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。

哈佛公开课 - 计算机科学课程节选

I ask you for the running time of this algorithm and you give me the running time in terms of the running time, right.

我需要得到此算法的时间复杂度,那就明确地给出其,运行时间。

哈佛公开课 - 计算机科学课程节选

And this was just a formal way of describing the best case running time and in the case of Selection Sort, what was the best case running time?

这是描述最好情况下运行时间的,一种正式的方式,在选择排序中，最理想的运行时间是多少呢？

哈佛公开课 - 计算机科学课程节选

So supposed that I give you 16 elements to sort, well, following the logic before, the running time involved in sorting 16 elements is gonna be twice the running time 16 of sorting 8 elements, left half and right half plus 16 - and again, a little sanity check, 16 means-- just the merge steps, right?

现在要对16个元素进行排序，根据之前的逻辑，对16个元素排序,要花的时间是对8个元素排序所花时间的,2倍，分别用于左半部分和右半部分，再加上6,这里16是-,做合并的步数，对吗？

哈佛公开课 - 计算机科学课程节选

If I'm using algorithm that I'm now calling merge sort, T the running time involved in sorting N elements, T of N, you know, is just the same as running the algorithm for the right half, plus what's this plus N come from?

如果我用归并排序算法，对N个元素其运行时间，就等于此算法一半元素的运行时间,另一半的运行时间，再加上N，这个N是什么呢？

哈佛公开课 - 计算机科学课程节选