TERA: optimizing stochastic regression tests in machine learning projects-Reference-Cited by-同舟云学术

TERA: optimizing stochastic regression tests in machine learning projects

Published:2021-07-11 Issue: Volume: Page:
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Container-title:Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis
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Author:

Dutta Saikat¹,Selvam Jeeva¹,Jain Aryaman¹,Misailovic Sasa¹

Affiliation:

1. University of Illinois at Urbana-Champaign, USA

Funder

National Science Foundation

Microsoft

Facebook

Publisher

ACM

Link

Reference112 articles.

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3. 2021. CircleCI. https://circleci.com 2021. CircleCI. https://circleci.com

4. 2021. Cleverhans. https://github.com/tensorflow/cleverhans 2021. Cleverhans. https://github.com/tensorflow/cleverhans

5. 2021. Fairseq. https://github.com/pytorch/fairseq 2021. Fairseq. https://github.com/pytorch/fairseq

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3. Balancing Effectiveness and Flakiness of Non-Deterministic Machine Learning Tests;2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE);2023-05