

3. Lewis H.P. & Papadimition C.H. Pearson, Elements of Theory of Computation, PHI.

Syllabus CS

17

SEMETSER-II

CS- 404 ADVANCED DATA STRUCTURES Credit: 04

Course Outcome: The student will understand basic concepts of data structures and algorithms such as

various searching and sorting techniques, concepts about stacks, queues, link-lists, trees and

graphs. They will able to summarize searching and sorting techniques. They will get knowledge

concepts graphs and various traversing algorithms. Also the various algorithms that are used for

hashing and how it is used in file system.

Unit-I:

Dictionaries, linear list representation, Skip list representation insertion, deletion and searching,

Hash table representation, Hash functions, Collision resolution – separate chaining Open

addressing – linear probing, quadratic probing, Double hashing, Rehashing, extendible hashing,

Comparison of hashing and skip list

Unit-II:

Priority queue operations, Double-ended priority queues, Binary search tree implementation,

Binary search tree operations – searching, Binary search tree insertion and deletion, AVL trees

operations – insertion, AVL tree deletion and searching

Unit-III:

B-tree of order m, insertion, B-tree deletion, searching, Height of a B-tree, Binary heaps, Heap

operations, specifications, Implementation and applications, Advanced heap structures, Red-

Black tree, Splay tree

Unit-IV:

Graph algorithms: Disjoint sets – Union by rank, Path compression

Graphs-topological sort, Shortest path algorithms, Minimum spanning tree, Applications of DFS.

Pattern matching algorithms – Brute force, Boyer-Moore algorithm, Knuth-Morris-Pratt

algorithm, Tries – standard tries, compressed tries

Recommended Books:

1. Mark Allen Weiss, “Data Structure and Algorithm Analysis in C”, 2nd

Edition, Pearson Education.

2. Peter Brass, “Advanced Data Structures”, Cambridge University Press.

3. Anny V. Levitin, “Introduction to the Design and Analysis of Algorithm”, 2nd

Edition, Pearson

Education

4. T.H. Cormen, C.E. Leiserson, R. L. Rivest and L.Stein, “Introduction to Algorithm”, 3rd

Edition, PHI

5. Samir Kumar Bandyopadhyay, “Data Structure using C”, 1st Edition, Pearson Education

6. E. Horowitz, S. Sahani, S.Rajsekharan, “Fundamentals of Computer Algorithm”, 2nd

Edition,

Universities Press

7. Richard F. Gilberg, Behrouz A. Forouzan, “ Data structures: A Pseudo-code Approach with C”, 2nd

Edition, Cengage Learning

8. Adam Drozdek, “Data Structures and Algorithms in C++” 3rd

Edition, Thomson

Syllabus CS

18

SEMETSER-II

CS-406 DISTRIBUTED DATABASE SYSTEMS Credit: 04

Course Outcome:

After completion of this course, the students will understand distributed database

systems architecture and design. Be able to apply methods and techniques for distributed query

processing and optimization. Understand the broad concepts of distributed transaction process.

Understand the basic concepts of Data warehousing and OLAP technology.

Unit I

Features of Distributed versus Centralized Databases – Why Distributed Databases – Distributed

Database Management Systems (DDBMSs)- Review of Databases – Review of Computer

Networks-Levels of Distribution Transparency- Reference Architecture for Distributed

Databases – Types of Data Fragmentation, Equivalence Transformations for Queries –

Transforming Global Queries into Fragment Queries – Distributed Grouping and Aggregate

Function Evaluation – Parametric Queries -Optimization of Access Strategies - A Framework for

Query Optimization – Join Queries – General Queries.

Unit II

A Framework for Transaction Management – Supporting Atomicity of Distributed Transactions

– Concurrency Control for Distributed Transactions – Architectural Aspects of Distributed

Transactions

Unit III

Foundations of Distributed Concurrency Control – Distributed Deadlocks – Concurrency Control

Based on Timestamps – Optimistic Methods for Distributed Concurrency Control - Reliability –

Basic Concepts Non-blocking Commitment Protocols – Reliability and Concurrency Control –

Determining a Consistent View of the Network – Detection and Resolution of Inconsistency –

Checkpoints and Cold Restart

Unit IV

Parallel Database Systems – Database Server Approach – Database Servers and Distributed

Databases – Parallel System Architectures – Objectives – Functional Aspects – Parallel Data

Processing – Parallel Query Optimization – Data Placement – Query Parallelism – Parallel

Execution Problems – Initialization – Interferences and Convoy Effect – Load Balancing

Recommended Books:

1. Stefano Ceri, Giuseppe Pelagatti, Distributed Databases Principles & Systems, McGraw-Hill.

2. M.Tamer Ozsu, Patrick Valduriez, Distributed database systems, 2nd Edition, PHI

Syllabus CS

19

SEMETSER-II

CS-408 OBJECT ORIENTED SOFTWARE ENGINEERING Credit: 04

Course Outcome: At the end of this course, each student should be able to understand the basics of software

engineering methods and practices in their appropriate applications and be able to distinguish the

various software process models such as waterfall model, spiral model, evolutionary models, etc.

Students can able to understand how to gather, analyze and specify requirements by

understanding the software requirements. They can develop architectural diagram, and

implement by following coding principles. Apply testing strategies and handle software product

maintenance issues. Also able to learn and understand various O-O concepts along with their

applicability contexts. They learn how to develop design solutions for problems on various O-O

concepts. They also learn various modeling techniques to model different perspectives of object-

oriented software design (UML), Understand the components of Unified Modeling Language,

Understand techniques and diagrams related to structural modeling, Understand techniques and

diagrams related to behavioral modeling, and Understand techniques of Object-Oriented

analysis, design, and testing.

Unit I Software Engineering - Definition, Principles of SE, Generic View of SE, Characteristics of

Software, Mc Call’s Quality Factors, SDLC, Classical, Waterfall Model, Spiral Model,

prototyping approach, 4GL approach.

Unit II

Feasibility study, Fact finding techniques, user transaction and design requirements, system

requirement specifications, software requirement and analysis, decision trees, decision tables,

DFD, Data dictionary, Input output design, structured chart, modules specification,

implementation, testing, maintenance.

Unit III Object orientated concepts, class, object, Polymorphism, Inheritance. Object oriented system

development - function /data methods, object oriented - analysis, construction, testing.

Identifying the elements of an object model- classes and objects, indicating attributes and

operations. Introduction to UML, uses of UML, phases of system development, Overview of

UML- views, diagrams, Model elements, Modeling.

Unit IV

Basic structure modeling - Classes, Objects and their relationships, Relationships between

classes - associations, Generalization, aggregation, dependency and abstraction. UML

Extensions - Stereo type, Constraints. Use case diagram , Class diagram ,Object diagram,. State

diagram,. Sequence diagram, Collaboration Diagram, Activity diagram, Component diagram,

Deployment diagram.

Syllabus CS

20

Recommended Books:

1. Timothy C. Lethbridge and Robert Laganiere, “Object-Oriented Software Engineering: Practical

software development using UML and Java”, McGraw-Hill Higher education.

2. Roger S. Pressman, "Software Engineering A practitioner’s Approach", 5th Edition, McGraw-Hill

Higher Education.

3. Stephen R Schach, “An Introduction to Object Oriented Systems Analysis and Design with UML and

the Unified Process”, Tata McGraw-Hill

4. Grady Booch , James Raumbaugh and Ivar Jacoboson, “The Unified Modeling Language User Guide”,

2nd

Edition, Addison Wesley

5. Mall Rajib, "Fundamentals of Software Engineering", PHI.

Syllabus CS

21

SEMETSER-II (Elective- I)

CS- 410 DIGITAL IMAGES PROCESSING AND MULTIMEDIA Credit: 04

Course Outcome:

The objective is to describe and explain students’ basic principles of digital image

processing. They will familiarize with concept of image processing and basic analytical methods

to be used in image processing. The aim is to let them understand the need for image

transformations, different types of image transforms and their properties. Moreover introduce the

concepts image enhancement and restoration techniques. The students will understand the

need for image compression and learn the spatial and frequency domain techniques of

image compression also different feature extraction techniques for image analysis and

recognition.

Unit-I

Digital Image fundamentals and transforms: Digital Image fundamentals, Image digitization,

Elements of visual perception, Sampling, quantization, Image resolution, Colour perception and

processing.

Image processing: pixel based transformation, Geometric transformation, Basic relationship

between pixels, Basic geometric transformation, Fourier transform, DFT transform, Properties

of 2D Fourier transform, DCT transform, Haar transform

Unit-II

Image enhancement techniques: Spatial Domain methods, Basic grey level transformation,

Histogram equalization, Image subtraction, Image averaging,

Spatial filtering: Smoothing, Sharpening filters, Laplacian filters, Frequency domain filtering:

Smoothing, Sharpening filters

Unit-III

Image restoration: Model of image degradation/restoration process, Noise models, Inverse

filtering, Least Mean Square filtering, Constrained Least Mean Square filtering, Blind image

restoration, Pseudo inverse, Singular Value decomposition

Unit-IV

Image compression and segmentation: Lossless compression, Variable length coding: LZW

coding, Bit plane coding, Predictive coding, DPCM, Lossy compression: Transform coding,

Wavelet coding.

Basics of Image compression standards: JPEG, MPEG, Basics of vector quantization.

Image segmentation and representation: Edge detection, Thresholding, Region based

segmentation, Boundary representation

Syllabus CS

22

Recommended Books:

1. Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Pearson Education.

2. Rafael C. Gonzalez, Richard E. Woods and Steven, Digital Image Processing using MATLAB,

Pearson Education.

3. Anil K Jain, Digital Image Processing, PHI.

Syllabus CS

23

SECOND YEAR

Semester-3RD

Paper

No Subject Title of the Paper Credit

Max. Marks

Internal Univ. Exam Total

CS-501 Core Numerical Computing 4 20 80 100

CS-503 Core Advanced Computer Networks 4 20 80 100

CS-505 Core Systems Programming & Compiler Design

4 20 80 100

CS-507 Core Concept of Core & Advanced JAVA 4 20 80 100

CS-509 Elective-II Bioinformatics

OR Data Mining & Warehousing

4 20 80 100

CS-511 Practical Programming Laboratory- V (Computer Networks)

4 100 100

CS-513 Practical Programming Laboratory- VI (Based on JAVA)

4 100 100

Total 28 700

Syllabus CS

24

SEMETSER-III

CS-501 NUMERICAL COMPUTING Credit: 04

Course Outcome: On completion of this course is the students will be able to understand how numerical

methods can be used to obtain approximate solutions to mathematical problems. The course

deals with various topics like finding roots of equations, solving linear algebraic equations,

interpolation analysis, numerical integration & differentiation, solution of differential equation,

solution of matrix problems. Moreover they will learn finding the numerical solutions for Eigen

values and Eigen vectors for square matrices.

Unit I

Number system and Errors, Floating point Representation, Approximation of numbers, Existence

and Uniqueness of interpolating polynomial, Lagrange’s Interpolating Formula; Error in

Interpolation, Interpolation points for minimizing the error bound, Newton’s Divided Difference

Interpolating polynomial, Properties of Divided Difference, Forward Difference Operator.

Newton’s Forward Difference Interpolating formula, Backward Difference Operator Newton’s

Backward Difference Interpolation formula,

Unit-II

Numerical Solution of non-linear equation: Introduction, Method of bisection, Secant Method,

Regular false Method, Newton-Raphson Method, Fixed point of a function, Fixed point iteration

method

Unit-III

Numerical Integration: Introduction, some simple quadrate Rules, Newton-Cotes, Rules,

Compound quadrate Rules, Gauss legendre-2&3 point

Unit-IV

Numerical solution of differential equation: Introduction, Euler’s Method, Determination of

Eigen value and vectors of matrix by iteration, invers of matrix

Recommended Books:

1. A course of Numerical Analysis by B.P Acharya and R.N das, publishers: kalyani Publishers

2. Elementary Numerical Analysis by K.A Tkrison

3. Numerical analysis by S.S Sastry.

4. Introductory Numerical analysis by Dutta & Jain, Sreedhar Prakshani

Syllabus CS

25

SEMETSER-III

MCS-503 ADVANCED COMPUTER NETWORK Credit: 04

Course Outcome:

After completing this course, students will be able to understand computer network

basics, network architecture, TCP/IP, and OSI reference models. Identify and understand various

techniques and modes of transmission. Describe data link protocols, multi-channel access

protocols, and IEEE 802 standards for LAN also able to describe routing and congestion in

network layer with routing algorithms and classify IPV4 addressing scheme. Students can also

Discuss the elements and protocols of the transport layer and finally able to understand network

security and various protocols such as FTP, HTTP, Telnet, DNS

Unit I Introduction: Data Communication, Network Protocols and Standards, Point to Point and Multi Point line configuration, Network Topologies: Mess, Star, Tree, Bus, Ring Transmission Modes: Simplex, Half Duplex, Networks: LAN, MAN, WAN. The OSI Models: Function of Layers. TCP/ IP Protocol Suit

Signals: Analog and Digital signals, Periodic and Aperiodic signal,

Encoding and Modulating: Digital to Digital conversion, Unipolar, Polar Bipolar, Analog to Digital conversion AM, FM, PM

Unit II Transmission of Digital data: Parallel and Serial transmission. DTE/DCE interface, Modems, Guided and Unguided transmission media. Transmission impairment, Performance.

Multiplexing: Frequency division, Wave division and Time division multiplexing, the Telephone

system, Digital Subscriber Line (DSL), Error Detection and Correction: Types of Error,

Redundancy Checks (VRC, LRC, CRC), Error Correction.

Data Link Control: Line Discipline, Flow Control, Error Control.

Data Link Protocol: Asynchronous and Synchronous Protocols, Character and Bit Oriented

Protocols.

Unit III

Local Area Networks: IEEE 802 standards, Ethernet, Token Bus, Token Ring, FDDl

Switching: Circuit Switching, Packet Switching, Message Switching

Integrated Services Digital Network (ISDN), Services, History, Subscribers access to ISDN, The ISDN layers, Broadband ISDN

X.25: X.25 Layers, Protocols related to X.25

Unit IV Frame Relay: Introduction, Frame Relay operation. Frame Relay layers, Congestion Control, Leaky bucket algorithm, Traffic Control.

Networking and Internetworking Devices: Repeaters, Bridges, Routers, Gateways, Routing

Algorithms. TCP/IP Protocol Suite: Overview, Network Layer, Addressing Subneting, Transport Layer,

Application Layer: Client Server Model, BOOTP, DHCP, DNS, Telnet, FTP, SMTP, SNMP, HTTP, WWW.

Syllabus CS

26

Recommended Books: 1. Behrouz A Forouzen “Data Communications and Networking “Tata McGraw Hill. “

2. Stalling W “Computer Communication Networks “ Prentice Hall.

3. Tannenbaum A.S “Computer Networks” PHI

4. Bartee T.C “Data Communication,Network and systems”BPB

5. Schweber WL”Data Communication “Mc Graw Hill.

6. Steven W.R: TCP/IP Illustrated ,Vol 1 ,The protocols” Addition Wesley

Syllabus CS

27

SEMETSER-III

CS-505 SYSTEMS PROGRAMMING AND COMPILER DESIGN Credit: 04

Course Outcome: After completion of this course all students will be able to define the phases of a typical

compiler, including the front- and backend. Identify tokens of a typical high-level programming

language; define regular expressions for tokens and design; implement a lexical analyzer using a

typical scanner generator. Explain the role of a parser in a compiler and relate the yield of a parse

tree to a grammar derivation; design and implement a parser using a typical parser generator.

Apply an algorithm for a top-down or a bottom-up parser construction; construct a parser for a

small context-free grammar. Explain the role of a semantic analyzer and type checking; create a

syntax-directed definition and an annotated parse tree; describe the purpose of a syntax tree.

Explain the role of different types of runtime environments and memory organization for

implementation of typical programming languages. Describe the purpose of translating to

intermediate code in the compilation process. Design and implement an intermediate code

generator based on given code patterns.

Unit I

Introduction to System Software, Hierarchy, System Programming, Machine structure,

Interfaces, Address Space, Computer languages, Life Cycles of a source programs, System

software development, levels of system software, Assemblers and Introduction to Assembly

Programming: Simple Arithmetic Calculation - Subroutine and Parameter Passing.

Unit II Introduction to Compiling and Lexical Analysis: Compilers, Analysis of the source program, the

phases of a compiler, Cousins of the compiler, the grouping of phases, Compiler construction

tools. Lexical Analysis -The role of the lexical analyzer, Input buffering, Specification of tokens,

Recognition of tokens, A language for specifying lexical analyzers, Design of a lexical analyzer

generator.

Unit III Syntax Analysis: The role of the parser, Context-free grammar, writing a grammar, Top- down

parsing, Bottom-up parsing, Operator-precedence parsing, LR parsers, Parser generators. Syntax-

Directed Translation: Syntax-directed definitions, Construction of syntax trees, Bottom up

evaluation of S-attributed definitions, L-attributed definitions, Top-down translations, Bottom up

evaluation of inherited attributes.

Unit IV Run-Time Environments: Source language issues, Storage organization, Storage allocation

strategies, Access to nonlocal names, Parameter passing, Symbol tables, Language facilities for

dynamic storage allocation, Code Generation: Issues in the design of a code generator, The target

machine, Runtime storage management, Basic blocks and flow graphs, Next- use information, A

simple code generator, Register allocation and assignment, The Dag representation of basic

blocks.

Syllabus CS

28

Recommended Books:

1. John J. Donovan “System Programming , Tata Mc Graw- Hill.

2. Alfred V. Aho, Ravi Sethi, Jeffrey D. Ullman, “Compilers - Principles, Techniques and Tools”,

Addison Wesley

3. Dhamdhare D., “System Programming and Operating System , Tata Mc Graw-Hill.

Syllabus CS

29

SEMETSER-III

CS – 507 CONCEPTS OF CORE AND ADVANCED JAVA Credit: 04

Course Outcome:

On successful completion of this course, the student will able to understand the basic

principles of the object-oriented programming. They will able to handle interfaces, class

hierarchies and exceptions in programs. Comprehend an introductory understanding of

multithreaded programming, graphical user interfaces and event-driven programming. Students

will be able to connect a JAVA program to a DBMS and perform insert, update and delete

operations on DBMS table.

Unit I

Introduction to Java: Java Architecture and Features, Understanding the semantic and syntax

differences between C++ and Java, Compiling and Executing a Java Program, Variables,

Constants, Keywords, Data Types, Operators (Arithmetic, Logical and Bitwise) and Expressions,

Comments, Decision Making Constructs and Nesting, Java Methods (Defining, Scope, Passing

and Returning Arguments), Type Conversion and Type and Checking, Built-in Java Class

Methods

Unit II

Arrays, Inheritance: Creating & Using Arrays (One Dimension, Multi-dimensional),

Referencing Arrays Dynamically,

Java Strings: The Java String class, Creating & Using String Objects, Manipulating Strings,

String Immutability & Equality, Passing Strings To & From Methods, String Buffer Classes,

Simple I/O using System.out and the Scanner class , Byte and Character streams,

Reading/Writing from console and files

Unit III

Inheritance: (Single Level and Multilevel), Method Overriding, Dynamic Method Dispatch,

Abstract Classes, Interface and Packages, Extending interfaces and packages, Package and Class

Visibility, Using Standard Java Packages (util, lang, io, net), Wrapper Classes

Exception Handling, Threading, Networking and Database Connectivity using JDBC, Multi-

threading the Thread class and Runnable interface, creating single and multiple threads, thread

prioritization , Synchronization and communication, suspending/resuming threads

Unit IV

Applet Event Handling: Java Applets: Introduction to Applets, Writing Java Applets, Working

with Graphics, Incorporating Images & Sounds, Event Handling Mechanisms, Listener

Interfaces, Adapter and Inner Classes, Design and Implementation of GUIs using the AWT

controls

Swing components of Java Foundation Classes such as labels, buttons, text fields, layout

managers, menus, events and listeners, Graphic objects for drawing figures such as lines,

rectangles, ovals, using different fonts.

Syllabus CS

30

Recommended Books:

1. Paul Deitel, Harvey Deitel, "Java: How to Program", 10th Edition, Prentice Hall, 2011.

2. Complete Reference: Java, Herbet Schildt & Naughton, Tata McGraw, 5Th Edition, 2006.

3. Java Unleashed, Jane Jawoske, SAM5, Tech Media 2006.

Syllabus CS

31

SEMETSER-III

CS-509 DATA MINING & SOFT COMPUTING Credit: 04

Course Outcome:

Upon successful completion of this course, students should be able to interpret the

contribution of data mining to the decision-support level of organizations. Categorize and

carefully differentiate between situations for applying different data-mining techniques: frequent

pattern mining, association, correlation, classification, prediction, cluster, and outlier analysis.

Design and implement systems for data mining. Evaluate the performance of different data-

mining algorithms. Also they will be able to propose data-mining solutions for different

applications. Also the students will comprehend the fuzzy logic and the concept of fuzziness

involved in various systems and fuzzy set theory. Also will able to acquire the fundamental

theory and concepts of neural networks. Identify different neural network architectures,

algorithms, applications and their limitations. Understand appropriate learning rules for each of

the architectures and learn several neural network paradigms and its applications. Also will able

to explain the principles underlying evolutionary computation in general and Genetic Algorithms

in particular. Apply evolutionary computation methods to find solutions to complex

problems. At last they reveal different applications of these models to solve engineering and

other problems

Unit I

Knowledge discovery in Databases, Data Mining Processes, Data Mining Software WEKA,

KEEL, Introduction to Association Rule Mining, Apriori Algorithms, Introduction to

Classification, classification algorithms- Decision Trees, Bayesian classifier, K-nearest neighbor

classifier, Neural network based classifier. Introduction to Clustering, Types of Clustering,

Clustering Algorithms.

Unit II

Supervised Neural Networks: Basic concepts of Artificial Neural Networks, Learning Schemes,

Multi-layer feed-forward neural networks, Back Propagation Algorithm, Effect of tuning

parameters of the back propagation neural network. Selection of various parameters in BPN,

Variations of standard back propagation algorithm. Recurrent Neural Networks, Functional Link

Neural Nets, Radial Basis Function Neural Nets, Hopfield Nets.

Unsupervised Neural Networks: Adaptive Resonance Theory: Introduction, ART1, ART2,

Kohonen Neural Network: Self-Organizing Feature Map, Learning Vector Quantization.

Unit III

Fuzzy Theory: Fuzzy Set Theory - Fuzzy Vs Crisp - Crisp & Fuzzy Sets, Crisp & Fuzzy

Relations, Fuzzy Systems -Crisp Logic, Predicate Logic, Fuzzy Logic, Fuzzy Rule Based

System, Defuzzification Methods.

Unit IV

Genetic Algorithms: Basic Concepts, Creation of Offspring’s, Working Principle, Encoding,

Fitness Function, Reproduction. Genetic Modeling, Inheritance Operators, Cross Over, Inversion

& Deletion, Mutation Operator. Bit-wise Operators, Bit-wise operators in GA, Generational

Cycle, Convergence of GA, Applications.

Syllabus CS

32

Recommended Books:

1. J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, 3rd Edition, Morgan

Kaufmann Series.

2. S. Rajasekaran, and G. A. Vijayalakshmi Pai, Neural Networks, Fuzzy Logic, & Genetic Algorithms

Synthesis & Applications, PHI.

3. J.-S. R. Jang, C.-T. Sun, E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational Approach

to Learning and Machine Intelligence, PHI, 2004.

4. Simon Haykin, Neural Networks A Comprehensive Foundation , Pearson Education.

5. H.J.Zimmermann, Fuzzy Set Theory and its Applications, Allide publishers Ltd., Kluwer Academic

Publishers.

6. B. Yegnanarayana, Artificial Neural Networks, PHI.

7. A.P.Engelbrecht, Computational Intelligence An Introduction, Joh Wiley & Sons Ltd.

Syllabus CS

33

Semester-4

Paper

No Subject Title of the Paper Credit

Max. Marks

Internal Univ. Exam Total

CS-502 Core Design and Analysis of Algorithms 4 20 80 100

CS-504 Elective-

III

Software Project

Management

OR

Computational Intelligence

OR

Pattern Recognition

4 20 80 100

CS-506 Dissertation & Viva Voce 8 200

Total 16 400

Syllabus CS

34

SEMETSER-IV

CS-502 DESIGNS AND ANALYSIS OF ALGORITHM Credit: 04

Course Outcome: Upon completion of this course the students will argue the correctness of algorithms

using inductive proofs and invariants. Analyze worst-case running times of algorithms using

asymptotic analysis. Describe the divide-and-conquer paradigm and explain when an algorithmic

design situation calls for it. Synthesize divide-and-conquer algorithms. Derive and solve

recurrences describing the performance of divide-and-conquer algorithms. Describe the

dynamic-programming paradigm and explain when an algorithmic design situation calls for it.

Synthesize dynamic-programming algorithms, and analyze them. Describe the greedy paradigm

and explain when an algorithmic design situation calls for it. Synthesize greedy algorithms, and

analyze them. Explain the major graph algorithms and their analyses. Explain the different ways

to analyze randomized algorithms (expected running time, probability of error). Explain the

difference between a randomized algorithm and an algorithm with probabilistic inputs. Employ

indicator random variables and linearity of expectation to perform the analyses. Explain what

amortized running time is and what it is good for. Describe the different methods of amortized

analysis (aggregate analysis, accounting, and potential method.

Unit I Introduction: Introduction to Design and Analysis of Algorithm, Growth of Functions,

Recurrences. Sorting and Selection: Insertion sort, Heapsort, Quicksort, Sorting in Linear Time,

Selection.

Unit II Algorithm Design & Analysis Techniques (I): Divide and Conquer & Randomization (Examples:

Quick Sort, Miller-Robin Primality Test). Data Structure: Binomial Heaps, Fibonnaci Heaps.

Unit III Algorithm Design & Analysis Techniques (II): Dynamic Programming (Examples-Traveling

Salesperson Problem, Longest common subsequence), Greedy Method (Example: Activity-

Selection Problem, Fractional knapsack problem, Huffman codes), Backtracking (Examples: 8-

Queens Problem & Subset sum Problem).

Unit IV Graph Algorithms: Data Structure for Disjoint Sets, Minimal Spanning Tree (Algorithms

Kruskal & Prim), Single Source Shortest Paths (Dijkstra’s Algorithm), All Pairs of Shortest

Paths (Floyd- Warshall Algorithm), Topological Sort, String Matching Algorithms, NP-

Completeness and Introduction to Approximation Algorithms.

Syllabus CS

35

Recommended Books:

1. T. H. Cormen, C. E. Leiserson & R. L. Rivest, Introduction to Algorithms, PHI, 3rd Edition.

2. E. Horwitz, S. Sahani, S. Rajasekharn, Fundamentals of Computer Algorithms, Galgotia Publication,

2000.

3. Alfred V. Aho, John E. Hopcroft, and Jeffrey D. Ullman, The Design and Analysis of Computer

Algorithms, Addison Wesley Longmans, 1998.

4. G. Brassard, P. Bratley, Fundamentals of Algorithmic, PHI, 1998.

Syllabus CS

36

SEMETSER-IV

CS-504 SOFTWARE PROJECT MANAGEMENT (Elective-iii) Credit: 04

Course Outcome:

After completing this course, students will be able to identify the impact of IT projects on

the performance of the organizations, they understand, manage and develop IT infrastructure in

different projects and will know the skills that are required to ensure successful medium and

large scale software projects. They also learn to select and apply project management techniques

for process modeling, planning, estimation, risk management, able to develop strategies to

calculate risk factors involved in IT projects. Learn to use project management software to

control the design, implementation, closure, and evaluation of IT projects. They can estimate,

plan, calculate and adjust project variables and are able to apply project management practices to

launch new programs, initiatives, products, services, and events relative to the needs of

stakeholders.

Unit I

Introduction to Software Project Management: Overview of the project, project management,

Project management process, Activities of project management, setting objectives, plans,

methods and methodologies, setting objectives, project success and failures

SW Project life cycle: Concept, analysis, planning, execution and closing stage, The ISO 12207

Software development life cycle, Project selection methodologies and technologies, process

models, selection of appropriate process model.

SW Project evaluation & Planning: Tools and techniques, funds flow analysis, cost-benefit

analysis, risk evaluation, project portfolio management, benefit= management, Gathering

requirements, Identification of project scope, step-wise project planning, case study.

Unit II

Software project estimation: Software effort estimation techniques, cost estimation, effect of

schedule compression, Capers Jone's estimation.

Design of software project management system: Activity planning, Work breakdown structures,

product breakdown structure, resource break-down structure, project scheduling, activity on an

arrow, activity on a node, dummy activities, Use of Gantt chart, formulating a network (CPM),

activity float, and critical activity.

Risk management: Risk identification, assessment, planning, and management, evaluating risks

to schedule, application of PERT.

Unit-III

Project Cost Analysis: Resource Allocation, schedule resources, crashing and resource sharing,

network scheduling with Limited Resources, capacity planning, and capacity expansion decision

Software project monitoring and control: Design of monitoring system, prioritizing monitoring,

Progress control, performance control, schedule control, cost control tools used in controlling the

project, earned value analysis, change control, status review meeting, project audit, and reviews.

Syllabus CS

37

Unit IV

Managing contracts: Types of contracts, contract placements, contract management

Software Project organizations & Managing people in software environment: Functional, matrix

and projectized organization, various team structures, Organization behavior, coordination and

procedures, project management and procedure, working in teams, skills and competency of the

manager.

Scope and software quality control: Importance of software quality, SQC, SQA, product process

and quality, cost of quality, ISO 9126, Process capability models, quality management system,

software testing, and reliability.

Recommended Books:

1. Bob Hughes, Mike Cotterell, Rajib Mall, Software Project Management, McGraw-HILL, 2011, 5th

Edition

2. R. Walker, Software Project Management, Pearson, 2003.

3. Robert K. Wysocki, Efective Software Project Management, Wiley India, Edition, 2008