CS2406 Open Source Lab-LM

CS2406 Open Source Lab-LM

    HYPERTEXT PREPROCESSOR(PHP)          

What is PHP

• PHP stands for PHP: Hypertext Preprocessor
• PHP is a powerfull tool for making dynamic and interactive web pages.
• PHP is the widely used, free, and efficient alternative to competitors such as Microsoft’s ASP.
• PHP is a server-side scripting language, like ASP
• PHP scripts are executed on the server
• PHP supports many databases (MySQL, Informix, Oracle, Sybase, Solid, PostgreSQL, Generic ODBC, etc.)
• PHP is an open source software
• PHP is free to download and use 

CS2251 -DESIGN AND ANALYSIS OF ALGORITHMS UNIT I QUESTIONS 1

16.            What do you mean by ²Best case-Efficiency” of an algorithm?

The ²Best case-Efficiency” of an algorithm is its efficiency for the Best-case input of size n, which is an input(or inputs)  of size n for which the algorithm runs the fastest among all possible inputs of that size.

    Ex: if you want to sort a list of numbers in ascending order when the numbers are given in ascending order. In this running time will be the smallest.

17.            Define the ²Average-case efficiency” of an algorithm?

The ²Average-case efficiency” of an algorithm is its efficiency for the  input of size n,  for which the algorithm runs between the best case and the worst case among all possible inputs of that size.

18.            What do you mean by “Amortized efficiency”?

The “Amortized efficiency” applies not only a single run of an algorithm but rather to a sequence of operations performed on the same data structure. It turns out that in some situations a single operation can be expensive ,but the total  time for an entire sequence of n such operations is always significantly better than the worst case efficiency of that single operation multiplied by n. This is known as “Amortized efficiency”.

19.            How to measure the algorithm’s efficiency?

It is logical to investigate the algorithm’s efficiency as a function of some parameter n indicating the algorithm’s input size.

Example: It will be the size of the list for problems of sorting, searching, finding the list’s smallest element, and most other problems dealing with lists.

20.            What is called the basic operation of an algorithm?

            The most important operation of the algorithm is the operation contributing the most to the total running time is called basic operation of an algorithm.

21.            How to measure an algorithm’s running time?

Let C_op be the time of execution of an algorithm’s basic iteration on a particular computer and let C (n) be the number of times this operation needs to be executed for this algorithm.  Then we can estimate the running time T(n) of a program implementing this algorithm on that computer by the formula

                                    T(n)   ≈  C_op C(n)

22.            Define order of growth.

            The efficiency analysis framework concentrates on the order of growth of an algorithm’s basic operation count as the principal indicator of the algorithm’s efficiency.  To compare and rank such orders of growth we use three notations

1)                                                      O (Big oh) notation

2)                                                      Ω (Big Omega) notation &

3)                                                      Θ (Big Theta) notation

23.            Define Big oh notation May/June 2006, April/May 2008

A function t(n) is said to be in O(g(n)) denoted t(n) ε O (g(n)), if t(n) is bounded above by some constant multiple of g(n) for all large n, i.e., if there exist some positive constant c and some non negative integer n₀ such that

                                    T (n) < c g (n) for n > n₀

CS2251 -DESIGN AND ANALYSIS OF ALGORITHMS UNIT I QUESTIONS

CS2251 -DESIGN AND ANALYSIS OF ALGORITHMS

UNIT –I

  1.                What is an Algorithm?  May/June 2006, Nov/Dec 2008

An algorithm is a sequence of unambiguous instructions for solving a problem, i.e., for obtaining a required output for any legitimate input in a finite amount of time

2.                State the Euclid’s algorithm for finding GCD of two given numbers.

ALGORITHM Euclid (m, n)

// Computes gcd(m,n) by Euclid’s algorithm

//Input   : Two nonnegative, not-both-zero integers m and n

//Output: Greatest common divisor of m and n

while n ¹ 0 do

                                    r ß m mod n

                                    m ß n

                                    n ß r

return m.

3.                What are Sequential Algorithms?

The central assumption of the RAM model is that instructions are executed one after another, one operation at a time. Accordingly, algorithms designed to be executed on such machines are called Sequential algorithms.

4.                What are Parallel Algorithms?

The central assumption of the RAM model does not hold for some newer computers that can execute operations concurrently, i.e., in parallel algorithms that take advantage of this capability are called Parallel algorithms.

5.                What is Exact and Approximation algorithm?

The principal decision to choose solving the problem exactly is called exact algorithm.

The principal decision to choose solving the problem approximately is called Approximation algorithm.

6.                What is Algorithm Design Technique?  Nov/Dec 2005

            An algorithm design technique is a general approach to solving problems algorithmically that is applicable to a variety of problems from different areas of computing.

7.                Define Pseudo code.

A Pseudo code is a mixture of a natural language and programming language like constructs. A pseudo code is usually more precise than a natural language, and its usage often yields more succinct algorithm descriptions.

CS2251 -DESIGN AND ANALYSIS OF ALGORITHMS UNIT V QUESTIONS

UNIT V

1) Define tractable and intractable problems

Problems that can be solved in polynomial time are called tractable problems, problems that cannot be solved in polynomial time are called intractable problems.

2) Explain the theory of computational complexity

A problem's intractability remains the same for all principal models of computations and all reasonable input encoding schemes for the problem under consideration

3)Explain class P problems

Class P is a class of decision problems that can be solved in polynomial time by(deterministic) algorithms. This class of problems is called polynomial.

4)Explain undecidable problems

If the decision problem cannot be solved in polynomial time, and if the decision problems cannot be solved at all by any algorithm. Such problems are called Undecidable.

5) Explain the halting problem

Given a computer program and an input to it,determine whether the program will halt on that input or continue working indefinitely on it.

CS2251 -DESIGN AND ANALYSIS OF ALGORITHMS UNIT IV QUESTIONS

UNIT IV

l) Explain Backtracking

The principal idea is to construct solutions one component at a time and evaluate such partially constructed candidates as follows.

> If a partially constructed solution can be developed further without violating the problem's constraints, it is done by taking the first remaininig legitimate option for the next component.

> If there is no legitimate option for the next component, no alternatives for any remaining component need to be considered.

In this case, the algorithm backtracks to replace the last component of the partially constructed solution with its next option

2) Explain State Space Tree

If it is convenient to implement backtracking by constructing a tree of choices being made, the tree is called a state space tree. Its root represents an initial state before the search for a solution begins.

3) Explain promising and nonpromising node

A node in a state space tree is said to be promising if it corresponds to a partially constructed solution that may still lead to a complete solution;otherwise it is called nonpromising

4) Explain n-Queens problem

The problem is to place n queens on an n by n chessboard so that no two queens attack each other by being in the same row or same column or on the same diagonal.

5) Explain Subset-Sum Problem

CS2251 -DESIGN AND ANALYSIS OF ALGORITHMS UNIT III QUESTIONS

UNIT III

1)Define Dynamic Programming

Dynamic programming is a technique for solving problems with overlapping problems. Typically, these subproblems arise from a recurrence relating a solution to a given problem with solutions to its smaller subproblems of the same type. Rather than solving overlapping subproblems again and again, dynamic programming suggests solving each of the smaller sub problems only once and recording the results in a table from which we can then obtain a solution to the original problem.

2) Define Binomial Coefficient

                                                                                         n

The Binomial Coefficient, denoted C(n,k) or   k     is the number of Combinations(subsets) of k elements from an n-element set(0<k<n). The name "binomial coefficients" comes from the participation of these numbers in the so called binomial formula

(a+b)ⁿ =(n,0)aⁿ+..........+C(n,i)a^n-ibⁱ+.......+C(n,n)bⁿ

3) Define Transitive closure

The transitive closure of a directed graph with n vertices can be defined as the n by n Boolean matrix T = {ti,}, in which the element in the i^th row (1<i<n) and the j^th column (l<j<n) is 1 if there exists a non trivial directed path from the i^th vertex to j^th vertex ; otherwise , t_ij is 0.

4) Explain Warshalls algorithm

Warshall's algorithm constructs the transitive closure of a given digraph with n vertices through a series of n by n Boolean matrices  R⁽⁰⁾, ………, R^(k-l)R^(k),…….., R⁽ⁿ⁾

Each of these matrices provides certain information about directed paths in the digraph.

CS2251 -DESIGN AND ANALYSIS OF ALGORITHMS UNIT I QUESTIONS

CS2251 -DESIGN AND ANALYSIS OF ALGORITHMS

UNIT –I

  1.                What is an Algorithm?  May/June 2006, Nov/Dec 2008

An algorithm is a sequence of unambiguous instructions for solving a problem, i.e., for obtaining a required output for any legitimate input in a finite amount of time

2.                State the Euclid’s algorithm for finding GCD of two given numbers.

ALGORITHM Euclid (m, n)

// Computes gcd(m,n) by Euclid’s algorithm

//Input   : Two nonnegative, not-both-zero integers m and n

//Output: Greatest common divisor of m and n

while n ¹ 0 do

                                    r ß m mod n

                                    m ß n

                                    n ß r

return m.

3.                What are Sequential Algorithms?

The central assumption of the RAM model is that instructions are executed one after another, one operation at a time. Accordingly, algorithms designed to be executed on such machines are called Sequential algorithms.

4.                What are Parallel Algorithms?

The central assumption of the RAM model does not hold for some newer computers that can execute operations concurrently, i.e., in parallel algorithms that take advantage of this capability are called Parallel algorithms.

5.                What is Exact and Approximation algorithm?

The principal decision to choose solving the problem exactly is called exact algorithm.

The principal decision to choose solving the problem approximately is called Approximation algorithm.

6.                What is Algorithm Design Technique?  Nov/Dec 2005

            An algorithm design technique is a general approach to solving problems algorithmically that is applicable to a variety of problems from different areas of computing.

7.                Define Pseudo code.

A Pseudo code is a mixture of a natural language and programming language like constructs. A pseudo code is usually more precise than a natural language, and its usage often yields more succinct algorithm descriptions.

DESIGN AND ANALYSIS OF ALGORITHMS ANNA UNIVERSITY PREVIOUS YEAR QUESTION PAPER DOWNLOAD

CS2251 - DESIGN AND ANALYSIS OF ALGORITHMS ANNA UNIVERSITY PREVIOUS YEAR QUESTION PAPER DOWNLOAD

B.E./B.Tech. DEGREE EXAMINATION, APRIL/MAY 2010.

Fourth Semester

Computer Science and Engineering

CS2251 - DESIGN AND ANALYSIS OF ALGORITHMS

(Regulation 2008)

Time: Three hours                                                                                                  Maximum:100 marks

Answer ALL Questions.

PART A- (10 X 2= 20 marks)

1. Differentiate Time complexity from Space complexity.

2. What is a Recurrence Equation?

3. What is called Substitution method?

4. What is an Optimal solution?

5. Define Multistage Graphs.

6. Define Optimal Binary Search Tree.

7. Differentiate Explicit and Implicit Constraints.

8. What is the difference between a Live Node and a Dead Node?

9. What is a Biconnected Graph?

10. What is a FIFO branch - and - bound algorithm?

PART B- (5 X 16 = 80 Marks)

JAVA PROGRAMMING QUESTION BANK PART 5

Unit-5

Two Marks
1. What is Networking?
2. What is UDP? Explain its purpose?
3. What is a Proxy Server?
4. What is DNS?
5. Explain TCP/IP Client Sockets?
6. What is URL Connection?
7. What is a Datagram?
8. What is URL & give its format?
9. What is the difference between TCP/IP Programming & datagram Programming? 
10. What is Event Handling?

JAVA PROGRAMMING QUESTION BANK PART 4

Unit-4

1. What is a thread?
2. What is the difference between multiprocessing and multithreading?
3. What is to be done to implement multithreading in a program?
4. What java interface must be implemented by all threads?
5. How to start a thread?
6. What are the 2 methods by which we may stop threads?
7. Difference between Suspending and stopping a thread?
8. How do we set priorities for threads?
9. Describe in brief the complete lifecycle of a thread?
10. What is synchronization? When do we use it?
11. Give some real life situations that illustrate the use of multithreading?
12. What is a file? Why do we require files to store data?
13. What is a stream? How is the concept of Streams used in Java?
14. What are I/P & O/P Streams?
15. What is Stream class?

JAVA PROGRAMMING QUESTION BANK PART 3

Unit-3:
2 marks:
1. What is inheritance? What are its types?
2.What is the use of super keyword in java?
3. What is method overloading?
4. What is overriding of methods?
5. What is the need of overridden methods?
6. What is dynamic method dispatch?
7.What is the use of final class in Java?
8. Define an abstract class with suitable examples?
9. What are the characteristics of an abstract class?
10.What is a package? How to define a package?
11. Describe access protection?

JAVA PROGRAMMING QUESTION BANK PART 2

UNIT-2
2-MARKS
1.What are objects?
2.What is a class?(define class)
3.What are instance variables?
4.Give the general form of method declaration?
5.How object are created in C++ and java>Explain with eg.
6.How to access class members of a class?
7.Define constructors?
8.Explain the usage of constructors?
9.What is method overloading?
10.What is static variable?
11.Explain static methods?
12.What ios nesting of methods w.r.t java?
13.What are the types of inheritance possible in java?
14.Explain the usage of inheritance?
15.What is function overloading?
16.When a variable is called a “final” variable and what is its use?
17.What are final methods and final classes?
18.What is finalization?

JAVA PROGRAMMING QUESTION BANK PART 1

UNIT-1
1.What are the features of java?
2.What is byte code interpretation?
3.Why is java strongly typed programming language?
4.Explain the OOPS concept briefly?
5.Why java is architectural-neutral?
6.What is byte code?
7.What is the use of JVM?
8.Why java is important to internet?
9.What is inheritance?
10.what is overloading and overriding?
11.What is polymorphism?
12.What is data abstraction?
13.What are difference between single inheritance, multiple inheritance and multilevel inheritance?
14.What is a constant?

TCP/IP & OSI:

TCP/IP & OSI:

In OSI reference model terminology -the TCP/IP protocol suite covers the network and transport layers.

TCP/IP can be used on many data-link layers (can support many network hardware implementations).

Ethernet - A Real Data-Link Layer

Supported by a variety of physical layer implementations.

It will be useful to discuss a real data-link layer.

Ethernet (really IEEE 802.3) is widely used.

Multi-access (shared medium).

Every Ethernet interface has a unique 48 bit address (a.k.a. hardware address).

Example:   C0:B3:44:17:21:17

The broadcast address is all 1’s.

Addresses are assigned to vendors by a central authority

CSMA/CD
 Carrier Sense Multiple Access
with
Collision Detection

Carrier Sense: can tell when another host is transmitting

Multiple Access: many hosts on 1 wire

Collision Detection: can tell when another host transmits at the same time.

An Ethernet Frame

ANNA UNIVERSITY PROFESSORS JOBS 2012

PROFESSORS | ASSOCIATIVE PROFESSORS | ASSISTANT PROFESSORS JOBS IN COIMBATORE 2012

 1.NANDHA ENGINEERING COLLEGE AND TECHNOLOGY - COIMBATORE.

2.SRIGURU INSTITUTE OF TECHNOLOGY - COIMBATORE.

Dear job seekers ,

                      Here i have attached with the complete attachment for recruitment advertisement . Its very useful for all. If you want to subscribe this news regularly , go the follow by e-mail gadget and submit your e-mail ids.You will get regular updates. want to get more details :http://tngovjobs.blogspot.in/

3.SASTRA UNIVERSITY RECRUITMENT 2012 - THANJAVUR.

4.P.A.COLLEGE OF ENGINEERING AND TECHNOLOGY - COIMBATORE

Dear job seekers ,

                      Here i have attached with the complete attachment for recruitment advertisement . Its very useful for all. If you want to subscribe this news regularly , go the follow by e-mail gadget and submit your e-mail ids.

Faculty Jobs in Tamilnadu 2011, Anna University Coimbatore, coimbatore professors jobs 2012,tamilnadu professors jobs 2012, 2012 tn govt jobs,

OPERATING SYSTEMS (Common to CSE & IT) Syllabus

CS 2254                                  OPERATING SYSTEMS                                     3  0  0  3

             (Common to CSE & IT)

Aim: To learn the various aspects of operating systems such as process management, memory management, and I/O management

UNIT I                         PROCESSES AND THREADS                                                                    9

Introduction to operating systems – review of computer organization – operating system structures – system calls – system programs – system structure – virtual machines. Processes: Process concept – Process scheduling – Operations on processes – Cooperating processes – Inter-process communication – Communication in client-server systems. Case study: IPC in Linux. Threads: Multi-threading models – Threading issues. Case Study: Pthreads library

UNIT II            PROCESS SCHEDULING AND SYNCHRONIZATION  

COMMUNICATION THEORY LECTURE PLAN and LESSON PLAN

 

LECTURE PLAN

Name of the staff    : XXXXXXXXXXXXXX                                        Department  : ECE

Subject                      : COMMUNICATION THEORY                            Sub Code       : EC2252

Branch                       : ECE                                                                         Semester       : IV

UNIT	TOPICS COVERED	HOURS REQUIRED	EXTRA HOURS
I	AMPLITUDE MODULATION SYSTEMS	12	-
II	ANGLE MODULATION SYSTEMS	12	-
III	NOISE THEORY	12	-
IV	PERFORMANCE OF CW MODULATION SYSTEMS	12	-
V	INFORMATION THEORY	12	-

Students will engage in:

  Independent Activities                                                            Seminars

  Tutoring                                                                         Lecture

  Visuals                                                                           Simulations

  Assignments                                                                  Motivative Study

                                                                                           Others

Procedure Followed:

1.      Class starter

2.      Review of Previously learned material/Lesson connections

3.      Statement of objectives

4.      Presentation of new materials

5.      Guided practice with corrective feedback

6.      Assign independent practice with corrective feedback

7.      Lesson review / Re-teach

MICROPROCESSORS AND MICROCONTROLLERS LECTURE PLAN

LECTURE PLAN

Name of the staff    : XXXXXXXXXXX                                                Department  : ECE

Subject                      : MICROPROCESSORS AND MICROCONTROLLERS    Sub Code       : CS2252

Branch                       : CSE                                                                          Semester       : IV

UNIT	TOPICS COVERED	HOURS REQUIRED	EXTRA HOURS
I	THE 8085 AND 8086 MICROPROCESSORS	9	-
II	8086 SOFTWARE ASPECTS	9	-
III	MULTIPROCESSOR CONFIGURATIONS	9	-
IV	I/O INTERFACING	9	-
V	MICROCONTROLLERS	9	-

Students will engage in:

  Independent Activities                                                            Seminars

  Tutoring                                                                         Lecture

  Visuals                                                                           Simulations

  Assignments                                                                  Motivative Study

                                                                                           Others

Procedure Followed:

PRINCIPLES OF COMPILER DESIGN Syllabus:

Syllabus:

PRINCIPLES OF COMPILER DESIGN

L T P

3 1 0

UNIT I           INTRODUCTION TO COMPILING                                                        9

Compilers − Analysis of the source program − Phases of a compiler − Cousins of the compiler − Grouping of phases − Compiler construction tools − Lexical analysis − Role of lexical analyzer − Input buffering − Specification of tokens.

UNIT II          SYNTAX ANALYSIS                                                                                 9

Role of the parser − Writing grammars − Context-free grammars − Top down parsing − Recursive descent parsing − Predictive parsing − Bottom-up parsing − Shift reduce parsing − Operator precedence parsing − LR parsers − SLR parser − Canonical LR parser − LALR parser.

UNIT III        INTERMEDIATE CODE GENERATION                                              9

Intermediate languages − Declarations − Assignment statements − Boolean expressions −

Case statements − Back patching − Procedure calls.