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Best case for insertion sort is O(n), where the array is already sorted. The worst case, where the array is completely reversed, is O(n*n).
On average merge sort is more efficient however insertion sort could potentially be faster. As a result it depends how close to reverse order the data is. If it is likely to be mostly sorted, insertion sort is faster, if not, merge sort is faster.
There is no worst case for merge sort. Each sort takes the same amount of steps, so the worst case is equal to the average case and best case. In each case it has a complexity of O( N * log(N) ).
Merge sort is good for large data sets, while insertion sort is good for small data sets.
the main reason is: Merge sort is non-adoptive while insertion sort is adoptive the main reason is: Merge sort is non-adoptive while insertion sort is adoptive
using doublelinked list insertion sort in c language
Ɵ(nlogn)
Explain and illustrate insertion sort algorithm to short a list of n numburs
You copy the list, while using an insertion sort criteria.
Best case: 2 Worst case: 3 Average: 2+2/3
Merge sort is O(n log n) for both best case and average case scenarios.
There are no records of when insertion sort was invented because people have been sorting things using the insertion sort and selection sort algorithms since before records began; they are ancient algorithms. You cannot be credited for creating an algorithm that already exists. Shell sort, which is a refinement of insertion sort, was developed much later, in 1959 by Donald Shell. His algorithm can be credited because it takes advantage of a computer's processing abilities, whereas insertion sort and selection sort rely purely on a human's processing abilities.