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Efficient software-based fault isolation

Open access
Wahbe, Robert, Lucco, Steven, Anderson, Thomas E., Graham, Susan L.·1993·Proceedings of the fourteenth ACM symposium on Operating systems principles - SOSP '93

Abstract

One way to provide fault isolation among cooperating software modules is to place each in its own address space. However, for tightly-coupled modules, this solution incurs prohibitive context switch overhead. In this paper, we present a software approach to implementing fault isolation within a single address space.Our approach has two parts. First, we load the code and data for a distrusted module into its own fault do main, a logically separate portion of the application's address space. Second, we modify the object code of a distrusted module to prevent it from writing or jumping to an address outside its fault domain. Both these software operations are portable and programming language independent.Our approach poses a tradeoff relative to hardware fault isolation: substantially faster communication between fault domains, at a cost of slightly increased execution time for distrusted modules. We demonstrate that for frequently communicating modules, implementing fault isolation in software rather than hardware can substantially improve end-to-end application performance.

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Metadata

Authors
Wahbe, R., Lucco, S., Anderson, T. E., & Graham, S. L.
Venue
Proceedings of the fourteenth ACM symposium on Operating systems principles - SOSP '93
Publisher
ACM Press
Published
1993
Pages
203-216
OpenAlex
W2079029390
Cited by
1,214
References
0
FWCI
31.41
Type
conference paper
Language
en
Open access
gold

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CoChat. (2026). Citation check: Efficient software-based fault isolation. https://app.cochat.ai/papers/10.1145/168619.168635
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Wahbe, R., Lucco, S., Anderson, T. E., & Graham, S. L. (1993). Efficient software-based fault isolation. Proceedings of the fourteenth ACM symposium on Operating systems principles - SOSP '93. https://doi.org/10.1145/168619.168635

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.