The impact of fault models on software robustness evaluations

Following the design and in-lab testing of software, the evaluation of its resilience to actual operational perturbations in the field is a key validation need. Software-implemented fault injection (SWIFI) is a widely used approach for evaluating the robustness of software components. Recent research [24, 18] indicates that the selection of the applied fault model has considerable influence on the results of SWIFI-based evaluations, thereby raising the question how to select appropriate fault models (i.e. that provide justified robustness evidence). This paper proposes several metrics for comparatively evaluating fault models's abilities to reveal robustness vulnerabilities. It demonstrates their application in the context of OS device drivers by investigating the influence (and relative utility) of four commonly used fault models, i.e. bit flips (in function parameters and in binaries), data type dependent parameter corruptions, and parameter fuzzing. We assess the efficiency of these models at detecting robustness vulnerabilities during the SWIFI evaluation of a real embedded operating system kernel and discuss application guidelines for our metrics alongside.