面向AI辅助编程的大代码自然语言生成与理解：综述
Natural Language Generation and Understanding of Big Code for AI-Assisted Programming: A Review
AI总结：
本文综述了基于大代码训练的Transformer大语言模型在AI辅助编程中的应用，涵盖代码生成、补全、翻译等任务，并探讨了融合NLP技术与软件自然性的挑战与机遇。
摘要：
本文对在AI辅助编程任务领域中利用自然语言处理（NLP）技术的文献进行了全面综述，特别关注使用大代码（Big Code）训练的基于Transformer的大型语言模型（LLMs）。经过软件自然性增强的LLMs在促进AI辅助编程应用方面发挥了关键作用，这些应用包括代码生成、代码补全、代码翻译、代码精化、代码摘要、缺陷检测和克隆检测。此类应用的著名示例包括由OpenAI Codex驱动的GitHub Copilot和DeepMind AlphaCode。本文概述了主要的LLMs及其在与AI辅助编程相关的下游任务中的应用。此外，本文探讨了在这些应用中将NLP技术与软件自然性相结合所面临的挑战与机遇，并讨论了将AI辅助编程能力扩展到Apple Xcode以用于移动软件开发的问题。本文还提出了将NLP技术与软件自然性相结合的挑战与机遇，从而为开发者提供先进的编码辅助并简化软件开发流程。
英文摘要：
This paper provides a comprehensive review of the literature concerning the utilization of Natural Language Processing (NLP) techniques, with a particular focus on transformer-based large language models (LLMs) trained using Big Code, within the domain of AI-assisted programming tasks. LLMs, augmented with software naturalness, have played a crucial role in facilitating AI-assisted programming applications, including code generation, code completion, code translation, code refinement, code summarization, defect detection, and clone detection. Notable examples of such applications include the GitHub Copilot powered by OpenAI's Codex and DeepMind AlphaCode. This paper presents an overview of the major LLMs and their applications in downstream tasks related to AI-assisted programming. Furthermore, it explores the challenges and opportunities associated with incorporating NLP techniques with software naturalness in these applications, with a discussion on extending AI-assisted programming capabilities to Apple's Xcode for mobile software development. This paper also presents the challenges of and opportunities for incorporating NLP techniques with software naturalness, empowering developers with advanced coding assistance and streamlining the software development process.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
