Xin Wang, Yasheng Wang, Yao Wan, Fei Mi, Yitong Li, Pingyi Zhou, Jin Liu, Hao Wu, Xin Jiang, Qun Liu
| Challenge: | Existing deep-learning approaches model code generation as text generation, but few of them account for compilability of the generated programs. |
| Approach: | They propose a three-stage pipeline utilizing compiler feedback for compilable code generation to improve compilability. |
| Outcome: | The proposed pipeline improves compilability of generated programs by combining compiler feedback, language model fine-tuning, and compilable discrimination. |
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