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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;
Five popular hashing functions are as follows: 1) Division Method 2) Midsquare Method 3) Folding Method 4) Multiplicative method 5) Digit Analysis
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characteristics of a good algorithm
Worst Case: For running time, Worst case running time is an upper bound with any input. This guarantees that, irrespective of the type of input, the algorithm will not take any lo
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write an algorithm to delete an element x from binary search with time complex
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