Select true or false for the statements below. Explain your answers if you like to receive
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Select true or false for the statements below. Explain your answers if you like to receive
partial credit
6) Given an array [10 9 8 7 6 5 4 3 2 1], which of the following is true of the following
sorting
a. If we used optimized bubble sort on this array, the performance is O(n)
b. If we used MergeSort on this array, the performance is O(n log n)
c. If we used InsertionSort on this array, the performance is near O(n)
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- Select true or false for the statements below. Explain your answers if you like to receive partial credit2) Which of the following is true about searching elements in an ordered array?a. You cannot use binary search on an ordered array so the performance is O(n)b. If there are no holes in the array and the elements are all next to each other,then the performance for search improves to O(1)c. If you do a linear search on a sorted array, the performance improves toO(log n)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)Select true or false for the statements below. Explain your answers if you like to receive partial credit 9) Which of the following is true about the Mergesort algorithm applied to an array ofnumbers that are all different?a. Memory usage is efficient because all swaps take place within the same arrayb. Performance is consistently at O(n log n) for all array scenariosc. When the partition function completes on the array, the pivot element willalways be in the exact center of the array
- You are given 4 items as (value, weightpairs in this format {{20, 5), (60, 20), (25, 10), (X, 25}}You can assume that the array is sorted based on the ratio. The capacity of knapsack is 50. The item no. 4 (whose weights 25) is taken fractionally to fill upto the knapsack capacity. That fraction is represented in format. What is the lowest possible value of ? weightSelect true or false for the statements below. Explain your answers if you like to receive partial credit 5) Which of the following is true about using the binary search algorithm in a sortedarray with no holes and always keeping the order of the array intact?a. Binary search improves the performance of delete to O(log n)b. Binary search improves the performance of update to O(log n)c. Binary search improves the performance of search to O(log n)Develop an implementation of insertion sortthat moves larger elements to the right one position with one array access per entry,rather than using exch(). Use SortCompare to evaluate the effectiveness of doing so.Develop an implementation of insertion sortthat moves larger elements to the right one position with one array access per entry,rather than using exch(). Use SortCompare to evaluate the effectiveness of doing so.
- Given the following array of numbers: 8 2 3 9 10 1 4 6 7 5 Show what the array looks like after each iteration of the following sorting algorithms: Bubble Selection Insertion Mergesort Only show the array contents with each algorithm. You do not need to show function call instances if recursion is used or write any code. Just show the array at key iterations of the algorithm. You can use your own words to describe them as well for more detail (but do not write any code). Show what the array looks like after each recursive iteration of the Quicksort algorithm.Please help me with this: using js create an array of 30 random numbers that range between 1and 100. And yet again, write a function that will receive a number from the userand determine if that number exists in the array or not. But this time, start bySORTING your input list. After a sort, the list in problem 1 is as follows:[2, 2, 3, 5, 12, 14, 14, 15, 23, 36, 39, 41, 44, 44, 45, 48,49, 50, 52, 52, 59, 71, 81, 82, 88, 89, 89, 93, 96, 97] Approach: Implement a method called findC(x, A, i, j), where x is the number we arelooking for in array A, the first index of the array is i and the last index is j. We wantto determine whether x exists in A anywhere between index i and index j. Your firstcall to this method will therefore look like this: findC(x, A, 0, A.length-1). In the body of your function, compare x with the item that is in the middle of thearray, as you did before. As before, call the middle of index of the array mid. But thistime, if x<=a[mid], recursively call your…How many times does a binary search need to execute to find its value? Recall from our lesson that the number of iterations is roughly a log base 2 relationship. In this exercise, you are going to calculate the maximum iterations and the actual iterations needed to find a random value in arrays of size 100, 1000, 10k, and 100k. You are given helper methods to calculate the maximum iterations, generate the random array, and do the binary search. You are also given a counter variable that increments up each time your recursive binary method is called. You will need to come up with the remainder of the code. Same output is provided below. Sample Output Array Size: 100 Max iterations: 7 Actual iterations: 5 Array Size: 1000 Max iterations: 10 Actual iterations: 5 import java.util.*; public class BinarySearchTest { static int count; public static void main(String[] args) {// Use the helper code to generate arrays, calculate the max// iterations, and then find the actual iterations for a…
- Rewrite this code, using modular programming style, and correcting any errors if necessary. 2. Optimize the algorithm by making the following modifications: (a) After the first pass, the largest number is guaranteed to be in the highest- numbered element in the array; after the second pass, the two highest numbers are "in place," and so on. Instead of comparing every pair on every pass, modify the algorithm to make as few comparisons as necessary on each pass. (b) Modify the algorithm to check at the end of each pass if any swaps have been made. If none have been made, the data must already be in the proper order, so the program should terminate. Observe the single-exit point rule when making this modification. 3. Insert appropriate statements in your code to output the state of the array after every pass. #include <iostream> #include <iomanip> using namespace std; using std::setw; using std::cout; using std::endl; using std::size_t; int main() { const short…can you solve this please ? Given an array of unsorted integers, you are requested to investigate whether there exist a pair of numbers in this array that has a sum equal to a given key or not. For example, if the arr = [8, 7, 2, 5, 3] and the key = 12, the answer will be "Yes" as the array has a pair (7 and 5) where their sum = 12 = key, otherwise "No" is returned. To solve this problem, the following idea can be used: i. Consider every pair in the given array and check if their sum = key. ii. Sort the array first, keeping two pointers to on the minimum and maximum of the array and then move from both directions toward the center of the array while checking whether the sum = key or not. Answer the following questions: a) Transform each of the above ideas (i) & (ii) into algorithm (pseudocode) and compute their complexities b) Critic these two ideas: [Which is better? Why?] c) Design a better solution with less complexity. [note: your idea should be…True or False For each statement below, indicate whether you think it is True or False 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 Binary search can be used on an unsorted array to significantly improve its performance from O(n) to O(1) Because the update algorithm depends on using linear search, its performance is O(1) in the worst case scenario 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) 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)