A Careful Balancing Act - The Daily WTF: "This just occurred to me. So many people here are using big-O to argue about which sorting algorithm would be fastest. Big-O tells us how an algorithm scales, not how fast an algorithm is. Of course, there is some set size that the better algortihm (as measured by Big-O) will be faster than the worse algorithm, but that could be ten elements or ten-bllion elements. Big-O does not tell us that.

Basicly everyone is arguing about the top speed of a car, but using the argument 'This car accelerates faster 0-60.' The two measures are not necessarily related.

For small data-sets an algorithm with a worse Big-O measure can be faster than and algorithm with a better Big-O measure. Big-O is only a measure of relative speed as n gets very large. I think we were told that n was under 1000. Please confine future performance arguments to relative speed of algorithms while n is between 1 and 1000."