And that's just a way of reminding you that we want to think carefully, but what are the things we're trying to measure when we talk about complexity here? It's both the size of the thing and how often are we going to use it? And there are some trade offs, but I still haven't said how I'm going to get an n log n sorting algorithm, and that's what I want to do today.

这只是在提醒你们我们要仔细的思考问题,但是当我们在讨论复杂性的时候,我们到底要衡量哪些东西？,是列表的大小和对其进行查找的频率吗？,这里面临一些取舍,但是我还没有说明,怎样得到一个n，log，n复杂度的排序算法,并且这是我今天想要讲的内容。

麻省理工公开课 - 计算机科学及编程导论课程节选

And so the fact that in this whole slide here, this algorithm for sorting, I'm using the verb sort.

在这个排序算法中,我用到了一个动词排序。

哈佛公开课 - 计算机科学课程节选

Well, you need an algorithm for sorting.

你需要一种排序算法。

哈佛公开课 - 计算机科学课程节选

So I propose this as a new algorithm for sorting N elements and being 8 in this case or really a thousand in the case of the phonebook, or anything of larger size.

所以我提出一种新的算法，来解决N个元素的排序问题,在这个问题中N是8，在电话簿的问题中N是一千,或者是大规模的任何问题。

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