deflake.rs: Detect Flaky Tests in Rust Projects using Execution Data

In automated software testing, flaky tests are test cases that fail non-deterministically, without any modifications to the code under test (Parry et al., 2021).They can occur in any programming language, and pose a painful issue for developers due to their randomness and uncontrollability.To deal with flaky tests, many tools have been created to detect them so that developers can fix, ignore or remove them.Such tools may detect flaky tests by simply running test cases multiple times and checking for diverging results, or use more advanced methods that take into account static (data collectable without running any tests) and/or execution data (data collected by running the test suite) to determine or predict if a test is flaky without multiple runs.

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Publication Details

Journal
The Journal of Open Source Software
Published
2025-09-09
DOI
https://doi.org/10.21105/joss.08757
Citations
1
Primary Topic
Software Reliability and Analysis Research
Type
article
Field-Weighted Citation Impact
2.31

Funders

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article

deflake.rs: Detect Flaky Tests in Rust Projects using Execution Data

Phil McMinn, Benjamin Magill
1 citations
The Journal of Open Source Software
Software Reliability and Analysis Research
2.31
article

deflake.rs: Detect Flaky Tests in Rust Projects using Execution Data

Phil McMinn, Benjamin Magill
article en
1 citations

Abstract

In automated software testing, flaky tests are test cases that fail non-deterministically, without any modifications to the code under test (Parry et al., 2021).They can occur in any programming language, and pose a painful issue for developers due to their randomness and uncontrollability.To deal with flaky tests, many tools have been created to detect them so that developers can fix, ignore or remove them.Such tools may detect flaky tests by simply running test cases multiple times and checking for diverging results, or use more advanced methods that take into account static (data collectable without running any tests) and/or execution data (data collected by running the test suite) to determine or predict if a test is flaky without multiple runs.

The Journal of Open Source SoftwareVol. 10(113)
University of Sheffield (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 10%
Software Reliability and Analysis Research
2.31
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