Can OpenAI's codex fix bugs? an evaluation on QuixBugs JA Prenner, H Babii, R Robbes Proceedings of the Third International Workshop on Automated Program Repair …, 2022 | 79 | 2022 |
Automatic program repair with openai's codex: Evaluating quixbugs JA Prenner, R Robbes arXiv preprint arXiv:2111.03922, 2021 | 52 | 2021 |
Making the most of small Software Engineering datasets with modern machine learning JA Prenner, R Robbes IEEE Transactions on Software Engineering 48 (12), 5050-5067, 2021 | 19 | 2021 |
Codex hacks hackerrank: Memorization issues and a framework for code synthesis evaluation A Karmakar, JA Prenner, M D'Ambros, R Robbes arXiv preprint arXiv:2212.02684, 2022 | 14 | 2022 |
RunBugRun--An Executable Dataset for Automated Program Repair JA Prenner, R Robbes arXiv preprint arXiv:2304.01102, 2023 | 8 | 2023 |
Mining software repositories with a collaborative heuristic repository H Babii, JA Prenner, L Stricker, A Karmakar, A Janes, R Robbes 2021 IEEE/ACM 43rd International Conference on Software Engineering: New …, 2021 | 6 | 2021 |
Out of context: How important is local context in neural program repair? JA Prenner, R Robbes Proceedings of the IEEE/ACM 46th International Conference on Software …, 2024 | 2 | 2024 |
GLUECode: A Benchmark for Source Code Machine Learning Models A Karmakar, JA Prenner, M Allamanis, R Robbes | | 2020 |