WARP -- Web-Augmented Real-time Program Repairer: A Real-Time Compilation Error Resolution using LLMs and Web-Augmented Synthesis
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911183980724224 |
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| author | Luiz, Anderson de Lima |
| author_facet | Luiz, Anderson de Lima |
| contents | Compilation errors represent a significant bottleneck in software development productivity. This paper introduces WARP (Web-Augmented Real-time Program Repairer), a novel system that leverages Large Language Models (LLMs) and dynamic web-augmented synthesis for real-time resolution of these errors. WARP actively monitors developer terminals, intelligently detects compilation errors, and synergistically combines the understanding of a fine-tuned Code-LLM with relevant solutions, explanations, and code snippets retrieved from up-to-date web sources like developer forums and official documentation. Experimental results on our curated benchmark, CGP (featuring C/C++, Python, and Go errors), demonstrate WARP achieves a superior fix rate (72.5 % Compiles correctly) and higher semantic correctness compared to baseline LLM-only approaches and traditional IDE quick-fixes. Key technical challenges in achieving high-accuracy synthesis from noisy web data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_25192 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | WARP -- Web-Augmented Real-time Program Repairer: A Real-Time Compilation Error Resolution using LLMs and Web-Augmented Synthesis Luiz, Anderson de Lima Software Engineering 68T07 Compilation errors represent a significant bottleneck in software development productivity. This paper introduces WARP (Web-Augmented Real-time Program Repairer), a novel system that leverages Large Language Models (LLMs) and dynamic web-augmented synthesis for real-time resolution of these errors. WARP actively monitors developer terminals, intelligently detects compilation errors, and synergistically combines the understanding of a fine-tuned Code-LLM with relevant solutions, explanations, and code snippets retrieved from up-to-date web sources like developer forums and official documentation. Experimental results on our curated benchmark, CGP (featuring C/C++, Python, and Go errors), demonstrate WARP achieves a superior fix rate (72.5 % Compiles correctly) and higher semantic correctness compared to baseline LLM-only approaches and traditional IDE quick-fixes. Key technical challenges in achieving high-accuracy synthesis from noisy web data. |
| title | WARP -- Web-Augmented Real-time Program Repairer: A Real-Time Compilation Error Resolution using LLMs and Web-Augmented Synthesis |
| topic | Software Engineering 68T07 |
| url | https://arxiv.org/abs/2509.25192 |