Sorting algorithms arrange elements in order. Comparison-based sorts such as merge sort, quicksort, and heapsort run in O(n log n), while non-comparison sorts like counting and radix sort can reach linear time on bounded keys.
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Sorting algorithms arrange elements in order. Comparison-based sorts such as merge sort, quicksort, and heapsort run in O(n log n), while non-comparison sorts like counting and radix sort can reach linear time on bounded keys.
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A stable divide-and-conquer sort with guaranteed O(n log n) time and O(n) extra space.
Partitions around a pivot for fast average O(n log n) time in place, but O(n squared) in the worst case without good pivots.
Interviews often ask whether a sort is stable and how much extra memory it needs.
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Quicksort is often fastest in practice for in-memory arrays, while merge sort guarantees O(n log n) and stability.
A stable sort keeps equal elements in their original relative order, which matters when sorting by multiple keys.
