Statistically both MergeSort and QuickSort have the same average case time: O(nlog(n)); However there are various differences.
Most implementations of Mergesort, require additional scratch space, which could bash the performance. The pros of Mergesort are: it is a stable sort, and there is no worst-case scenario.
Quicksort is often implemented inplace thus saving the performance and memory by not creating extra storage space. However the performance falls on already sorted/almost sorted lists if the pivot is not randomized.
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Comolexity Not efficent big data
types of sorting in c language are: insertion sort selection sort bubble sort merge sort two way merge sort heap sort quick sort
Never. Bubble sort is often cited as an example of how not to write a sorting algorithm and is used purely as a programming exercise. It is never used in production code. Although reasonably efficient when sorting small lists, an insertion sort performs better on average. But for larger lists it has no practical uses. A merge sort is better for large lists, but if stability isn't an issue a quick sort is even better. Hybrid sorts typically use quick sort until a partition is small enough for an insertion sort to complete the job.
There is no key element in a merge sort. Unlike quick sort which requires a key element (a pivot) to recursively divide a subset into two subsets, merge sort simply divides a subset into subsets of 1 element and merges adjacent subsets together to produce sorted subsets. When there is only one subset remaining, the subset is fully sorted.
quicksort should be O(n^2), but merge sort should be O(nlogn). but if you can modify partition algorithm with checking all values same in array from p to r, it could be O(nlogn).
it has less complexity
Comolexity Not efficent big data
types of sorting in c language are: insertion sort selection sort bubble sort merge sort two way merge sort heap sort quick sort
insertion,bubble,quick, quick3, merge, shell,heap, selection sorting
Insertion sort is better than merge sort in terms of efficiency and performance when sorting small arrays or lists with a limited number of elements. Insertion sort has a lower overhead and performs better on small datasets due to its simplicity and lower time complexity.
Never. Bubble sort is often cited as an example of how not to write a sorting algorithm and is used purely as a programming exercise. It is never used in production code. Although reasonably efficient when sorting small lists, an insertion sort performs better on average. But for larger lists it has no practical uses. A merge sort is better for large lists, but if stability isn't an issue a quick sort is even better. Hybrid sorts typically use quick sort until a partition is small enough for an insertion sort to complete the job.
There is no key element in a merge sort. Unlike quick sort which requires a key element (a pivot) to recursively divide a subset into two subsets, merge sort simply divides a subset into subsets of 1 element and merges adjacent subsets together to produce sorted subsets. When there is only one subset remaining, the subset is fully sorted.
quicksort should be O(n^2), but merge sort should be O(nlogn). but if you can modify partition algorithm with checking all values same in array from p to r, it could be O(nlogn).
Quick sort runs the loop from the start to the end everytime it finds a large value or a small value while in merge sort starts from the first position of the array and assembles the large or small numbers in one side in just one loop so its more faster than quick sort
Merge sort is good for large data sets, while insertion sort is good for small data sets.
The reason we have so many sorting techniques is that there is no "best." Depending on circumstances, your best bet will usually be either quick sort or merge sort.
Because the quick sort can be used for large lists but selection not. selection sort is used to find the minimum element ,but quick choose element called pivot and move all smaller nums before it & larger after it.