Consider your ID as an array of 9 elements. Show and explain your steps in details to solve the following questions. (No coding skills are required here!) Example ID: 201710340 Target Value = 22.
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- ID number is k190516 these 2 questions are interlinked with eachother, I need answer of both seperately 1. Consider an array of 6 elements (keys should be your student ID). Apply quick sort steps manually and show the results at each step. 2. Consider the question that you attempted earlier in which you sorted an array with keys as your student ID. Look at your solution and see how many comparison operations your performed?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)Following is the function for interpolation search. This searching algorithm estimates the position (index) of a key in array based on the elements in the first position and last position in the array, and the length of array. The array must be sorted in ascending order. Suppose array A contains the following 15 elements: A = [1, 3, 3, 10, 17, 22, 22, 22, 24, 25, 26, 27, 27, 28, 28] At first iteration, at which position (index) the element of 24 is estimated in array A? In which part of array (starting index and ending index) the searching should continue? How many iterations the searching are performed until the element of 24 is found? int InterpolationSearch(int x[], int key, int n) { int mid, min = 0, max = n-1; while(x[min] < key && x[max] > key) { mid = min + ((key-x[min])*(max-min)) / (x[max]-x[min]); if(x[mid] < key) min = mid + 1; else if(x[mid] > key) max = mid - 1; else return mid; } if…
- True or False For each statement below, indicate whether you think it is True or False 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)True or False For each statement below, indicate whether you think it is True or False. If you like, you can provide a description of your answer. 1) If you use binary search on a sorted array, the performance at worst is O(log n) 2) For the insert algorithm, if you use binary search to find the location to insert the new element, it will improve the overall performance of the algorithm to O(log n) 3) For the update algorithm in a sorted array, all you have to do is use linear or binary search to find the element you want to change, and if you find it, you only need to change it to the new value 4) Binary search can be used on an unsorted arrayTrue or False For each statement below, indicate whether you think it is True or False. If you use binary search on a sorted array, the performance at worst is O(log n) For the insert algorithm, if you use binary search to find the location to insert the new element, it will improve the overall performance of the algorithm to O(log n) For the update algorithm in a sorted array, all you have to do is use linear or binary search to find the element you want to change, and if you find it, you only need to change it to the new value Binary search can be used on an unsorted array Inserting elements into a sorted array is O(n) because you have to find the location to add the new element and then shift the remaining elements If the sorted array gets too large, the performance of binary search becomes O(n) For the delete algorithm, after you find the element to delete, you can make the algorithm run faster by replacing it with the last element in the array If you used binary search to…
- 1a) Insertion sort is chosen to sort this array, write the contents of the array each time that the sort algorithm changes it. How many comparison operations and how many swaps are performed in the sorting? b) Usually, one swap operation equals seven comparison operations in terms of their executing time. By comparing the number of swap and comparison operations of each of the above sort algorithms, which of these sort methods is most efficient in sorting this array?Below is your exercise for Basic Sorts. For submitting your answers, you can either send me an updated Word document with your answers, email your answers directly, or even take a screen shot of your work on paper if you like. In all cases, email me your answers when you feel ready. Use the following array of numbers for each of the sorting tasks below: 6 2 8 1 7 5 3 4 Bubble Sort (not optimized) – show what the array looks like each time the swap operation is performedusing the bubble sort algorithm (not optimized, meaning no use of swapFlag) Selection Sort - show what the array looks like each time the swap operation is performed using the selection sort algorithm Insertion Sort – show what the array looks like at the end of each outer loop iteration of the insertion sort algorithmDo it as a c ++ please and explain each step Sort an array of 10,000 elements using the quick sort algorithm as follows:a. Sort the array using pivot as the middle element of the array.b. Sort the array using pivot as the median of the first, last, andmiddle elements of the array.c. Sort the array using pivot as the middle element of the array. However, when the size of any sublist reduces to less than 20, sort the sublistusing an insertion sort.d. Sort the array using pivot as the median of the first, last, andmiddle elements of the array. When the size of any sublist reduces toless than 20, sort the sublist using an insertion sort.e. Calculate and print the CPU time for each of the preceding four steps.
- Below is how the arrays are represented ARRAY1[] = [1, 5, 6, 6, 9, 9, 9, 11, 11, 21] Here length of ARRAY1 is m. ARRAY2[] = [6, 6, 9, 11, 21, 21, 21] Here length of ARRAY2 is n. Array to be returned would be: ARRAY[] = [6, 9, 11, 21] ATTN : Further, please be reminded that you cannot use library functions to either sort and or perform the de-duplication operation. solve the problem in two ways In a separate implementation, code up a solution in such a way that your solution solves the problem with O(nlog(m)) time complexity 2 or O(mlog(n)) time complexity. Here log means to the base of 2. I’m sure you already know that the hint is to use Binary Search. In the form of sentences, as a comment in your code (at the bottom of your Solution2), you are required to suggest how can Solution2 be improved by leveraging the fact that both the arrays are already sorted. Suggest a solution so that your suggested solution can run linearly with O(m + n) time complexity. Your suggestion should be no…Consider a name in capital letters for example, Bill Gates. Apply Merge Sort on complete name. You are required to elaborate each sub array that are created during the dry run process. With best visualization possible.H3. Let S = [x1, x2, x3, ...xn], where n ≥ 5. How many ways can you choose five of the values in the array S, given that x1 = x2 = x3 and all other xi are distinct? The order of the chosen elements does not matter