Non-Flaky and Nearly Optimal Time-Based Treatment of Asynchronous Wait Web Tests

Asynchronous waits are a common root cause of flaky tests and a major time-influential factor of Web application testing. We build a dataset of 49 reproducible asynchronous wait flaky tests and their fixes from 26 open source projects to study their characteristics in Web testing. Our study reveals that developers adjusted wait time to address asynchronous wait flakiness in about 63% of cases (31 out of 49), even when the underlying causes lie elsewhere. From this, we introduce TRaf , an automated time-based repair for asynchronous wait flakiness in Web applications. TRaf determines appropriate wait times for asynchronous calls in Web applications by analyzing code similarity and past change history. Its key insight is that efficient wait times can be inferred from the current or past codebase since developers tend to repeat similar mistakes. Our analysis shows that TRaf can statically suggest a shorter wait time to alleviate async wait flakiness immediately upon the detection, reducing test execution time by 11.1% compared to the timeout values initially chosen by developers. With optional dynamic tuning, TRaf can reduce the execution time by 16.8% in its initial refinement compared to developer-written patches and by 6.2% compared to the post-refinements of these original patches. Overall, we sent 16 pull requests from our dataset, each fixing one test, to the developers. So far, three have been accepted by the developers.

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Publication Details

Journal
ACM Transactions on Software Engineering and Methodology
Published
2024-09-13
DOI
https://doi.org/10.1145/3695989
Citations
3
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
1.46
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article

Non-Flaky and Nearly Optimal Time-Based Treatment of Asynchronous Wait Web Tests

Jeongju Sohn, Sarra Habchi, Yu Pei, Mike Papadakis
3 citations
ACM Transactions on Software Engineering and Methodology
Software Testing and Debugging Techniques
1.46
article

Non-Flaky and Nearly Optimal Time-Based Treatment of Asynchronous Wait Web Tests

Jeongju Sohn, Sarra Habchi, Yu Pei, Mike Papadakis
article en
3 citations

Abstract

Asynchronous waits are a common root cause of flaky tests and a major time-influential factor of Web application testing. We build a dataset of 49 reproducible asynchronous wait flaky tests and their fixes from 26 open source projects to study their characteristics in Web testing. Our study reveals that developers adjusted wait time to address asynchronous wait flakiness in about 63% of cases (31 out of 49), even when the underlying causes lie elsewhere. From this, we introduce TRaf , an automated time-based repair for asynchronous wait flakiness in Web applications. TRaf determines appropriate wait times for asynchronous calls in Web applications by analyzing code similarity and past change history. Its key insight is that efficient wait times can be inferred from the current or past codebase since developers tend to repeat similar mistakes. Our analysis shows that TRaf can statically suggest a shorter wait time to alleviate async wait flakiness immediately upon the detection, reducing test execution time by 11.1% compared to the timeout values initially chosen by developers. With optional dynamic tuning, TRaf can reduce the execution time by 16.8% in its initial refinement compared to developer-written patches and by 6.2% compared to the post-refinements of these original patches. Overall, we sent 16 pull requests from our dataset, each fixing one test, to the developers. So far, three have been accepted by the developers.

ACM Transactions on Software Engineering and MethodologyVol. 34(2)
University of Luxembourg (LU), Kyungpook National University (KR), Ubisoft (Canada) (CA)
Openalex Percentile: Top 16%
Software Testing and Debugging Techniques
1.46
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Non-Flaky and Nearly Optimal Time-Based Treatment of Asynchronous Wait Web Tests — Jeongju Sohn, Sarra Habchi, et al. · ACM Transactions on Software Engineering and Methodology (2024) | TGRS Research Map | TGRS