Consider the algorithm given below.     ALGORITHM MinDistance(A[0..n − 1])     //Input: Array A[0..n − 1] of numbers     //Output: Minimum distance between two of its elements         dmin←∞          for i ←0 to n − 1 do                 for j ←0 to n − 1 do                          if i != j and |A[i]− A[j ]| < dmin                                   dmin ←|A[i]− A[j ]|       return dmin if  n = 20, and the list is sorted in descending order, then the loop  " or i ←0 to n − 1 do " will be executed ______ times.

Given an integer array nums sorted in non-decreasing order, return an array of the squares of each number sorted in non-decreasing order. Example 1: Input: nums = [-4,-1,0,3,10] Output: [0,1,9,16,100] Explanation: After squaring, the array becomes [16,1,0,9,100]. After sorting, it becomes [0,1,9,16,100]. Example 2: Input: nums = [-7, -3,2,3,11] Output: [4.9,9,49,121]

See the pseudo-code of the Binary Search using recursion below. Fill in the XXXX and YYYY in the code Algorithm BinarySearch (A,v,low,hi) Input: array A indexed from low to hi with items sorted from smallest to largest. We are searching for the item v Output: returns a location index of item v in array A; if v is not found, -1 is returned. if (low > hi) then return (-1); mid = (lo + hi)/2; if (A[mid] = v) then == return(mid); if (A[mid] < v) then return(BinarySearch(A, XXXX ,hi, v)); else return(BinarySearch(a, lo, YYYY, v)); О а. ХX: lo+1, YҮҮ: hi O b. XXXX: mid, YYYY: mid О с. ХXXX: lo, YYYY: hi O d. XXXX: lo+1, YYYY: hi-1 O e. XXXX: mid+1. YYYY: mid-1

You are given an array A[1, ., n] in which the elements A[2] to A[n] are already sorted, i.e., A[2, .., n] is a sorted array. Write down an efficient algorithm with proper pseudocode for moving A[1] in the correct place, so that the full array A[1, ..., n] is sorted.

Q1.  Write the code necessary to find the largest element in an unsorted array of integers. What is the time complexity of this algorithm?               Q2.  Determine the growth function and order of the following code fragment: for (int count=0; count < n; count++) { for (int count2=0; count2 < n; count2=count2+2) { System.out.println(count, count2); } }                                                                                     Q3. Determine the growth function and order of the following code fragment: for (int count=0; count < n; count++) { for (int count2=0; count2 < n; count2=count2*2) { System.out.println(count, count2); } }     Q4. What is the order of the following growth functions? 10n2 + 100n + 1000 10n3 – 7 2n + 100n3 n2 log n     Q5. Arrange the growth functions of Q4 in ascending order of efficiency for n=10 and again for n = 1,000,000.

There is a group of n children standing in a queue, where their ages are listed in the array A[ ]. The children are standing randomly in the queue. Most probably, their ages in the array A[ ] are randomly listed too. For each child, you are required to search for the next older childin the queue and to print the difference oftheir ages. Print all the outputs in an array Out[ ]. a) Design an efficient algorithm to solve this problem.  [The efficiency of your algorithm is the main driver of the mark], and analyze the complexity of your solution. [full explanation of your answer should be provided]b) Develop a python code to implement your efficient algorithm.  [The marks depend on the correctness of the code, indentation, comments, test-case]c) Prepare a brief report (250 words) comparing the two algorithms

Calculating the Minimum Sum Path in a Triangle (LeetCode Problem)Given a triangle array, return the minimum path sum from top to bottom. For each step, you may move toan adjacent number of the row below. More formally, if you are on index i on the current row, you maymove to either index i or index i + 1 on the next row.   public static int minSumPathMemo(int[][] triangle)This method will calculate the minimum sum path in the triangle using the top down strategy. Note thismethod MUST BE recursive and you will need to create a recursive helper method. public static int minSumPathBottomUp(int[][] triangle)This method will calculate the minimum sum path in the triangle using the bottom up strategy. Note thismethod CANNOT be recursive and you should not create any additional helper functions.   Extra Challenge: Could you do this using only O(n) extra space where n is the total number of rows in thetriangle?  This is method signature class below: package dynamic; public class MinSumPath {…

Write an efficient algorithm (to the best of your knowledge) for the following problem, briefly describe why it is a correct algorithm, and analyze the time complexity. If you cannot find any polynomial-time algorithm, then give a backtracking algorithm. Problem: Repeated Number Input: An array A[1...3n] of positive integers. Output:  If any number in the array appears at least n times, then print such a number. Otherwise, print 'none'. Example: Input: A = [1,3,3,3,1,1]. Here 3n = 6 and n =2. Output: 3. Note that here 1 would also be a valid output. You just need to print one if there are many options. Example: Input: A = [4,3,5,7,9,1]. Here 3n = 6 and n =2. Output: 'none'

Answer question number 5 please

The following algorithm adds all the entries in the “upper triangular” part of a square n × n array A. Consider n = 5 and the 5 × 5 array below. The work unit is the addition operation, sum = sum + A[k, j]. How many times is the sum = sum + A[k, j] operation done? sum = 0 for k = 1 to n do for j = k to n do sum = sum + A[k, j] end for end for 1 3 1 0 2 3 1 0 3 3 0 0 1 2 0 0 2 3 1 2 2 2 3 0 1