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1) The set of the algorithms whose order is O (1) would run in the identical time. True/False
2) Determine the complexity of the following program into big O notation:
printMultiplicationTable(int max){
for(int i = 1 ; i <= max ; i + +)
{
for(int j = 1 ; j <= max ; j + +) cout << (i * j) << " " ; cout << endl ;
} //for
3) Assume the following program segment:
for (i = 1; i <= n; i *= 2)
j = 1;
}
Find out running time of the above program segment into big O notation?
4) Prove that if f(n) = n2 + 2n + 5 and g(n) = n2 then f(n) = O (g(n)).
5) How several times does the given for loop will run
for (i=1; i<= n; i*2)
k = k + 1;
end;
Multidimensional array: Multidimensional arrays can be defined as "arrays of arrays". For example, a bidimensional array can be imagined as a bidimensional table made of elements,
Q. Write down an algorithm to convert an infix expression into the postfix expression. Ans. Algo rithm to convert infix expression to post fix expression is given as
The complexity Ladder: T(n) = O(1). It is called constant growth. T(n) does not raise at all as a function of n, it is a constant. For illustration, array access has this c
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Draw trace table and determine the output from the below flowchart using following data (NOTE: input of the word "end" stops program and outputs results of survey): Vehicle = c
Explain binary search with an example
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draw a flowchart which prints all the even numbers between 1-50
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