The space complexity of Merge Sort is O(n), where "n" is the number of elements in the array being sorted. Merge Sort has a linear space complexity because it requires additional space for the merging process and the temporary storage of subarrays during the recursion.
The primary factor contributing to the space complexity is the need for auxiliary arrays during the merge step. In the merging process, two sorted subarrays are combined into a single sorted subarray, and an auxiliary array is used to temporarily store the merged result. This temporary storage is essential to maintain the order of elements during the merging process.
The maximum amount of additional space required is proportional to the size of the input array. In the worst case, when the merging process is performed at each level of recursion, the total space required is O(n). This space complexity is a consideration in scenarios where memory usage is critical.
It's important to note that Merge Sort is a stable sorting algorithm, meaning it preserves the relative order of equal elements. This stability, along with its consistent O(n log n) time complexity, makes Merge Sort a popular choice in various applications, especially when the additional space usage is acceptable.
