Automated Unit Test Improvement using Large Language Models at Meta-Reference-Cited by-同舟云学术

Automated Unit Test Improvement using Large Language Models at Meta

Published:2024-07-10 Issue: Volume: Page:
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Container-title:Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering
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Author:

Alshahwan Nadia¹^ORCID,Chheda Jubin¹^ORCID,Finogenova Anastasia¹^ORCID,Gokkaya Beliz¹^ORCID,Harman Mark²^ORCID,Harper Inna¹^ORCID,Marginean Alexandru¹^ORCID,Sengupta Shubho¹^ORCID,Wang Eddy¹^ORCID

Affiliation:

1. Meta Platforms, Menlo Park, USA

2. Meta Platforms, Menlo Park, USA / University College London, London, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3663529.3663839

Reference52 articles.

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3. Toufique Ahmed, Kunal Suresh Pai, Premkumar Devanbu, and Earl T. Barr. 2023. Improving Few-Shot Prompts with Relevant Static Analysis Products. arXiv:2304.06815

4. Nadia Alshahwan, Xinbo Gao, Mark Harman, Yue Jia, Ke Mao, Alexander Mols, Taijin Tei, and Ilya Zorin. 2018. Deploying Search Based Software Engineering with Sapienz at Facebook (keynote paper). In 10^th International Symposium on Search Based Software Engineering (SSBSE 2018). Montpellier, France. 3–45. Springer LNCS 11036

5. Nadia Alshahwan, Mark Harman, and Alexandru Marginean. 2023. Software Testing Research Challenges: An Industrial Perspective. In 2023 IEEE Conference on Software Testing, Verification and Validation (ICST 2023). 1–10.

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