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Reasoning and planning with large language models in code development (survey for KDD 2024 tutorial)

By Gaurav Gupta, Wooseok Ha, Behrooz Omidvar-Tehrani, Shiqi Wang, Jun Huan
2024
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Large Language Models (LLMs) are revolutionizing the field of code development by leveraging their deep understanding of code patterns, syntax, and semantics to assist developers in various tasks, from code generation and testing to code understanding and documentation. In this survey, accompanying our proposed lecture-style tutorial for KDD 2024, we explore the multifaceted impact of LLMs on code development, delving into techniques for generating high-quality code, creating comprehensive test cases, automatically generating documentation, and engaging in interactive code reasoning. Throughout the survey, we highlight some crucial components surrounding LLMs, including pre-training, fine-tuning, prompt engineering, iterative refinement, agent planning, and hallucination mitigation. We put forward that such ingredients are essential to harness the full potential of these powerful AI models in revolutionizing software engineering and paving the way for a more efficient, effective, and innovative future in code development.
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