5.3.
10 COMPUTER ENGINEERING AND INFORMATION TECHNOLOGY (CO)
ENGINEERING MATHEMATICS
Linear Algebra: Matrix algebra, Systems of linear equations, Eigen values and
eigenvectors.
o
Calculus: Functions of single variable, Limit, continuity and differentiability, Mean
value theorems, Evaluation of definite and improper integrals, Partial derivatives,
o
Total derivative, Maxima and minima, Gradient, Divergence and Curl, Vector
identities, Directional derivatives, Line, Surface and Volume integrals, Stokes,
Gauss and Green’s theorems.
Differential equations: First order equations (linear and nonlinear), Higher order
linear differential
o
equations with constant coefficients, Cauchy’s and Euler’s equations, Initial and
boundary value problems, Laplace transforms, Solutions of one dimensional heat
and wave equations and Laplace equation.
Complex variables: Analytic functions, Cauchy’s integral theorem, Taylor and
Laurent series.
o
Probability and Statistics: Definitions of probability and sampling theorems,
Conditional probability,
o
Mean, median, mode and standard deviation, Random variables, Poisson, Normal
and Binomial
distributions. Numerical Methods: Numerical solutions of linear and non -linear
algebraic equations
Integration by trapezoidal and Simpson’s rule, single and multi-step methods for
differential equations.
Digital Logic:
Logic functions, Minimization, Design and synthesis of combinational and sequential
circuits; Number representation and computer arithmetic (fixed and floating point).
Computer Organization and Architecture:
Machine instructions and addressing modes, ALU and data-path, CPU control
design,
Memory interface, I/O interface (Interrupt and DMA mode), Instruction pipelining,
Cache and main memory, Secondary storage.
Programming and Data Structures:
Programming in C; Functions, Recursion, Parameter passing, Scope, Binding;
Abstract data types, Arrays, Stacks, Queues, Linked Lists, Trees, Binary search
trees,
Binary heaps.
Algorithms:
Analysis, Asymptotic notation, Notions of space and time complexity, Worst and
Average case analysis; Design: Greedy approach, Dynamic programming, Divide-
And conquer; Tree and graph traversals, Connected components, Spanning trees,
Shortest
paths; Hashing, Sorting, Searching. Asymptotic analysis (best, worst, average
cases)
of time and space, upper and lower bounds, Basic concepts of complexity classes P,
NP, NP-hard, NP-complete.
Theory of Computation:
Regular languages and finite automata, Context free languages and Push-down
automata, Recursively enumerable sets and Turing machines, Undecidability.
Compiler Design:
Lexical analysis, Parsing, Syntax directed translation, Runtime environments,
Intermediate and target code generation, Basics of code optimization.
Operating System:
Processes, Threads, Inter-process communication, Concurrency, Synchronization,
Deadlock, CPU scheduling, Memory management and virtual memory, File systems,
I/O systems, Protection and security.
Databases:
ER-model, Relational model (relational algebra, tuple calculus), Database design
(integrity constraints, normal forms), Query languages (SQL), File structures
(sequential files, indexing, B and B+ trees), Transactions and concurrency control.
Information Systems and Software Engineering:
Information gathering, requirement and feasibility analysis, data flow diagrams,
process Specifications, input/output design, process life cycle, planning and
managing
the Project, design, coding, testing, implementation, maintenance.
Computer Networks:
ISO/OSI stack, LAN technologies (Ethernet, Token ring), Flow and error control
Techniques, Routing algorithms, Congestion control, TCP/UDP and sockets,
IP(v4), Application layer protocols (icmp, dns, smtp, pop, ftp, http); Basic concepts
of hubs, switches, gateways, and routers. Network security basic concepts of public
key and private key cryptography, digital signature, firewalls.
Web technologies:
HTML, XML, basic concepts of client-server computing.
