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Testing for Floating Point Exceptions

31 Aug 2020 - adolgert

Acceptance testing for divide-by-zero behavior.

Floating point isn’t the real numbers

If you’re used to writing scientific code in a language, then you know the results of these calculations:

x = sqrt(-2)
y = 1 / 0
z = 2^(-50) / 2^10

These are all cases where something goes wrong, to a greater or lesser extent, and we rely on however our language of choice behaves.

The problem is that not all languages give the same answers for these lines of code, and the same language can give different answers for different installations or operating system settings.

Floating-point exceptions

Those lines of code are examples of three of the five kinds of floating-point exceptions. The CPU will flag these exceptions when they happen.

An inexact result is hardly unusual, given the binary representation of floating point, but it is still possible to catch this as an exception. The floating-point standard, IEEE 754, is designed to be configurable (Overton 2001), and exceptions raised on the CPU are the first link in a chain.

When the CPU sets a flag indicating that an exception has happened, the operating system has to check for that flag and clear it. The operating system then decides whether to raise an interrupt.

Each language, from C++ to Julia, has a runtime that receives interrupts from the operating system. That runtime then decides whether to generate a language-level exception or whether to ignore it.

Acceptance testing

It used to be important to include tests of floating-point exceptions in C++ because settings in the operating system or installation could change behavior. I don’t know to what extent languages are able to provide stable behavior for divide-by-zero and NaN-generating calls, but it seems like a good spot for an acceptance test during installation.


Overton, Michael L. Numerical computing with IEEE floating point arithmetic. Society for Industrial and Applied Mathematics, 2001.