Measuring software dependability by robustness benchmarking

Mukherjee, A.; Siewiorek, D.P.

doi:10.1109/32.601075

Cited by 65 publications

(25 citation statements)

References 10 publications

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“…This modified version could crash the Mach 3.0 OS in less than ten seconds. The authors also pointed out the usefulness of modular benchmarks, targeting specific areas of the system, such as file, memory and inter-process communication subsystems for an OS [Siewiorek et al, 1993;Dingman et al, 1995;Mukherjee and Siewiorek, 1997].…”

Section: Operating Systems Dependability Evaluationmentioning

confidence: 99%

“…This simple test successfully crashed several UNIX systems. The program was later extended to CMU Crashme which subjected UNIX system calls to random strings, thereby testing their parameter checking code [Mukherjee and Siewiorek, 1997]. This modified version could crash the Mach 3.0 OS in less than ten seconds.…”

Section: Operating Systems Dependability Evaluationmentioning

confidence: 99%

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Robustness Evaluation of Operating Systems

Johansson

2008

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SummaryThe premise behind this thesis is the observation that Operating Systems (OS), being the foundation behind operations of computing systems, are complex entities and also subject to failures. Consequently, when they do fail, the impact is the loss of system service and the applications running thereon. While a multitude of sources for OS failures exist, device drivers are often identified as a prominent cause behind failures.In order to characterize the impact of driver failures, at both the OS and application levels, this thesis develops a framework for error propagation-based robustness profiling for an OS. The framework is first developed conceptually and then experimentally validated on a real OS, namely Windows CE .Net. The choice of Windows CE is driven by its representativeness for a multitude of OS's, as well as the ability to customize the OS components for particular needs.For experimental validation, fault injection is a prominent technique that can be used to simulate faults (or errors) in the system by inserting synthetic ones and study their effect. Three key questions with such a technique are where, what and when to inject faults. This thesis shows how injecting errors at the interface between drivers and the OS can be very effective in evaluating the effects driver faults can have.To quantify the OS's robustness, this thesis defines a series of error propagation measures, specifically tailored for device drivers. These measures allow for quantifying and comparing both individual services and device drivers on their susceptibility and diffusing abilities.This thesis compares three contemporary error models on their suitability for robustness evaluation. The classical bit-flip model is found to identify a higher number of severe failures in the system. It also identifies failures for more services than both other models, data type and fuzzing. However, its main drawback is that it requires substantially more injections than the other two. Fuzzing, even though not giving rise to as many failures is able to find new additional services with severe failures.A careful study of the injections performed with the bit-flip model shows that only a few bits are generally useful for identifying new services with robustness weaknesses. Consequently, a new composite model is proposed, combining the most effective bits of the bit-flip model with the fuzzing model's ability to identify new services, giving rise to new model without loss of important information and at the same time incurring a moderate number of injections.To answer the question of when to inject an error this thesis proposes a novel model of a driver's usage profile, focusing on high-level operations being carried out. It guides the injection of errors to instances when the driver is carrying out specific operations. Results from extensive fault injection experiments show that more service vulnerabilities can be discovered. Furthermore, a priori profiling of the drivers can show how effective the proposed approach will be. vi

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Section: Operating Systems Dependability Evaluationmentioning

confidence: 99%

Section: Operating Systems Dependability Evaluationmentioning

confidence: 99%

Robustness Evaluation of Operating Systems

Johansson

2008

Information Assurance

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“…Middleware support systems like CORBA have been examined at the client-side interface of an ORB [19] and internally at the level of the Naming and Event services [14]. Dependability benchmarking has resorted to robustness testing in order to evaluate systems [18,23,24]. For example, Kalakech et al proposed an OS benchmark which provided a comprehensive set of measures, and applied it to the Windows 2000 [11].…”

Section: Related Workmentioning

confidence: 99%

Robustness Testing of the Windows DDK

Mendonça¹,

Neves²

2007

37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'07)

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“…Several relevant attempts have been previously proposed to help characterize the failure modes and robustness of software executives. A comprehensive analysis of the issues linking robustness and dependability can be found in [7]. The executives targeted in these studies encompass real time microkernels and general purpose OSs [1,8].…”

Section: Introductionmentioning

confidence: 99%