Merge sort has o (n log n) worst-case and average-case performance.
合并排序的最差性能和平均性能为o (n log n)。
So I have n operations log n times, n log n there we go, n log n. Took us a long time to get there, but it's a nice algorithm to have.
所以我log,n遍的n次操作,就得到了,虽然花了不少时间得到了这个结论。
As I mentioned in the overview section, random character access on a rope with many internal nodes is approximately o (log n), so traversal is o (n log n).
就像我在概述一节中提到过的,在拥有许多内部节点的rope上随机访问字符的时间大约为o (log n),所以遍历时间为o (nlog n)。
It at least does corroborate the claim that merge sort N*log N as we argue intuitively is in fact, N log N in running time.
但这至少证实了归并排序,的时间复杂度为。
Boy, there's a dumb question, because I've been telling you n log n for the last two lectures the complexity is n log n, but let's see if it really is.
孩子们,这是一个愚蠢的问题,因为前两节课的时候我就已经告诉你们了,复杂度是,但是让我们来看一下是不是真的是这样。
N log N is not nearly as good as log N. As a sanity check, what algorithm have we seen that runs in log N time?
而N,log,N和log,N并不一样,我们之前探讨过的哪个算法其时间复杂度是log,N呢?
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