September 04, 2014

GATE 2015 Syllabus for Computer Science and Information Technology (CSE)

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GATE 2015 Syllabus of Computer Science

Syllabus for Computer Science and Information Technology (CSE) 


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 

Combinatory: 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. 


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. 

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