Mutation testing is an established approach for checking whether
code satisfies a code-independent functional specification, and for
evaluating whether a test set is adequate. Current mutation testing
approaches, however, do not account for accuracy requirements
that appear with numerical specifications implemented in floating-
point arithmetic code, but which are a frequent part of safety-critical
software. We present Magneto, an instantiation of mutation testing
that fully automatically generates a test set from a real-valued specification. The generated tests check numerical code for accuracy,
robustness and functional behavior bugs. Our technique is based on
formulating test case and oracle generation as a constraint satisfaction problem over interval domains, which soundly bounds errors,
but is nonetheless efficient. We evaluate Magneto on a standard
floating-point benchmark set and find that it outperforms a random
testing baseline for producing useful adequate test sets.