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frotaur • today at 3:49 AM • 2 replies • view on HN

I think you are free not to care about what they are doing. It turns out that big O notation has some useful properties, and in particular it is a useful definition as it allows you to define complexity classes which are a very useful tool for analyzing algorithms in general.

Much of our 'practical' understanding of algorithms also in part came from theoretical advances.


Replies

burpingtree • today at 5:54 AM

The argument in the article isn’t about whether big O notation is useful it’s about whether the n in any particular big O is relevant. In this case the algorithm’s claim is that you can multiply arbitrarily large numbers faster than n log n where n is the size of the numbers being multiplied. But that result holds only if you don’t include the cost to multiple arbitrarily large complex numbers in that n, which are assumed to be able to multiply in constant time.

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adastra22 • today at 4:05 AM

That’s sloppy reasoning. There might be notations that allow for classifying complexity classes that don’t suffer this problem.

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