This paper explores the use of Large Language Models (LLMs) and in particular ChatGPT in programming, source code analysis, and code generation. LLMs and ChatGPT are built using machine learning and artificial intelligence techniques, and they offer several benefits to developers and programmers. While these models can save time and provide highly accurate results, they are not yet advanced enough to replace human programmers entirely. The paper investigates the potential applications of LLMs and ChatGPT in various areas, such as code creation, code documentation, bug detection, refactoring, and more. The paper also suggests that the usage of LLMs and ChatGPT is expected to increase in the future as they offer unparalleled benefits to the programming community.
@article{arxiv.2306.00597,
title = {Analysis of ChatGPT on Source Code},
author = {Ahmed R. Sadik and Antonello Ceravola and Frank Joublin and Jibesh Patra},
journal= {arXiv preprint arXiv:2306.00597},
year = {2023}
}
Comments
40 pages, examples provided for each experiment. arXiv admin note: text overlap with arXiv:2107.03374 by other authors