Papers › GAP-Gen: Guided Automatic Python Code Generation
GAP-Gen: Guided Automatic Python Code Generation
Junchen Zhao, Yurun Song, Junlin Wang, Ian G. Harris
Automatic code generation from natural language descriptions can be highly beneficial during the process of software development. In this work, we propose GAP-Gen, a Guided Automatic Python Code Generation method based on Python syntactic constraints and semantic constraints. We first introduce Python syntactic constraints in the form of Syntax-Flow, which is a simplified version of Abstract Syntax Tree (AST) reducing the size and high complexity of Abstract Syntax Tree but maintaining crucial syntactic information of Python code. In addition to Syntax-Flow, we introduce Variable-Flow which abstracts variable and function names consistently through out the code. In our work, rather than pretraining, we focus on modifying the finetuning process which reduces computational requirements but retains high generation performance on automatic Python code generation task. GAP-Gen fine-tunes the transformer based language models T5 and CodeT5 using the Code-to-Docstring datasets CodeSearchNet, CodeSearchNet AdvTest and Code-Docstring Corpus from EdinburghNLP. Our experiments show that GAP-Gen achieves better results on automatic Python code generation task than previous works.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Code Generation | CodeXGLUE - CodeSearchNet | GAP-Gen | Java/BLEU | - | #2 of 2 | Archive leaderboard | report |
| Code Generation | CodeXGLUE - CodeSearchNet | GAP-Gen | Java/EM | - | #2 of 2 | Archive leaderboard | report |
| Code Generation | CodeXGLUE - CodeSearchNet | GAP-Gen | Python/BLEU | 22.3 | #2 of 2 | Archive leaderboard | report |
| Code Generation | CodeXGLUE - CodeSearchNet | GAP-Gen | Python/CodeBLEU | 24.1 | #2 of 2 | Archive leaderboard | report |
| Code Generation | CodeXGLUE - CodeSearchNet | GAP-Gen | Python/EM | - | #2 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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