On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot-Reference-Cited by-同舟云学术

On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot

Published:2023-05 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)
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Author:

Mastropaolo Antonio¹,Pascarella Luca¹,Guglielmi Emanuela²,Ciniselli Matteo¹,Scalabrino Simone²,Oliveto Rocco²,Bavota Gabriele¹

Affiliation:

1. SEART @ Software Institute, Università della Svizzera italiana (USI),Switzerland

2. University of Molise,STAKE Lab,Italy

Funder

European Research Council (ERC)

Publisher

IEEE

Link

Reference67 articles.

1. Cognitive Complexity — An Overview and Evaluation;campbell;Proceedings of the 2018 International Conference on Technical Debt - TechDebt '18,2018

2. Generating accurate assert statements for unit test cases using pretrained transformers;tufano;CoRR,2020

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