Big-O notation

[Andrew Dalke]

A. Lloyd Flanagan
> This mathematical analysis of an algorithm's behavior (and best-case,
> average, and worst-case performance) can be trivial.  For example, x +
> 1 is O(1).

Or not so trivial.  If x can be an arbitrary size integer, represented
in memory as a chunk of bits, the value 'n' for the number of bits,
and a sign flag, then addition could be O(n) == O(log(x)).  Eg,
suppose    x =  1111111111111111111111111111111111111111
add 1 to get = 10000000000000000000000000000000000000000
so 49 bits were affected.

But for fixed size integers, the above is true.

                    Andrew
                    dalke at dalkescientific.com