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1703979 Vol 6 · Issue 7 Download Paper

Generative AI: Automating Code and Unit Testing for Faster, High-Quality Development

Allen R Chan

Subject area: Science,Engineering and Technology  ·  Area of research: Artificial Intelligence

Abstract

Automating two of the most timeconsuming tasks in software development - code generators and unit tests - Generative AI is transforming software. These modern AI models train using huge, real-world code repositories and apply state-of-the-art algorithms to deliver correct, high-quality code in minuscule times compared to traditional ways. They also create relevant and comprehensive test cases that keep pace with continuous changes made in the codebase. By taking over mundane tasks from software engineers and also ensuring adequate test coverage, Generative AI helps release faster with reduced defects and more innovative development cycles. This article explores the mechanics behind these AI-driven techniques and considers their potential benefits and drawbacks as well as future directions in software engineering.

Keywords

Generative AI, code automation, unit testing, software development, AI-driven testing

How to cite this paper

Allen R Chan "Generative AI: Automating Code and Unit Testing for Faster, High-Quality Development" Iconic Research And Engineering Journals Volume 6 Issue 7 2023 Page 527-537
Allen R Chan "Generative AI: Automating Code and Unit Testing for Faster, High-Quality Development" Iconic Research And Engineering Journals, vol. 6, no. 7, Jan. 2023
Allen R Chan (2023). Generative AI: Automating Code and Unit Testing for Faster, High-Quality Development. Iconic Research And Engineering Journals, 6(7).
Allen R Chan "Generative AI: Automating Code and Unit Testing for Faster, High-Quality Development" Iconic Research And Engineering Journals, vol. 6, no. 7, Jan. 2023.
@article{1703979,
      author = {Allen R Chan},
      title = {Generative AI: Automating Code and Unit Testing for Faster, High-Quality Development},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {7},
      pages = {527-537},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703979.pdf},
      abstract = {Automating two of the most timeconsuming tasks in software development - code generators and unit tests - Generative AI is transforming software. These modern AI models train using huge, real-world code repositories and apply state-of-the-art algorithms to deliver correct, high-quality code in minuscule times compared to traditional ways. They also create relevant and comprehensive test cases that keep pace with continuous changes made in the codebase. By taking over mundane tasks from software engineers and also ensuring adequate test coverage, Generative AI helps release faster with reduced defects and more innovative development cycles. This article explores the mechanics behind these AI-driven techniques and considers their potential benefits and drawbacks as well as future directions in software engineering.},
      keywords = {Generative AI, code automation, unit testing, software development, AI-driven testing},
      month = {January},
  }