Fast Kernel Error Propagation Analysis in Virtualized Environments

Coppik, Nicolas and Darmstadt, TU and Suri, Neeraj (2021) Fast Kernel Error Propagation Analysis in Virtualized Environments. In: 2021 14th IEEE Conference on Software Testing, Verification and Validation (ICST) :. IEEE, BRA, pp. 159-170. ISBN 9781728168371

[thumbnail of vmfork-ieee-copyright]
Text (vmfork-ieee-copyright)
vmfork_ieee_copyright.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (293kB)

Abstract

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

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
©2021 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ID Code:
154904
Deposited By:
Deposited On:
19 May 2021 11:55
Refereed?:
Yes
Published?:
Published
Last Modified:
24 Sep 2024 23:54