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Two Steps to Precision: Enhancing Reliable API Invocation in Code Generation
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AI
DOI：10.1007/978-981-95-3346-6_33.png)
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Abstract
En 中文
Automatic code generation is crucial in modern software development, yet large language models struggle with real-world challenges like code versioning and multi-API invocation. Existing approaches, including direct generation and retrieval-augmented methods, often fail to ensure precise API usage. This paper introduces a simple yet effective two-step framework: rough code generation or retrieval followed by fine code editing. Experiments on VersiCode and BigCodeBench show significant performance gains in version-specific code completion and function-level programming. These results demonstrate the framework's practicality in enhancing LLM-based code generation systems.
Keywords:
code generation
API invocation
code editing
large language models
version-specific completion
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