All right? And I'm going to say-- sort of set that stage here, so that-- It turns out that that's probably about the best we can do, or again ends at the length of the list.

我要说的是，这一阶段的集合,我们用最优的方法完成,还是取决于列表的长度，好的，还是回到了我的问题上了。

麻省理工公开课 - 计算机科学及编程导论课程节选

This lets me have a way of representing things that could be arbitrary in size. And some of these things could be huge, if they're themselves lists.

有些可能很大，如,果他们本身就是列表,那问题来了。

麻省理工公开课 - 计算机科学及编程导论课程节选

We don't seem to be doing that just yet, certainly not as badly, alright, so at this point in the story I have a sorted list of size 4.

当然现在我们不需要那样做,此时此刻,我已对整个问题中大小为4的列表排好序了。

哈佛公开课 - 计算机科学课程节选

Well let's see. My fall back is, I could just do linear search, walk down the list one at a time, just comparing those things. OK. So that's sort of my base. But what if I wanted, you know, how do I want to get to that sorted list? All right?

我只能做线性搜索了,一次遍历一遍列表，一个一个比较，但如果我想要,那怎样得到有序的列表呢？,现在的一个问题是，我们排序之前？

麻省理工公开课 - 计算机科学及编程导论课程节选

The second question I want to ask is what's the base case? When do I get down to a problem that's small enough that it's basically trivial to solve? Here it was lists of size one. I could have stopped at lists of size two right. That's an easy comparison.

第二个问题是什么是基础条件？,我要将问题分解到何时才使得问题,小到可以解决的基本问题？,这里是当列表的长度为1有时候,我也可以在长度为2的时候停止分解,那是一个非常简单的对比。

麻省理工公开课 - 计算机科学及编程导论课程节选