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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;
illlustraate the construction of tree of a binary tree given its in order and post order transversal
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why the space increase in less time programs
The two pointers per number of a doubly linked list prepare programming quite easy. Singly linked lists as like the lean sisters of doubly linked lists. We need SItem to consider t
The total of time needed by an algorithm to run to its completion is termed as time complexity. The asymptotic running time of an algorithm is given in terms of functions. Th
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how to define the size of array
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