And the obvious question I could start with is, and suppose I ask you, how long does the algorithm implemented by this program take to run?

我开始这个话题的第一个问题是，假设我问你，由这个算法实现的程序大概,要运行多久才能给出答案？

麻省理工公开课 - 计算机科学及编程导论课程节选

So, the curious thing about recursion is that pretty much always can you implement this idea of doing the same thing again and again and again but with smaller bytes each time.

可见，递归算法中新奇的一点是,为了实现一个想法,你可以一遍又一遍地做相同的事情,但每次的规模都会有所减小。

哈佛公开课 - 计算机科学课程节选

Because if you did what I suggested with the list, the time to look up the key would be linear in the length of the list. You'd have to look at each element until you found the key.

字典是用一种很神奇的，叫做散列法的算法,来实现的，后面我们将,会学到一点关于。

麻省理工公开课 - 计算机科学及编程导论课程节选

Alright, so we can implement any number of algorithms using this thing because the basic mechanism I have here is a comparator.

好了，利用它我们可以实现,很多种算法,因为在此我用到的基本原理是一个比较器。

哈佛公开课 - 计算机科学课程节选

And so one of the things we'll look at today is how can we leverage an algorithm, how can we implement an algorithm that at least at first glance the second time we've now seen it feels so obviously better.

因此，今天我们要学习的一点就是,我们怎样才能影响一个算法，怎样实现一个算法,使你在第二次看它时会觉得,至少比你第一次看到它时更好。

哈佛公开课 - 计算机科学课程节选

And yeah, I know it comes built in, that's OK, what we want to do is use it as an example to look at it.

对，我知道这个方法可以通过内置的算法，来实现，这没关系，我们只是,把它当做一个例子来讲解。

麻省理工公开课 - 计算机科学及编程导论课程节选

Well, we saw the teaser in terms of that animation that suggests this merge sort algorithm when implemented by a computer is absolutely faster.

我们从前面的动画中可以看到,这个归并排序算法在计算机上实现之后,绝对比其他算法更快。

哈佛公开课 - 计算机科学课程节选

N But it's definitely not one and in fact it wasn't N in the case of Selection Sort because remember the algorithm we implemented on stage last week had me going back and forth across the stage selecting on iteration, the smallest person I can find, the smallest number and then putting them into place.

但在选择排序中，肯定不会是1，也不是,注意，上周我们在这儿,实现的算法中，反复地,迭代进行选择，选出最小的数,然后将其放在合适的位置。

哈佛公开课 - 计算机科学课程节选