Assessing operating system dependability remains a challenging problem, particularly in monolithic systems. Component interfaces are not well-defined and boundaries are not enforced at runtime. This allows faults in individual components to arbitrarily affect other parts of the system. Software fault injection (SFI) can be used to experimentally assess the resilience of such systems in the presence of faulty components. However, applying SFI to complex, monolithic operating systems poses challenges due to long test latencies and the difficulty of detecting corruptions in the internal state of the operating system.In this paper, we present a novel approach that leverages static and dynamic analysis alongside modern operating system and virtual machine features to reduce SFI test latencies for operating system kernel components while enabling efficient and accurate detection of internal state corruptions.We demonstrate the feasibility of our approach by applying it to multiple widely used Linux file systems.

In this paper, we present a novel approach that leverages static and dynamic analysis alongside modern operating system and virtual machine features to reduce SFI test latencies for operating system kernel components while enabling efficient and accurate detection of internal state corruptions.

We demonstrate the feasibility of our approach by applying it to multiple widely used Linux file systems