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The impact of fault models on software robustness evaluations

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The impact of fault models on software robustness evaluations. / Winter, S.; Sârbu, C.; Suri, Neeraj; Murphy, B.

Proceedings of the 33rd International Conference on Software Engineering . ACM, 2011. p. 51-60.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Winter, S, Sârbu, C, Suri, N & Murphy, B 2011, The impact of fault models on software robustness evaluations. in Proceedings of the 33rd International Conference on Software Engineering . ACM, pp. 51-60. https://doi.org/10.1145/1985793.1985801

APA

Winter, S., Sârbu, C., Suri, N., & Murphy, B. (2011). The impact of fault models on software robustness evaluations. In Proceedings of the 33rd International Conference on Software Engineering (pp. 51-60). ACM. https://doi.org/10.1145/1985793.1985801

Vancouver

Winter S, Sârbu C, Suri N, Murphy B. The impact of fault models on software robustness evaluations. In Proceedings of the 33rd International Conference on Software Engineering . ACM. 2011. p. 51-60 https://doi.org/10.1145/1985793.1985801

Author

Winter, S. ; Sârbu, C. ; Suri, Neeraj ; Murphy, B. / The impact of fault models on software robustness evaluations. Proceedings of the 33rd International Conference on Software Engineering . ACM, 2011. pp. 51-60

Bibtex

@inproceedings{16da6552c79b4c8e8cedf6849d4f098e,
title = "The impact of fault models on software robustness evaluations",
abstract = "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. {\textcopyright} 2011 ACM.",
keywords = "fault injection, fault models, robustness testing, Bit-flips, Data type, Device Driver, Embedded operating systems, Fault injection, Fault model, Function parameters, Relative utility, Robustness evaluation, Software component, Random access storage, Software engineering, Software testing, Models",
author = "S. Winter and C. S{\^a}rbu and Neeraj Suri and B. Murphy",
year = "2011",
month = may,
day = "21",
doi = "10.1145/1985793.1985801",
language = "English",
isbn = "9781450304450",
pages = "51--60",
booktitle = "Proceedings of the 33rd International Conference on Software Engineering",
publisher = "ACM",

}

RIS

TY - GEN

T1 - The impact of fault models on software robustness evaluations

AU - Winter, S.

AU - Sârbu, C.

AU - Suri, Neeraj

AU - Murphy, B.

PY - 2011/5/21

Y1 - 2011/5/21

N2 - 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. © 2011 ACM.

AB - 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. © 2011 ACM.

KW - fault injection

KW - fault models

KW - robustness testing

KW - Bit-flips

KW - Data type

KW - Device Driver

KW - Embedded operating systems

KW - Fault injection

KW - Fault model

KW - Function parameters

KW - Relative utility

KW - Robustness evaluation

KW - Software component

KW - Random access storage

KW - Software engineering

KW - Software testing

KW - Models

U2 - 10.1145/1985793.1985801

DO - 10.1145/1985793.1985801

M3 - Conference contribution/Paper

SN - 9781450304450

SP - 51

EP - 60

BT - Proceedings of the 33rd International Conference on Software Engineering

PB - ACM

ER -