Answer-Which sorting algorithm is considered the most efficient for large datasets with no additional memor...

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Merge sort is a highly efficient sorting algorithm for large datasets due to its divide-and-conquer approach. It divides the array into smaller subarrays, sorts them individually, and then merges them in a sorted manner. With a time complexity of Onlog  n in all cases best, average, and worst, merge sort is highly predictable and handles large datasets efficiently. It is stable and works well for linked lists and external sorting, where data cannot fit into main memory.   Why Other Options Are Incorrect     Bubble Sort  This has a worst-case time complexity of On2 and is inefficient for large datasets.   Selection Sort  While more efficient than bubble sort, its time complexity is still On2.   Quick Sort  Quick sort has an average time complexity of Onlog  n, but in the worst case when the pivot is poorly chosen, it can degrade to On2.   Insertion Sort  This is suitable for small datasets or nearly sorted data but has a time complexity of On2 for large, unsorted datasets.

Which sorting algorithm is considered the most efficient for large datasets with no additional memory constraints?

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