Interval constraint-based mutation testing of numerical specifications

Abstract

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.