Pitfalls in Experiments with DNN4SE: An Analysis of the State of the Practice

Author:

Vegas Sira1,Elbaum Sebastian2

Affiliation:

1. Universidad Politécnica de Madrid, Madrid, Spain

2. University of Virginia, Charlottesville, USA

Funder

MCIN/AEI/10.13039/501100011033, ERDF A way of making Europe

NSF

Publisher

ACM

Reference38 articles.

1. 2022. The 37th AAAI Conference on Artificial Intelligence Reproducibility Checklist. accessed August 26, 2022 . 2022. The 37th AAAI Conference on Artificial Intelligence Reproducibility Checklist. accessed August 26, 2022.

2. Sources of variation

3. Identifying, categorizing and mitigating threats to validity in software engineering secondary studies

4. Andrea Arcuri and Lionel Briand . 2011 . A Practical Guide for Using Statistical Tests to Assess Randomized Algorithms in Software Engineering . In Proceedings of the 33rd International Conference on Software Engineering. 1–10 . https://doi.org/10.1145/1985793.1985795 10.1145/1985793.1985795 10.1145/1985793.1985795 Andrea Arcuri and Lionel Briand. 2011. A Practical Guide for Using Statistical Tests to Assess Randomized Algorithms in Software Engineering. In Proceedings of the 33rd International Conference on Software Engineering. 1–10. https://doi.org/10.1145/1985793.1985795 10.1145/1985793.1985795

5. Xavier Bouthillier , Pierre Delaunay , Mirko Bronzi , Assya Trofimov , Brennan Nichyporuk , Justin Szeto , Nazanin Mohammadi Sepahvand , Edward Raff , Kanika Madan , Vikram Voleti , Samira Ebrahimi Kahou , Vincent Michalski , Tal Arbel , Chris Pal , Gael Varoquaux , and Pascal Vincent . 2021 . Accounting for Variance in Machine Learning Benchmarks . In Proceedings of Machine Learning and Systems. 747–769 . Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Nazanin Mohammadi Sepahvand, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Tal Arbel, Chris Pal, Gael Varoquaux, and Pascal Vincent. 2021. Accounting for Variance in Machine Learning Benchmarks. In Proceedings of Machine Learning and Systems. 747–769.

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1. Pitfalls in Experiments with DNN4SE: An Analysis of the State of the Practice;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

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