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Natural Language Generation and Understanding of Big Code for AI-Assisted Programming: A Review.

Man-Fai Wong1, Shangxin Guo2, Ching-Nam Hang1

  • 1Department of Computer Science, City University of Hong Kong, Hong Kong, China.

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Summary
This summary is machine-generated.

This review explores how large language models (LLMs) trained on Big Code enhance AI-assisted programming. These models improve tasks like code generation and defect detection, streamlining software development.

Keywords:
AI-assisted programminglarge language modelssoftware naturalness

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Software Engineering

Background:

  • Natural Language Processing (NLP) techniques, particularly transformer-based large language models (LLMs), are increasingly vital in AI-assisted programming.
  • LLMs trained on Big Code, incorporating software naturalness, power applications like GitHub Copilot and DeepMind AlphaCode.
  • These models are integral to diverse programming tasks including code generation, completion, translation, refinement, summarization, and defect/clone detection.

Purpose of the Study:

  • To provide a comprehensive literature review on the application of NLP and LLMs in AI-assisted programming.
  • To overview major LLMs and their downstream applications in software development.
  • To explore challenges and opportunities in integrating NLP with software naturalness for enhanced coding assistance.

Main Methods:

  • Literature review of NLP techniques and transformer-based LLMs in AI-assisted programming.
  • Analysis of LLM applications in code generation, completion, translation, refinement, summarization, defect detection, and clone detection.
  • Exploration of challenges and opportunities, including extending capabilities to mobile development environments like Xcode.

Main Results:

  • LLMs trained on Big Code significantly enhance AI-assisted programming tasks.
  • Applications like GitHub Copilot demonstrate the practical impact of these models.
  • The integration of NLP with software naturalness offers substantial opportunities for developer empowerment.

Conclusions:

  • LLMs trained on Big Code are transformative for AI-assisted programming.
  • Further research into NLP integration can unlock advanced coding assistance and streamline development.
  • Extending these capabilities to mobile development platforms like Xcode presents a significant future opportunity.