爲什麼快速排序在數組的情況下比歸併排序快

快速排序和歸併排序的時間複雜度都是O(N lgN)，但是CLRS說了，實踐證明快速排序的速度比歸併排序的速度更快，爲什麼呢?另外其實這個結論是有限制範圍的，當對數組進行排序的時候，這個結論適用。爲什麼對於鏈表，卻是歸併排序的速度優於快速排序呢？這裏看到的一段對比說得挺好，直接抄過來。

One of the main sources of efficiency in quicksort is locality of reference, where the computer hardware is optimized so that accessing memory locations that are near one another tends to be faster than accessing memory locations scattered throughout memory. The partitioning step in quicksort typically has excellent locality, since it accesses consecutive array elements near the front and the back. As a result, quicksort tends to perform much better than other sorting algorithms like heapsort even though it often does roughly the same number of comparisons and swaps, since in the case of heapsort the accesses are more scattered.

Additionally, quicksort is typically much faster than other sorting algorithms because it operates in-place, without needing to create any auxiliary arrays to hold temporary values. Compared to something like merge sort, this can be a huge advantage because the time required to allocate and deallocate the auxiliary arrays can be noticeable. Operating in-place also improves quicksort's locality.

When working with linked lists, neither of these advantages necessarily applies. Because linked list cells are often scattered throughout memory, there is no locality bonus to accessing adjacent linked list cells. Consequently, one of quicksort's huge performance advantages is eaten up. Similarly, the benefits of working in-place no longer apply, since merge sort's linked list algorithm doesn't need any extra auxiliary storage space.

That said, quicksort is still very fast on linked lists. Merge sort just tends to be faster because it more evenly splits the lists in half and does less work per iteration to do a merge than to do the partitioning step.