Definition of the merge sort algorithm
merge sort is an efficient algorithm, and one of Divide and Conquer algorithms that splits the giving array into two halves, and then merge them in a sorted manner.
Time complexity of merge sort
| best-case | average case | worst-case |
|---|---|---|
| O(n log n) | O(n log n) | O(n log n) |
Space complexity
The space complexity of merge sort is O(n)
Advantages of using merge sort algorithm
- Fast for large arrays unlike selection, insertion, and bubble sort it doesn't go through the whole array many times.
Disadvantages of using merge sort algorithm
- extra space to store subarrays
- slow for small arrays
- the algorithm does the whole process even the array is already sorted
Implementation of merge sort using python
def MergeSortAlgorithm(arr: list) -> list: """ [ name ] => merge sort [ type ] => sorting algorithms [ time complexity ] => O(n log n) [ space complexity ] => O(n) [ params ] => ( arr {list} list to sort ) """ n = len(arr) if n > 1: #getting the middle of the giving array mid = n // 2 # left half leftHalf = arr[:mid] # right half rightHalf = arr[mid:] # sort left half MergeSortAlgorithm(leftHalf) # sort right half MergeSortAlgorithm(rightHalf) i = k = j = 0 while i < len(leftHalf) and j < len(rightHalf): if leftHalf[i] > rightHalf[j]: arr[k] = rightHalf[j] j+=1 else: arr[k] = leftHalf[i] i+=1 k+=1 # inserting to the sortedArray the rest of the leftHalf while i < len(leftHalf): arr[k] = leftHalf[i] k += 1 i+=1 # inserting to the sortedArray the rest of the rightHalf while j < len(rightHalf): arr[k] = rightHalf[j] k+=1 j+=1 References and useful resources
- https://getrevising.co.uk/grids/merge-sort-advantages-and-disadvantages
- https://www.tutorialspoint.com/data_structures_algorithms/merge_sort_algorithm.htm
- https://www.geeksforgeeks.org/merge-sort/
- https://www.interviewbit.com/tutorial/merge-sort-algorithm/#:~:text=Merge%20sort%20is%20one%20of,results%20into%20a%20sorted%20list.
Thank you so much for your time! :)
#day_11
Top comments (0)