Write the c++ code according to the following algorithm insert 1357 using forloop and then while loop
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Write the c++ code according to the following
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- Conduct doubling experiments to compute the run time and plot the results (for array A and B ) for array sizes n = 2, 4, ... 1024. The function merge_sort (provided) . def merge (front, back): pos_f, pos_b = 0,0 merged = np.zeros(len(front)+len(back)) for i in range (len(merged)): if pos_f == len(front): merged[i] = back[pos_b] pos_b += 1 elif pos_b == len(back): merged[i] = front[pos_f] pos_f += 1 elif front[pos_f] < back[pos_b]: merged[i] = front[pos_f] pos_f += 1 else: merged[i] = back[pos_b] pos_b += 1 return merged def merge_sort(A): n = len(A) if n <= 1: return A mid = int(n/2) front = merge_sort(A[0:mid]) back = merge_sort(A[mid:]) return merge(front, back) ARRAY A) Ai s perfectly sorted and contains random integers (0 to 100 inclusive). b) B is reversely sorted and contains random integers (0 to 100 inclusive)a. Propose a data structure that supports the stack push and pop operations and a third operation FindMin, which returns the smallest element in the data structure, all in O(1) worst case time. b. Prove that if we add the fourth operation DeleteMin which finds and removes the smallest element, then at least one of the operations must take Ω(log n) time.1) Suppose hashing is being done by using open addressing with linear probing. The hash function tobe used for an element with key k is h(k) = k mod 11. Show the contents of the hash table afterinserting the following keys in order into the hash table:27 40 22 15 31 18 36 19 20
- For this given code, please help me create a recursive case for transpose of matrix using the cache oblivious algorithm. for ( size_t i=0; i<n; i += block ) { for ( size_t j=0; j<n; j++ ) { for ( size_t b = 0; b < block && i + b < n; ++b){ b[ j*n + i ] = a[ i*n + j ]; } } else { recursMatTranspose ( n, n, a, 0, 0, b, 0, 0 ); //recursive case using cache-oblivious algo } }Please convert to C language //quadratic probing#include <bits/stdc++.h>using namespace std; void add_using_quadratic_probing(int hash[], int a){ //hash function h(x)=x%10 int k = a % 10; //quadratic probing int incr = 1; while (true) { if (hash[k] == -1) { hash[k] = a; break; } //quadratic increment of probe k = (k + int(pow(incr, 2))) % 10; incr++; }} int main(){ //set of input numbers vector<int> arr{ 123, 124, 333, 4679, 983 }; //initialize the hash table //each entry of the hash table is a single entry int hash[10]; //size of hashtable is 10 memset(hash, -1, sizeof(hash)); //initialize with empty initially for (int a : arr) { //hashing add_using_quadratic_probing(hash, a); } cout << "---------using quadratic probing---------\n"; cout << "Hash table is:\n"; for (int i = 0; i < 10; i++) { if (hash[i] == -1) cout…C++ R-11.2 - Suppose S is a list of n bits, that is, n 0’s and 1’s. How long will it take to sort S with the merge-sort algorithm? What about quick-sort?
- The amortized time efficiency for performing deletion of a minimum element is?a) O(N)b) O(log N)c) O(N2)d) O(M log N)Q3. Compute the cost of r JOINA=B s using the method of index loops with an index of height 2 on B of s. Do the computation for the clustering index case. Assume that r occupies 4,000 blocks with 20 tuples per block, s occupies 10,000 blocks with 5 tuples per block, and the amount of main memory available is 402 blocks. Assume that at most 5 tuples in s match each tuple in r.Given an array A and two indices p and r consider the following modified merge sort algorithm write a recurrence relation describing the running time of algorithm modified merge sort(A, p,r) include base case. mofified merge sort (A, p, r) if p<r n = r - p + 1 q = n/3 foo(A,p,p + q) foo (A,p, + q + 1, p + 2q) foo(A, P + 2q + 1, r) merge (A, p, p + q, p + 2q) merge(A, p,p + 2q,r)
- Modify the FindBestPlan(S) function to create a function FindBestPlan(S, O),where O is a desired sort order for S, and which considers interesting sortorders. A null order indicates that the order is not relevant. Hints: An algorithmA may give the desired order O; if not a sort operation may need to be added to get the desired order. If A is a merge-join, FindBestPlan must be invoked on the two inputs with the desired orders for the inputs.What is the time complexity of deleting an element from a sorted array? Does it have better time complexity than deleting a node from an unsorted array? Why? What is the time complexity of append operation of an unsorted array of size n? why? What is the time complexity (in big-O notation) of binary search in a sorted array containing m (m >0) numbers? Why is the insertion not supported for unsorted array? What are the fundamental operations of an unsorted array?S1 and S2 are two sorted stacks of n and m numbers sorted in decreasing order, with their top items pointing to the smallest in their lists, respectively. Create a stack MERGE that merges the items in stacks S1 and S2, so that at the conclusion of the merge, all of the elements in S1 and S2 are available in MERGE in decreasing order, with the largest element at the top.Keep in mind that the number of components in stack MERGE is (n + m).