Syllabus of GATE for Computer Science and Information Technology

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 nonlinear

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 datapath,

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.