Question

When comparing doubles for equality, we need to give a tolerance level, because floating-point computation might introduce errors. For example:

double x; 
double y; 
x = f();
y = g();

if (fabs(x-y)<epsilon) {
   // they are equal!
} else {
   // they are not!
}

However, if I simply assign a constant value, without any computation, do I still need to check the epsilon?

double x = 1;
double y = 1;

if (x==y) {
   // they are equal!
} else {
   // no they are not!
}

Is == comparison good enough? Or I need to do fabs(x-y)<epsilon again? Is it possible to introduce error in assigning? Am I too paranoid?

How about casting (double x = static_cast<double>(100))? Is that gonna introduce floating-point error as well?

I am using C++ on Linux, but if it differs by language, I would like to understand that as well.

Answer 1

Actually, it depends on the value and the implementation. The C++ standard (draft n3126) has this to say in 2.14.4 Floating literals:

If the scaled value is in the range of representable values for its type, the result is the scaled value if representable, else the larger or smaller representable value nearest the scaled value, chosen in an implementation-defined manner.

In other words, if the value is exactly representable (and 1 is, in IEEE754, as is 100 in your static cast), you get the value. Otherwise (such as with 0.1) you get an implementation-defined close match ^(a). Now I’d be very worried about an implementation that chose a different close match based on the same input token but it is possible.

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^(a) Actually, that paragraph can be read in two ways, either the implementation is free to choose either the closest higher or closest lower value regardless of which is actually the closest, or it must choose the closest to the desired value.

If the latter, it doesn’t change this answer however since all you have to do is hardcode a floating point value exactly at the midpoint of two representable types and the implementation is once again free to choose either.

For example, it might alternate between the next higher and next lower for the same reason banker’s rounding is applied – to reduce the cumulative errors.