gate 2014

GATE 2014 – A Brief Analysis

1. Questions with numerical answers accounted for 40-50 % of the paper. Hence you cannot

guess your way through the paper. General Ability section also has such questions.

2. In the papers of the past, there used to be some questions which could be solved by

eliminating the wrong options. But with an increase in the “numerical answer” type

questions, this method of problem solving takes a backseat.

3. With the high occurrence of “numerical answer” type questions, one has to be thorough and

careful with unit conversions so as to type in the correct answer. Earlier, the four options

more or less served as guidelines.

4. Among general ability questions, probability accounted for around 3-4 marks with one

question each from Data Interpretation, logical reasoning and critical reasoning.

5. Engineering Mathematics questions were tough compared to the previous year. There were

no direct questions.

6. There were direct questions from few of topics. And some of questions needed concept of

two topics to solve them. Such were tough to solve. Scoring sections in IN were Networks,

Control Systems and Analog Circuits. These could be the scoring sections in the upcoming

ECE papers too.

7. The sequence of questions was different for each candidate i.e. no two candidates will have

same sequence of questions.

8. There were no “Common Data” and “Linked” questions in the papers we analyzed.

9. Some papers wrongly mentioned a penalty for a wrong answer to a “numerical type”

question. This was later corrected through an announcement by the invigilators.

According to the latest info from IIT Kharagpur, the marks of candidates appearing in EC, CS, EE, ME and

CE will be normalized across the multiple sessions. This means that whether the paper in a particular

session is easy or tough will not matter in the overall scheme of things. The following formula will be

used for the normalization.

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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.