Systems Correctness Practices at AWS

Building reliable and secure software requires a range of approaches to reason about systems correctness. Alongside industry-standard testing methods (such as unit and integration testing), AWS has adopted model checking, fuzzing, property-based testing, fault-injection testing, deterministic simulation, event-based simulation, and runtime validation of execution traces. Formal methods have been an important part of the development process - perhaps most importantly, formal specifications as test oracles that provide the correct answers for many of AWS's testing practices. Correctness testing and formal methods remain key areas of investment at AWS, accelerated by the excellent returns seen on investments in these areas already.

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Publication Details

Journal
Queue
Published
2024-12-31
DOI
https://doi.org/10.1145/3712057
Citations
3
Primary Topic
Software Reliability and Analysis Research
Type
article
Field-Weighted Citation Impact
1.46
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article

Systems Correctness Practices at AWS

Marc Brooker, Ankush Desai
3 citations
Queue
Software Reliability and Analysis Research
1.46
article

Systems Correctness Practices at AWS

Marc Brooker, Ankush Desai
article en
3 citations

Abstract

Building reliable and secure software requires a range of approaches to reason about systems correctness. Alongside industry-standard testing methods (such as unit and integration testing), AWS has adopted model checking, fuzzing, property-based testing, fault-injection testing, deterministic simulation, event-based simulation, and runtime validation of execution traces. Formal methods have been an important part of the development process - perhaps most importantly, formal specifications as test oracles that provide the correct answers for many of AWS's testing practices. Correctness testing and formal methods remain key areas of investment at AWS, accelerated by the excellent returns seen on investments in these areas already.

QueueVol. 22(6)
Amazon (United States) (US)
Openalex Percentile: Top 14%
Software Reliability and Analysis Research
1.46
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