2. Suppose the function MergeSort( O s a recursive implementation of the merge sort algorithm, which takes as input an integer array A. How many tìmes MergeSort() recursively called, if A is of size n? Answer: I Select| Select Ofnlogn) 3. How many times is the Merge routine called in total, O(1) On^2) swer. Select]

Plese Explain Q 5. Thank you.

Using Java, 1. Implement external sort: for sort phase use normal sort,   for merge phase use two way merge to merge n sorted files (merge2way(n)), for array sort use heapsort. Also write merge(f1, f2, f3) to merge two sorted files f1 and f2 into f3.. Write mergenway(n) method and print execution time of both merges for initial input file over 10MB data.  A sample input is as follow:Note:Fist input is max array size for sort           10   84   82   52   80   96   85   75   75   82   87  92   89   57   94   93   92   63   99   87  72   73   56   74   50   84   62   72   55   86   75  74  100   83   60   53   68   89   67  66  65   72   94   73   54   98   96   85   75   75   82   87  92   89

Below is the exercise for unsorted arrays. True or False: For each statement below, indicate whether you think it is True or False 3) For the insert function, if the array is empty, there are no comparison operations that need to be performed and you can immediately add the new element 5) Because the update algorithm depends on using linear search, its performance is O(1) in the worst case scenario 6) If you search for and delete an element in an unsorted array and then shift the rest of the elements to fill the hole, the worst case performance is O(n) 7) If you search for and delete an element in an unsorted array and then move the last element to fill the hole, the worst case performance is O(n)

Let A = [n, n − 1, n − 2, . . . , 3, 2, 1] be an array where the first n positive integers are listed in decreasing order. Determine whether Heapsort or Quicksort sorts this array faster.For this question, assume the Quicksort pivot is always the right-most element.

ALGORITHM Quicksort(A[l..r])//Sorts a subarray by quicksort//Input: Subarray of array A[0..n − 1], defined by its left and right// indices l and r//Output: Subarray A[l..r] sorted in nondecreasing order  if l < r    s = Partition(A[l..r]) //s is a split position    Quicksort(A[l..s − 1])    Quicksort(A[s + 1..r]) The above code is the quicksort algorithm.Perform a time complexity analysis for quicksort. You need to explain 1) what makes a worst case, what makes a best case, 2) the time complexity for both the worst case and the best case, 3) how to avoid the worst case in practice.

Let A be an array, where each of the n elements is a randomly chosen digit between 0 and 9. For example, if n = 12, this array could be A = [3,5,1,0,5,7,9,2,2,8,8,6]. Determine whether Counting Sort or Merge Sort sorts this array faster.

All parts of Q11 please.

Create a merge-sort multithread.A is an array, and p and q are array indexes used to sort the sub-array A[p..r]. B is a subarray that will be filled by the sort. A p-merge-sort(A,p,r,B,s) call sorts items from A[p..r] and places them in B[s..s+r-p].