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April 28, 2021
Question 1
it divided into smaller subproblems and then solve each problem independently
the problem should be able to be divided into smaller overlapping sub-problem
the closest solution that seems to provide an optimum solution is chosen
none
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In the divide and conquer approach, the problem in hand is divided into smaller sub-problems, and then each problem is solved independently.
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Question 2
Divide/Break
Conquer/Solve
Merge/Combine
All the mention
The divide-and-conquer approach in a three-step process that is break, solve, and combine.
Question 3
Merge Sort
Quick Sort
Binary Search
All the above
The above mentioned and closest pair of points, Strassen’s algorithm is a good example of a divide and conquer approach.
Question 4
Quick sort
Merge sort
Selection sort
Heap sort
The quick sort algorithm picks a pivot element, rearranges the array elements in such a way that all elements smaller than the picked pivot element move to the left side of the pivot, and all greater elements move to the right side. Finally, the algorithm recursively sorts the subarrays on the left and right of the pivot element.
Question 5
O(nlogn), O(n2) and O(nlogn)
O(n), O(nlogn) and O(nlogn)
O(n), O(n2) and O(nlogn)
O(n2), O(n2) and O(logn)
These are the time complexity of QuickSort.
Question 6
Divide
Conquer
Combine
None
The sub-problem by calling recursively until sub-problem solved is known as Conquer.
Question 7
The Sub problem Solved so that we will get find a problem solution is called a combine.
Question 8
This involves dividing the problem into some sub-problem is termed as divide.
Question 9
Binary search
This involves dividing the problem into some sub-problem that is termed as Merge sort.
Question 10
quick-sort with random output
quick-sort with random input
quick-sort with a random choice of pivot
quick-sort with random partitions
Randomized Quicksort selects a random element as a pivot. This is done to avoid the worst case of a quick sort in which the array of inputs is already sorted.
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