Notes

Syllabus for Computer
Science and Information
Technology (CS)
ENGINEERING MATHEMATICS
Mathematical Logic : Propositional Logic; First
Order Logic.
Probability: Conditional Probability; Mean,
Median, Mode and Standard Deviation; Random
Variables; Distributions; uniform, normal,
exponential, Poisson, Binomial.
Set Theory & Algebra : Sets; Relations;
Functions; Groups; Partial Orders; Lattice;
Boolean Algebra.
Combinatorics: Permutations; Combinations;
Counting; Summation; generating functions;
recurrence relations; asymptotics.
Graph Theory: Connectivity; spanning trees; Cut
vertices & edges; covering; matching;
independent sets; Colouring; Planarity;
Isomorphism.
Linear Algebra : Algebra of matrices,
determinants, systems of linear equations, Eigen
values and Eigen vectors.
Numerical Methods : LU decomposition for
systems of linear equations; numerical solutions
of non-linear algebraic equations by Secant,
Bisection and Newton-Raphson Methods;
Numerical integration by trapezoidal and
Simpson’s rules.
Calculus: Limit, Continuity & differentiability,
Mean value Theorems, Theorems of integral
calculus, evaluation of definite & improper
integrals, Partial derivatives, Total derivatives,
maxima & minima.
COMPUTER SCIENCE AND INFORMATION
TECHNOLOGY
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.