Iterative Refinement of Project-Level Code Context for Precise Code Generation with Compiler Feedback

arXiv:2403.16792v1 Announce Type: new
Abstract: Large language models (LLMs) have shown remarkable progress in automated code generation. Yet, incorporating LLM-based code generation into real-life software projects poses challenges, as the generated code may contain errors in API usage, class, data structure, or missing project-specific information. As much of this project-specific context cannot fit into the prompts of LLMs, we must find ways to allow the model to explore the project-level code context. To this end, this paper puts forward a …

abstract api arxiv automated challenges class code code generation compiler context cs.cl cs.se data errors feedback generated information iterative language language models large language large language models life llm llms progress project projects software type usage