Many times in expensive loops one must make decisions. Decisions
must be determined and the determination costs.
for(int i = 0; i < N; i++)
{
if(decision(i)) A; else B;
}
the if statement costs N times the cycle cost.
In some cases the decision holds for continuous ranges. For some
0 <= n <= N the decision is constant, but n is
arbitrary(determined by unknown factors at compile time).
One can speed up the routine by using something akin to a
simplified strategy pattern where one uses
functions/delegates/lambdas to code a faster version without the
test:
for(int i = 0; i < N; i++)
{
d = (){ if(decision(i)) A; else d = () { B; };
d();
}
this code basically reduces to
for(int i = 0; i < N; i++)
{
B;
}
Once the decision fails, which we assume once it fails it always
fails in this particular case.
Therefor, once the decision fails it kicks in the "faster" code.
Suppose decision is very slow.
The cycle cost is then n times rather than N times.
In general, such techniques can be used to speed up code,
sometimes significantly, but are difficult to implement using a
standard pattern and for more complex decision functions.
Does anyone see any way to use some some of D's power to help
simplify such things but not using something like a strategy
pattern or complexifying the overall design(using advanced
techniques such as templates, mixins is not making the code more
complex).
