Flaky Tests in the AI Domain
Author:
Affiliation:
1. University of Szeged, Szeged, Hungary
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3643656.3643897
Reference10 articles.
1. Detecting flaky tests in probabilistic and machine learning applications
2. To Seed or Not to Seed? An Empirical Analysis of Usage of Seeds for Testing in Machine Learning Projects
3. S. Dutta A. Shi and S. Misailovic "Flex: Fixing flaky tests in machine learning projects by updating assertion bounds " in Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering ser. ESEC/FSE 2021. New York NY USA: Association for Computing Machinery 2021 pp. 603--614. [Online]. 10.1145/3468264.3468615
4. A practical guide for using statistical tests to assess randomized algorithms in software engineering
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