Which of the following sorting algorithms can be used to sort a random linked list with minimum time complexity? a) Insertion Sort b) Quick Sort c) Heap Sort d) Merge Sort
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Which of the following sorting
a) Insertion Sort
b) Quick Sort
c) Heap Sort
d) Merge Sort
Step by step
Solved in 2 steps
- A list is sorted from smallest to largest when a sort algorithm is called. which of the following sorts would take the longest time to execute, & which would take the shortest time?a) Quick Sort, with the first element used as the split valueb) Sort Bubblec) Selection Sort d) Heap Sort e) Insertion Sortf) Merge SortBig-O Solving (PYTHON) Question: Does the choice of the pivot affect the running time of quick sort? Why or why not? It would help if you could provide examples or illustrations. Given ONLY: Quick Sort is another sorting algorithm that follows a divide-and-conquer approach. The algorithm can be summarized in 3 steps: A pivot element is chosen, usually the first element. All elements smaller than the pivot are placed to the left of the pivot. This creates 2 partitions, elements greater than the pivot and elements less than the pivot. The 2 partitions are sorted using Quick Sort. Sample code in python3: def quick_sort(arr): def quick_sort_r(arr, start, end): if end - start < 2: # single element base case return # choose a pivot pivot = start # you may choose other elements store = pivot+1 # index to store less than elements # for all elements after the pivot for i in range(pivot+1, end): if arr[i] < arr[pivot]:…Language: Python 3 Autocomplete Ready O 1 v import ast 3. Hybrid Sort input() lst %3D 3 lst = ast.literal_eval(lst) 4 Insertion sort is a simple sorting algorithm that builds the final sorted array one item at a time. In each iteration, insertion sort inserts an element into an already sorted list (on left). The position where the item will be inserted is found through linear search. You decided to improve insertion sort by using binary search to find the position p where the new insertion should take place. 6 print(BinaryInsertionSort(lst)) Algorithm BinarylnsertionSort Input/output: takes an integer array a = {a[0], ..., a[n – 1]} of size n begin BinarylnsertionSort for i =1 to n val = a[i] p = BinarySearch(a, val, 0, i – 1) for j = i-1 to p a[j + 1]= a[i] j= j-1 end for a[p] = val i i+1 end for end BinarylnsertionSort Here, val = a[i] is the current value to be inserted at each step i into the already sorted part a[0], ..., ați – 1] of the array a. The binary search along that part…
- Quick Sort is another sorting algorithm that follows a divide-and-conquer approach. The algorithm can be summarized in 3 steps: A pivot element is chosen, usually the first element. All elements smaller than the pivot are placed to the left of the pivot. This creates 2 partitions, elements greater than the pivot and elements less than the pivot. The 2 partitions are sorted using Quick Sort. Sample code in python3: def quick_sort(arr): def quick_sort_r(arr, start, end): if end - start < 2: # single element base case return # choose a pivot pivot = start # you may choose other elements store = pivot+1 # index to store less than elements # for all elements after the pivot for i in range(pivot+1, end): if arr[i] < arr[pivot]: # if element is less than pivot arr[i], arr[store] = arr[store], arr[i] # swap store += 1 # increment store index # swap pivot with last element in less than…Sort the following lists using the Bubble Sort algorithm provide Step-by-step answers? a) Original list: [5, 2, 8, 1,6] b) Original list: [8, 3, 1, 5, 4]Q6: which of the following data structure is Linear a) Single Linked List b) Double linked list c) Array d) All of them Q7: The efficiency of an algorithm is measured by a) Number of steps in an algorithm b) Time and space consumed by the algorithm c) Number of loops in the algorithm d) The kind of data structures used in the algorithm Q8: In the context of algorithms time complexity, select the best time: a) O(n) b) O(n(log(n))) c) O(log(n)) d) O(n°) Q9: Consider the code fragment: integer n = 128; while (n2 1) {do something; n=n/2; } a) The code runs in O(n) time b) The code runs in O(n?) time c) The code runs in O(log(n)) time d) The code runs in O(n(log(n))) time Q10: for an array of size 10 which sorting algorithm would you choose? a) Quick sort b) Merge sort c) Insertion sort d) None of the above
- BUBBLE SORT Sort the following list of elements using the bubble sorting algorithm. Show the passes until the list is sorted. 23 15 8 12 20 10linear search algorithm is a procedure for sorting a list array by element a procedure for sorting a list O element by element a procedure for searching a list O element by element a procedure for sorting a list array by arrayLanguage: Python 3 • Autocomplete Ready O 1 v import ast lst = input(O lst = ast.literal_eval(lst) def binarysearch(lst,x,low,high): if low - high x: 10 11 Algorithm BinarylnsertionSort 12 Input/output: takes an integer array a = {a[0], ..., a[n – 1]} of size n 13 begin BinarylnsertionSort return binarysearch (lst, x, mid, high) 14 for i =1 to n val = a[i] p = BinarySearch(a, val, 0, i – 1) for j = i-1 to p alj + 1]= a[j] j= j-1 end for 15 else: 16 return mid 17 18 def BinaryInsertionSort(lst): 19 print (BinaryInsertionSort(lst)) 20 a[p] = val j=i+1 end for end BinarylnsertionSort Here, val = a[i] is the current value to be inserted at each step i into the already sorted part a[0], ..., ați – 1] of the array a. The binary search along that part returns the position p where the val will be inserted. After finding p, the data values in the subsequent positions j = i- 1, ..., p are sequentially moved one position up to i, ..., p+1 so that the value val can be inserted into the proper…
- Module 5: Merge Sort Merge Sort works by continuously partitioning a list into two smaller sub-lists so it is working with smaller sub-lists during each recursive call. When does the Merge Sort method stop partitioning a list into sub-lists and begin returning? After four divides When each sublist has one element When each sublist is already sorted When each sublist has two elementsQ1: Sort the following array using Heap sort i.e. i. S,0,R,T,I,N,G Q 2: Sort the following using merge sort: 85, 24, 63, 45, 17, 31, 96, 50 Q 3: Write an algorithm for Quick Sort. Q 4: Find the minimum spanning tree using Kruskal's Algorithm. A 10 D 3 B 6 4 4 1 H F G 5. 3) 6, 2.A merge sort is used to sort an array of 1000 test scores in descending order. Which of the following statements is true?a) The sort is fastest if the original test scores are sorted from smallest to largestb) The sort is fastest if the original test scores are in completely sorted order.c) The sort is fastest if the original test scores are sorted from largest to smallest.d) The sort is the same, no matter what the order of the original elements.