[someplaceguy]

> Ultimately when an algorithm has worse complexity than another it might still be faster up to a certain point.

Sure, but the author didn't argue that the simpler algorithm would be faster for 5 items, which would indeed make sense.

Instead, the author argued that it's OK to use the simpler algorithm for less than 5 items because 5 is a constant and therefore the simpler algorithm runs in constant time, hence my point that you could use the same argument to say that 2^140 (or 2^256) could just as well be used as the cut-off point and similarly argue that the simpler algorithm runs in constant time for all arrays than can be represented on a real-world computer, therefore obviating the need for the more complex algorithm (which obviously makes no sense).

[thrw2486776]

If you set n=2^140, then sure, it’s constant. If instead you only have n<=2^140, then n varies across a large set and is practically indistinguishable from n<=infinity (since we get into the territory of the number of atoms in the universe), therefore you can perform limit calculations on it, in particular big O stuff.

In the article n was set to 5. All of those arrays (except maybe 1) have exactly 5 elements. There is no variance (and even if there was, it would be tiny, there is no point in talking about limits of 5-element sequences).

[someplaceguy]

> In the article n was set to 5. All of those arrays (except maybe 1) have exactly 5 elements. There is no variance

No, the code was:

    # If there are < 5 items, just return the median
    if len(l) < 5:
        return nlogn_median(l)

> and even if there was, it would be tiny, there is no point in talking about limits of 5-element sequences

So your point is: not all constants are created equal. Which circles all the way back to my original point that this argument is pretty funny :)