FLEX: fixing flaky tests in machine learning projects by updating assertion bounds-Reference-Cited by-同舟云学术

FLEX: fixing flaky tests in machine learning projects by updating assertion bounds

Published:2021-08-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
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Author:

Dutta Saikat¹,Shi August²,Misailovic Sasa¹

Affiliation:

1. University of Illinois at Urbana-Champaign, USA

2. University of Texas at Austin, USA

Funder

Facebook

Microsoft

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3468264.3468615

Reference85 articles.

1. 2020. https://anaconda.org/ 2020. https://anaconda.org/

2. Andrea Arcuri and Lionel Briand. 2011. A Practical Guide for Using Statistical Tests to Assess Randomized Algorithms in Software Engineering. In ICSE. Andrea Arcuri and Lionel Briand. 2011. A Practical Guide for Using Statistical Tests to Assess Randomized Algorithms in Software Engineering. In ICSE.

3. Andrea Arcuri and Lionel Briand. 2014. A hitchhiker’s guide to statistical tests for assessing randomized algorithms in software engineering. STVR. Andrea Arcuri and Lionel Briand. 2014. A hitchhiker’s guide to statistical tests for assessing randomized algorithms in software engineering. STVR.

4. Automated threshold selection for extreme value analysis via ordered goodness-of-fit tests with adjustment for false discovery rate

5. August A Balkema and Laurens De Haan. 1978. Limit distributions for order statistics. I. Theory of Probability & Its Applications. August A Balkema and Laurens De Haan. 1978. Limit distributions for order statistics. I. Theory of Probability & Its Applications.

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