Скачать или смотреть Merge Sort Algorithm _ Data Structure

Merge Sort is a stable, comparison-based sorting algorithm that uses the divide-and-conquer approach. It is known for its efficiency, especially with larger datasets, due to its predictable time complexity of O(nlog⁡n)O(nlogn).
Steps of the Merge Sort Algorithm

Divide the Array:
The input array is divided into two halves until each subarray contains only one element (a single-element array is inherently sorted).

Merge Step:
The sorted subarrays are combined (or merged) to produce a sorted array. This merging process ensures that the final array is sorted.

Recursive Process:
The divide and merge steps are performed recursively until the entire array is sorted.

Key Features

Stable Sorting: The relative order of equal elements is preserved.
Not In-Place: Requires additional memory for temporary arrays during the merging process.
Divide-and-Conquer: The algorithm repeatedly splits and combines smaller subproblems to solve the overall sorting problem.
Time Complexity

Best Case: O(nlog⁡n)O(nlogn) (Efficient for uniformly distributed data.)
Worst Case: O(nlog⁡n)O(nlogn) (Same for all cases due to the recursive structure.)
Average Case: O(nlog⁡n)O(nlogn)

Space Complexity

Requires O(n)O(n) additional space for temporary arrays during the merge process.

Applications

Preferred for sorting linked lists due to efficient merging without needing index-based access.
Used in external sorting where the data is too large to fit into memory, as it works well with sequential data access.