I was spending a lot of time lately thinking about how I can improve my program’s sorting performance a little bit more. I was thinking:

最近，我花了很多时间思考如何才能提高程序的排序性能。 我刚在想：

“Hey, there are sorting algorithms that have proven themselves well and that everyone knows, but there must be something we all are missing, maybe?”

“ 嘿，有一些排序算法已经很好地证明了自己，并且每个人都知道，但是一定有我们所有人都缺少的东西，也许吗？ ”

Well, I found something and I wasn’t wrong. There was something that we didn’t know much about, though it wasn’t exactly what I was looking for.

好吧，我发现了一些东西，但我没看错。 尽管我并不是真正想要的东西，但我们并没有太多了解。

I found a really slow sorting algorithm called Monkey Sort aka Bogosort.

我发现了一种非常慢的 排序算法，称为Monkey Sort aka Bogosort。

Monkey Sort is based on Infinite Monkey Theorem:

猴子排序基于无限猴子定理：

The infinite monkey theorem is a popular demonstration of the mathematical probability, stating a monkey hitting keys at random on a typewriter keyboard, given enough time and typewriters, will eventually reproduce the entire works of William Shakespeare.

无限猴子定理 是数学概率的流行示例，它说明猴子在打字机键盘上随机敲击键， 有足够的时间 和打字机，最终将重现威廉·莎士比亚的全部作品。

From Wikipedia:

从维基百科：

while not isInOrder(deck):    shuffle(deck)

Algorithm implemented in Java:

用Java实现的算法：

import static java.util.Collections.shuffle;public List<Integer> monkeySort(List<Integer> list) {    while (!list.equals(sortedList)) {        shuffle(list);    }    return list;}

We are shuffling the list until it’s sorted.

我们正在整理列表，直到对其进行排序。

Best scenario is O(N), if the list is already sorted. It’s not O(1) because it will take O(N) to find out the list is sorted.

如果列表已经排序， 最好的情况是O(N)。 它不是O(1)，因为它需要O(N)才能找到已排序的列表。

Worst scenario is O(∞) since this algorithm has no upper bound. But hey, even though it has no upper bound, it’s finite! We know it can’t be infinite from the infinite monkey theorem. We’ll get the result eventually. :)

最糟糕的情况是 O(∞)，因为此算法没有上限。 乙 UT斯达康哎，即使它没有上限， 它的有限的！ 宽 E知道它不能从无限猴子定理是无限的。 我们最终会得到结果。 :)

Thank you for reading! ❤️

感谢您的阅读！ ❤️