Sep 26, 2023 · In this paper, we propose an approach to suggest a correct program with minimal repair edits using CodeT5.
In this paper, we propose an approach to suggest a correct program with minimal repair edits using CodeT5. We fine-tune a pre-trained CodeT5 on code pairs ...
program with minimal repair edits using CodeT5. We fine-tune a pre-trained CodeT5 on code pairs of wrong and correct programs and evaluate its performance ...
The effectiveness of LMs in suggesting program repair with minimal edits for solving introductory programming problems is demonstrated and it is shown that ...
The experimental results show that the fine-tuned CodeT5 achieves a pass@100 of 91.95% and an average edit distance of the most similar correct program of 6.84, ...
The experimental results show that the fine-tuned CodeT5 achieves a pass@100 of 91. 95% and an average edit distance of the most similar correct program of 6.
Sep 17, 2024 · Towards Minimal Edits in Automated Program Repair: A Hybrid Framework Integrating Graph Neural Networks and Large Language Models.
Our model, which is semi-parametric in nature, aims to combine both benefits of the implicit (parametric) end-to-end program repair learning and the explicit ( ...
This paper formulates automatic program repair (APR) for low-resource error types and proposes a meta-learning framework to address this. More concretely, Meta- ...
Missing: Edits | Show results with:Edits
Refactoring programs using large language models with few-shot examples ... 2023. Program Repair with Minimal Edits Using CodeT5. A Shirafuji, MM Rahman ...