In the worst case scenario, we will have n elements to be compared and this will take n number of iterations
Leading to a complexity of n^2 as n*n comparisons will be made in the worst case due to execution of 2 loops
So, correct ans is option A
In the worst case, the very best that a comparison based sorting algorithm can do when...
In the worst case, the very best that a comparison based sorting algorithm can do when sorting n records is 2 (n^2) (log (n!)) (logn) (n)
not A Question 5 In the worst case, the very best that a comparison based sorting algorithm can do when sorting n records is Q (n^2) Q(log (n!)) Q (logn) (n)
Canvas →XC 6 D Question 10 5 pts When sorting n records, Quicksort has worst-case cost On) On 2) On logn) Olm Question 11 5 pts In the worst case, the very best that a comparison based sorting algorithm can do when sorting n records is On 2) Allog in! (n) (login) Question 12 5 pts An AVL tree is a Binary Search Tree that has the following additional property none of the above for every node in the tree....
When sorting n records, Merge sort has worst-case running time a. O(n log n) b. O(n) c. O(log n) d. O(n^2)
When sorting n records, Merge Sort has worst-case running time O(log n) O O(n log n) O O(n) O(n^2)
Find the best case, worst case and average case complexity for numbers of comparison and assignment operations for the following code. Indicate when there is no best or worst case. Comparisons Assignments Given 2-D array of integer map[n][n]: Best: Best: worst: worst: for (i0; 1 <n; i++) for(j = 0j <n; j++) If (map 10] < 0) map[001-mapli01: average: average: For ease of analysis, assume half of the elements in map are negative.
Give an algorithm with the following properties. • Worst case running time of O(n 2 log(n)). • Average running time of Θ(n). • Best case running time of Ω(1).
Data Structures: For each of the following situations, name the best sorting algorithm we studied. (For one or two questions, there may be more than one answer deserving full credit, but you only need to give one answer for each.) (a) The array is mostly sorted already (a few elements are in the wrong place). (b) You need an O(n log n) sort even in the worst case and you cannot use any extra space except for a few local...
The worst-case complexity of the Quicksort is O(n2). (a) Use the selection algorithm to modify Quicksort and reduce its worst-case complexity to O( n*log(n) ) (b) Write the recurrence equation for the modified Quicksort algorithm.
(5 marks; questions to Reza) In Lecture 5, Travis said you can prove QuickSort takes N(n log n) time in the best case the same way he proved any comparison-based sorting algorithm takes (n log n) time in the worst case. Give that proof. Notice it doesn't follow directly: e.g., Insertion Sort takes O(n) time in the best case. You can assume QuickSort divides each array into elements less than or equal to the pivot (including the pivot itself) and...