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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;
Krushkal's algorithm uses the concept of forest of trees. At first the forest contains n single node trees (and no edges). At each of the step, we add on one (the cheapest one) edg
Write a program that uses the radix sort to sort 1000 random digits. Print the data before and after the sort. Each sort bucket should be a linked list. At the end of the sort, the
Best Case: If the list is sorted already then A[i] T (n) = c1n + c2 (n -1) + c3(n -1) + c4 (n -1) = O (n), which indicates that the time complexity is linear. Worst Case:
Explain binary search with an example
Construct a B+ tree for the following keys, starting with an empty tree. Each node in the tree can hold a maximum of 2 entries (i.e., order d = 1). Start with an empty root nod
Explain divide and conquer algorithms Divide and conquer is probably the best known general algorithm design method. It work according to the following general p
What are the features of an expert system
In internal sorting, all of the data to be sorted is obtainable in the high speed main memory of the computer. We will learn the methods of internal sorting which are following:
Determine about the unreachable code assertion An unreachable code assertion is an assertion that is placed at a point in a program that shouldn't be executed under any circum
basic calculation for algorith.
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