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.
[Type text]
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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.