Banasthali University Aptitude Test  M.Tech Computer Science Overview
All about Banasthali University Aptitude Test  M.Tech Computer Science
Banasthali Vidyapith situated in Rajasthan is one of the oldest institutions of higher education.The name ‘Banasthali Vidyapith’ was adopted in 1943. The aptitude test will be common for M.Tech course in Computer Science, VLSI Design, and many more programmes. One has to fill only one form for applying to more than one M.Tech. In case of M.Tech. the preferences for the branches are to be given in the application form. Allocation of branch will be finalized at the time of counseling based on merit.
Preparation
How to prepare
EXAM SYLLABUS
(A) Logical Reasoning
(B) Mathematics
(C) Computer Fundamentals
(D) Computer Science(for CS/IT/SE)
(E) Electronics(for VLSI)
Logical Reasoning:
Analytical reasoning
Statements Assumptions
Non Verbal Tests (Visual reasoning)
Analogy Test
Inferences
Statements and assumptions
Statements Arguments
Cause and effects
Statements and conclusion
Ranking Tests
Linear arrangements
Matrix arrangements
Blood relationship test
Matrix arrangements
Symbol based problems
Sequencing, coding and decoding problem
Number series
Direction and Distance test
Mathematics
Algebra: Group, subgroups, Normal subgroups, Quotient Groups, Homomorphisms, Cyclic Groups, permutation Groups, Cayley’s Theorem, Rings, Ideals, Integral Domains, Fields, Polynomial Rings. Linear Algebra: Finite dimensional vector spaces, Linear transformations – Finite dimensional inner product spaces, selfadjoint and Normal linear operations, spectral theorem, Quadratic forms.
(ii) Analysis
Real Analysis: Sequences and series of functions, uniform convergence, power series, Fourier series, functions of several variables, maxima, minima, multiple integrals, line, surface and volume integrals, theorems of Green, Strokes and Gauss; metric spaces, completeness, Weierstrass approximation theorem, compactness. Complex Analysis: Analytic functions, conformal mappings, bilinear transformations, complex integration: Cauchy’s integral theorem and formula, Taylor and Laurent’s series, residue theorem and applications for evaluating real integrals.
(iii) Topology and Functional Analysis
Topology: Basic concepts of topology, product topology, connectedness, compactness, countability and separation axioms, Urysohn’s Lemma, Tietze extension theorem, metrization theorems, Tychonoff theorem on compactness of product spaces. Functional Analysis: Banach spaces, HahnBanach theorems, open mapping and closed graph theorems, principle of uniform boundedness; Hilbert spaces, orthonormal sets, Riesz representation theorem, selfadjoint, unitary and normal linear operators on Hilbert Spaces.
iii) Differential and integral Equations
Ordinary Differential Equations: First order ordinary differential equations, existence and uniqueness theorems, systems of linear first order ordinary differential equations, linear ordinary differential equations of higher order with constant coefficients; linear second order ordinary differential equations with variable coefficients, method of Laplace transforms for solving ordinary differential equations. Partial Differential Equations: Linear and quasilinear first order partial differential equations, method of characteristics; second order linear equations in two variables and their classification; Cauchy, Dirichlet and Neumann problems, Green’s functions; solutions of Laplace, wave and diffusion equations using Fourier series and transform methods. Calculus of Variations and Integral Equations: Variational problems with fixed boundaries; sufficient conditions for extremum, Linear integral equations of Fredholm and Volterra type, their iterative solutions, Fredholm alternative.
(v) Statistics & Linear Programming
Statistics: Testing of hypotheses: standard parametric tests based on normal, chisquare, t and F distributions.
Linear Programming: Linear programming problem and its formulation, graphical method, basic feasible solution, simplex method, bigM and two phase methods. Dual problem and duality theorems, dual simplex method. Balanced and unbalanced transportation problems, unimodular property and uv method for solving transportation problems. Hungarian method for solving assignment problems.
Computer Fundamentals
Operating System: Process Management System, CPU Scheduling, Memory management and Virtual memory, File systems, Deadlock, synchronization, Interprocess communication, I/O Systems. Disk operating System; Computer Network: ISO/OSI stack, Routing algorithms, IP addressing , internet protocol, X.25, Transmission medium, Signal encoding techniques, Application protocols, Security and cryptography; Computer Organization and Architecture: Machine instructions and addressing modes, ALU and datapath, CPU control design, Memory interface, Instruction pipelining, main memory, RISC and CISC; Automata Theory: Regular languages and finite automata , Chomsky Classification of languages, Context free grammars , Chomsky normal form, Greibach normal form, Turing machine , Recursive enumerable sets; Algorithms: Analysis, Notions of space and time complexity, Asymptotic analysis (best, worst, average cases) of time and space, array, Tree , Heap, Binary search tree ; Sorting, Searching, upper and lower bounds; Databases: Relational model(relational algebra, Relational calculus), Query languages (SQL, MSAccess), Database design, Transactions control; Software Engineering: information gathering, process life cycle; Programming: Programming in C, C++: Functions, Recursion, Parameter passing, Abstract data types, Arrays, Trees, Binary search trees, Binary heaps, File handling; Machine learning: Bayesian Learning Theory, Linear Analysis.
Computer Science(for CS/IT/SE)
i) Applied Probability And Operations Research : Random Processes, Probability Distributions,Queuing Models and Simulation, Testing of Hypothesis, Design of Experiments.
ii) Discrete Mathematical Structures : Formal Language and Automata  Graph Theory.
iii) Compiler Design : Optimization – Code Generation – Implementation – Principles of Programming Languages – Programming Paradigms.
iv) Operating Systems And System Software : Process Management, Storage Management, I/O Systems, Design and Implementation of LINUX OS, assemblers, Loaders, Linkers, Macro Processors.
v) Distributed Systems : Communication and Distributed Environment, Distributed Operating Systems, Distributed Shared Memory, Protocols, Fault Tolerance and Distributed File Systems, Distributed Object Based Systems.
vi) Programming And Data Structures : Problem Solving Techniques, Trees, Hashing and Priority Queues, Sorting, Graph, Heap Search.
vii) Algorithm Analysis And Design Techniques : Dynamic Programming, Greedy Algorithms, Advanced Algorithms, NP Completeness and Approximation Algorithms.
viii) Microprocessors And Microcontrollers  Computer Architecture And Organization : Digital Fundamentals, Combinational Circuits, Synchronous and Asynchronous Sequential Circuits, Instruction Set Architecture(RISC,CISC,ALU Design), Instruction Level Parallelism, Processing Unit and Pipelining, Memory Organization.
ix) Digital Signal Processing : FFT, Filter Design.
x) Computer Networks : Data Communication Systems, Applications.
xi) Database Management Systems : Relational Model, Database Design, Implementation
Techniques, Distributed Databases, Object Oriented Databases, Object Relational Databases, Data Mining and Data Warehousing.
xii) Software Engineering Methodologies : Software Product and Processes  Software Requirements Management  Requirement Engineering, Elicitation, Analysis, Requirements Development and Validation, Requirements Testing  Object Oriented Analysis And Design – Modular Design, Architectural Design, User Interface Design, Real Time Software Design, System Design, Data acquisition System  Software Testing And Quality Assurance  SQA Fundamentals, Quality Standards, Quality Metrics, Software Testing Principles, Defects, Test Case Design Strategies, Software Quality and reusability, Software Project Management, Software Cost Estimation, Function Point Models, Software Configuration Management, Software Maintenance.
xiii) Artificial Intelligence : Intelligent Agents, Search Strategies, Knowledge Representation, Learning, Applications.
xiv) Mobile Computing : Wireless Communication Fundamentals, Telecommunication Systems, Wireless Networks.
xv) Security In Computing : Program Security, Security in Operating Systems, Database and Network Security, Scientific Computing, Information Coding Techniques, Cryptography,Network Security.
Electronics(for VLSI)
I. Circuit Analysis: DC Circuit analysis, Thevenin’s and Norton’s equivalent circuits, Sinusoidal steady state analysis, Transient and resonance in RLC circuits. Electronic Devices: Diodes, Bipolar Junction Transistors, FET, MOSFET, UJT, Thyristor. Electronic Circuits: Small signal amplifiers using BJT and FET devices, Large signal amplifiers, Power supplies, Feed back amplifiers, Oscillators, Pulse shaping circuits. Digital Electronics: Logic gates, Combinational circuits, Sequential circuits. Linear Integrated Circuits: Operational amplifiers and its applications, PLL, Voltage regulators, A/D and D/A converters. Measurements and Instrumentation: Transducers, Digital Instruments, Display and Recording systems. Microprocessor and its applications: Microprocessors8085 and 8086 architectures and interfaces, Microcontroller and applications.
II. Electromagnetic Fields: Static Electric and Magnetic fields, Time varying Electric and Magnetic fields, Maxwell equations. Transmission Lines and Networks: Transmission line equations, impedance matching, Filters. EM waves and waveguides: Guided waves, Rectangular and cylindrical waveguides. Antennas and Propagation: Aperture antennas, arrays, Propagation of radio waves. Microwave Engineering: Microwave tubes, semiconductor devices, Passive components, Microwave measurements.
III. Communication Theory and Systems: AM, FM and PM, Sampling and Quantization, PCM, DM, ADM, Multiplexing. Digital Communication: Base band signaling, Band pass signaling, Error control coding, Spread spectrum techniques. Computer Communication Networks: Definition of layers, data link protocols, Network interconnection. Message routing technologies, EndEnd protocols. Optical Communication: Optical Fibers, optical transmitters and receivers.
IV. Signals and Systems: Continuous time signals and systemsFourier Transform, Laplace transform, Discrete time signals and systemsDTFT, DFT, ZTransform. Digital Signal Processing: IIR and FIR filters, Realization and implementation, Quantization effects. Control Systems: Transfer function, Time and frequency response analysis, Stability analysis, state variable analysis.
Preparation Strategy
Make a proper Time Table
It is very important that you make a time table and stick to it and you will have an exact idea of what you are required to study and the time required for it.
Concept clarity rather than rote learning
It is essential that you have a clear idea of the formulas and concepts rather than rote learning of things for the papers. While you might require it for memorizing formulas it is important that for other stuff you make sure you clear your basis and concepts before moving on.
Prepare Notes
It is very important make small notes or a comprehensive list of formulas on each covered topic and chapter which will come in handy at the time of revision. This will require you to be regular with your work but will surely make things easy at the time of revision.
Seek guidance
It is not possible for you to know everything in your syllabus, at least not at the time of preparation. Sooner or later you will run into a concept or so which will give you trouble and then it is best you seek guidance from an instructor or a teacher. It is necessary that you clear your doubts at regular intervals and don’t prolong things for long. Getting into a good coaching class is nothing to be ashamed off and if anything a regular coaching class will enable you to avoid roadblocks in your preparation.
Sample Papers
Even though there may be a complete change in the exam pattern or the expected questions altogether,it is important that you practice on the sample and previous years question papers available for the engineering exam you’d be attempting. You will know the existing pattern and have a fair idea of the type of questions to expect in the paper along with the time constraint.
Mock tests
The paper pattern, duration of the paper and the number of questions to be attempted in the given amount of time is not something you will be able to pick up on the day of the examination. A Mock Test tests a student’s abilities as it not only provides a similar feel of real exams but also helps in building speed and confident to face the exam. Furthermore, they can improve their performance to get an extra edge in actual exams. Try to build up an Engineering Entrance Exam Test Prep MCQ Question Bank
Time management
Time management can be learnt through thorough practice and regular test taking. So it is important that you practice it and practice it well.
Negative marking
Most the entrance examinations will have negative marking and everyone would suggest you stay clear of questions are not sure about. But some experts are of the opinion that you answer the questions in which you are confused between an option or two because there will also be a chance of getting it right.
Syllabus Summary  

No. Of Subjects  No. Of Units  No. Of Chapters 
11  15  71 
How To Prepare
EXAM SYLLABUS
(A) Logical Reasoning
(B) Mathematics
(C) Computer Fundamentals
(D) Computer Science(for CS/IT/SE)
(E) Electronics(for VLSI)
Logical Reasoning:
Analytical reasoning
Statements Assumptions
Non Verbal Tests (Visual reasoning)
Analogy Test
Inferences
Statements and assumptions
Statements Arguments
Cause and effects
Statements and conclusion
Ranking Tests
Linear arrangements
Matrix arrangements
Blood relationship test
Matrix arrangements
Symbol based problems
Sequencing, coding and decoding problem
Number series
Direction and Distance test
Mathematics
Algebra: Group, subgroups, Normal subgroups, Quotient Groups, Homomorphisms, Cyclic Groups, permutation Groups, Cayley’s Theorem, Rings, Ideals, Integral Domains, Fields, Polynomial Rings. Linear Algebra: Finite dimensional vector spaces, Linear transformations – Finite dimensional inner product spaces, selfadjoint and Normal linear operations, spectral theorem, Quadratic forms.
(ii) Analysis
Real Analysis: Sequences and series of functions, uniform convergence, power series, Fourier series, functions of several variables, maxima, minima, multiple integrals, line, surface and volume integrals, theorems of Green, Strokes and Gauss; metric spaces, completeness, Weierstrass approximation theorem, compactness. Complex Analysis: Analytic functions, conformal mappings, bilinear transformations, complex integration: Cauchy’s integral theorem and formula, Taylor and Laurent’s series, residue theorem and applications for evaluating real integrals.
(iii) Topology and Functional Analysis
Topology: Basic concepts of topology, product topology, connectedness, compactness, countability and separation axioms, Urysohn’s Lemma, Tietze extension theorem, metrization theorems, Tychonoff theorem on compactness of product spaces. Functional Analysis: Banach spaces, HahnBanach theorems, open mapping and closed graph theorems, principle of uniform boundedness; Hilbert spaces, orthonormal sets, Riesz representation theorem, selfadjoint, unitary and normal linear operators on Hilbert Spaces.
iii) Differential and integral Equations
Ordinary Differential Equations: First order ordinary differential equations, existence and uniqueness theorems, systems of linear first order ordinary differential equations, linear ordinary differential equations of higher order with constant coefficients; linear second order ordinary differential equations with variable coefficients, method of Laplace transforms for solving ordinary differential equations. Partial Differential Equations: Linear and quasilinear first order partial differential equations, method of characteristics; second order linear equations in two variables and their classification; Cauchy, Dirichlet and Neumann problems, Green’s functions; solutions of Laplace, wave and diffusion equations using Fourier series and transform methods. Calculus of Variations and Integral Equations: Variational problems with fixed boundaries; sufficient conditions for extremum, Linear integral equations of Fredholm and Volterra type, their iterative solutions, Fredholm alternative.
(v) Statistics & Linear Programming
Statistics: Testing of hypotheses: standard parametric tests based on normal, chisquare, t and F distributions.
Linear Programming: Linear programming problem and its formulation, graphical method, basic feasible solution, simplex method, bigM and two phase methods. Dual problem and duality theorems, dual simplex method. Balanced and unbalanced transportation problems, unimodular property and uv method for solving transportation problems. Hungarian method for solving assignment problems.
Computer Fundamentals
Operating System: Process Management System, CPU Scheduling, Memory management and Virtual memory, File systems, Deadlock, synchronization, Interprocess communication, I/O Systems. Disk operating System; Computer Network: ISO/OSI stack, Routing algorithms, IP addressing , internet protocol, X.25, Transmission medium, Signal encoding techniques, Application protocols, Security and cryptography; Computer Organization and Architecture: Machine instructions and addressing modes, ALU and datapath, CPU control design, Memory interface, Instruction pipelining, main memory, RISC and CISC; Automata Theory: Regular languages and finite automata , Chomsky Classification of languages, Context free grammars , Chomsky normal form, Greibach normal form, Turing machine , Recursive enumerable sets; Algorithms: Analysis, Notions of space and time complexity, Asymptotic analysis (best, worst, average cases) of time and space, array, Tree , Heap, Binary search tree ; Sorting, Searching, upper and lower bounds; Databases: Relational model(relational algebra, Relational calculus), Query languages (SQL, MSAccess), Database design, Transactions control; Software Engineering: information gathering, process life cycle; Programming: Programming in C, C++: Functions, Recursion, Parameter passing, Abstract data types, Arrays, Trees, Binary search trees, Binary heaps, File handling; Machine learning: Bayesian Learning Theory, Linear Analysis.
Computer Science(for CS/IT/SE)
i) Applied Probability And Operations Research : Random Processes, Probability Distributions,Queuing Models and Simulation, Testing of Hypothesis, Design of Experiments.
ii) Discrete Mathematical Structures : Formal Language and Automata  Graph Theory.
iii) Compiler Design : Optimization – Code Generation – Implementation – Principles of Programming Languages – Programming Paradigms.
iv) Operating Systems And System Software : Process Management, Storage Management, I/O Systems, Design and Implementation of LINUX OS, assemblers, Loaders, Linkers, Macro Processors.
v) Distributed Systems : Communication and Distributed Environment, Distributed Operating Systems, Distributed Shared Memory, Protocols, Fault Tolerance and Distributed File Systems, Distributed Object Based Systems.
vi) Programming And Data Structures : Problem Solving Techniques, Trees, Hashing and Priority Queues, Sorting, Graph, Heap Search.
vii) Algorithm Analysis And Design Techniques : Dynamic Programming, Greedy Algorithms, Advanced Algorithms, NP Completeness and Approximation Algorithms.
viii) Microprocessors And Microcontrollers  Computer Architecture And Organization : Digital Fundamentals, Combinational Circuits, Synchronous and Asynchronous Sequential Circuits, Instruction Set Architecture(RISC,CISC,ALU Design), Instruction Level Parallelism, Processing Unit and Pipelining, Memory Organization.
ix) Digital Signal Processing : FFT, Filter Design.
x) Computer Networks : Data Communication Systems, Applications.
xi) Database Management Systems : Relational Model, Database Design, Implementation
Techniques, Distributed Databases, Object Oriented Databases, Object Relational Databases, Data Mining and Data Warehousing.
xii) Software Engineering Methodologies : Software Product and Processes  Software Requirements Management  Requirement Engineering, Elicitation, Analysis, Requirements Development and Validation, Requirements Testing  Object Oriented Analysis And Design – Modular Design, Architectural Design, User Interface Design, Real Time Software Design, System Design, Data acquisition System  Software Testing And Quality Assurance  SQA Fundamentals, Quality Standards, Quality Metrics, Software Testing Principles, Defects, Test Case Design Strategies, Software Quality and reusability, Software Project Management, Software Cost Estimation, Function Point Models, Software Configuration Management, Software Maintenance.
xiii) Artificial Intelligence : Intelligent Agents, Search Strategies, Knowledge Representation, Learning, Applications.
xiv) Mobile Computing : Wireless Communication Fundamentals, Telecommunication Systems, Wireless Networks.
xv) Security In Computing : Program Security, Security in Operating Systems, Database and Network Security, Scientific Computing, Information Coding Techniques, Cryptography,Network Security.
Electronics(for VLSI)
I. Circuit Analysis: DC Circuit analysis, Thevenin’s and Norton’s equivalent circuits, Sinusoidal steady state analysis, Transient and resonance in RLC circuits. Electronic Devices: Diodes, Bipolar Junction Transistors, FET, MOSFET, UJT, Thyristor. Electronic Circuits: Small signal amplifiers using BJT and FET devices, Large signal amplifiers, Power supplies, Feed back amplifiers, Oscillators, Pulse shaping circuits. Digital Electronics: Logic gates, Combinational circuits, Sequential circuits. Linear Integrated Circuits: Operational amplifiers and its applications, PLL, Voltage regulators, A/D and D/A converters. Measurements and Instrumentation: Transducers, Digital Instruments, Display and Recording systems. Microprocessor and its applications: Microprocessors8085 and 8086 architectures and interfaces, Microcontroller and applications.
II. Electromagnetic Fields: Static Electric and Magnetic fields, Time varying Electric and Magnetic fields, Maxwell equations. Transmission Lines and Networks: Transmission line equations, impedance matching, Filters. EM waves and waveguides: Guided waves, Rectangular and cylindrical waveguides. Antennas and Propagation: Aperture antennas, arrays, Propagation of radio waves. Microwave Engineering: Microwave tubes, semiconductor devices, Passive components, Microwave measurements.
III. Communication Theory and Systems: AM, FM and PM, Sampling and Quantization, PCM, DM, ADM, Multiplexing. Digital Communication: Base band signaling, Band pass signaling, Error control coding, Spread spectrum techniques. Computer Communication Networks: Definition of layers, data link protocols, Network interconnection. Message routing technologies, EndEnd protocols. Optical Communication: Optical Fibers, optical transmitters and receivers.
IV. Signals and Systems: Continuous time signals and systemsFourier Transform, Laplace transform, Discrete time signals and systemsDTFT, DFT, ZTransform. Digital Signal Processing: IIR and FIR filters, Realization and implementation, Quantization effects. Control Systems: Transfer function, Time and frequency response analysis, Stability analysis, state variable analysis.
Preparation Strategy
Make a proper Time Table
It is very important that you make a time table and stick to it and you will have an exact idea of what you are required to study and the time required for it.
Concept clarity rather than rote learning
It is essential that you have a clear idea of the formulas and concepts rather than rote learning of things for the papers. While you might require it for memorizing formulas it is important that for other stuff you make sure you clear your basis and concepts before moving on.
Prepare Notes
It is very important make small notes or a comprehensive list of formulas on each covered topic and chapter which will come in handy at the time of revision. This will require you to be regular with your work but will surely make things easy at the time of revision.
Seek guidance
It is not possible for you to know everything in your syllabus, at least not at the time of preparation. Sooner or later you will run into a concept or so which will give you trouble and then it is best you seek guidance from an instructor or a teacher. It is necessary that you clear your doubts at regular intervals and don’t prolong things for long. Getting into a good coaching class is nothing to be ashamed off and if anything a regular coaching class will enable you to avoid roadblocks in your preparation.
Sample Papers
Even though there may be a complete change in the exam pattern or the expected questions altogether,it is important that you practice on the sample and previous years question papers available for the engineering exam you’d be attempting. You will know the existing pattern and have a fair idea of the type of questions to expect in the paper along with the time constraint.
Mock tests
The paper pattern, duration of the paper and the number of questions to be attempted in the given amount of time is not something you will be able to pick up on the day of the examination. A Mock Test tests a student’s abilities as it not only provides a similar feel of real exams but also helps in building speed and confident to face the exam. Furthermore, they can improve their performance to get an extra edge in actual exams. Try to build up an Engineering Entrance Exam Test Prep MCQ Question Bank
Time management
Time management can be learnt through thorough practice and regular test taking. So it is important that you practice it and practice it well.
Negative marking
Most the entrance examinations will have negative marking and everyone would suggest you stay clear of questions are not sure about. But some experts are of the opinion that you answer the questions in which you are confused between an option or two because there will also be a chance of getting it right.
Banasthali University Aptitude Test  M.Tech Computer Science Eligibility Criteria
Educational qualification

M.Tech.(Computer Science): B.E./B.Tech.(Computer Science/Engg)/M.Sc.(Comp.Sc.)/MCA/M.Sc.(Maths: Theoretical Computer Science) with a minimum of 55% aggregate marks.

The Minimum Eligibility for appearing in the Aptitude Test for students passing the qualifying examination from Banasthali University will be 50% aggregate marks in the qualifying examination.

Applicants who fail to appear in the Aptitude test will not be considered under any circumstances.
Age N/A
Marks minimum of 55% aggregate marks in B.E./B.Tech.
Relaxation policy (if any) For SC/ ST candidates the minimum eligibility is 40% aggregate in 10+2 with subjects as above.
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