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In fact, better than that, this guy is already sorted as well because I whittled that problem down to size 1.
事实上，更好的结果是这个杯子也是有序的了,因为我已将这个问题的规模削减到只有1个元素。
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A log algorithm typically is one where you cut the size of the problem down by some multiplicative factor.
对数级复杂度的算法就是指,通过一系列常量级步数的操作,可以将问题的规模。
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When you're quadrupling in size in terms of people, there's always a tendency.
当公司需要将员工规模扩大为四倍时，许多公司会降低标准，但马克不会心慈手软。
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We took the problem of size a thousand, we divided it in half.
当我们遇到一个规模为一千左右的问题时，会将其分为两部分。
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Linear algorithms tend to be things where, at one pass-through, you reduce the problem by a constant amount by one. If you reduce it by two, 1 it's going to be the same thing.
有问题么？,线性复杂度的算法，当进行了一个,常量级步数的操作的时候，将问题的规模缩小了一个。
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bug What I typically do is I start with the input that provoked the problem, and I keep making it smaller and smaller.
我这里做的就是从引起,出现的输入开始，然后将输入，一步步的缩小规模。
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What we really want to worry about is, as the size of the problem gets larger, how does this thing grow? How does the cost go up?
随着问题规模的变大，解决问题花费的代价是怎么增长的,因此我们将会主要地讲讲？
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The printout is simply telling me, what are the ranges of the search.
你可以看到这个方法每次都将，原问题的规模缩小了一半。
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But in one step, I've reduced this problem in half.
我就将这个问题的规模减半了，我不仅仅是缩小了问题的规模。
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If I'm running at nanosecond speed, 1000 n, the size of the problem, whatever it is, is 1000, and I've got a log algorithm, it takes 10 nanoseconds to complete.
如果这个问题的规模，也就是n，是，如果这个问题是对数级的，这将会占据10纳秒的时间，你一眨眼的时间。
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