CLC number:
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2023-09-25
Cited: 0
Clicked: 1509
Xin PENG. Software development in the age of intelligence: embracing large language models with the right approach[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(11): 1513-1519.
@article{title="Software development in the age of intelligence: embracing large language models with the right approach",
author="Xin PENG",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="24",
number="11",
pages="1513-1519",
year="2023",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300537"
}
%0 Journal Article
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%A Xin PENG
%J Frontiers of Information Technology & Electronic Engineering
%V 24
%N 11
%P 1513-1519
%@ 2095-9184
%D 2023
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2300537
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T1 - Software development in the age of intelligence: embracing large language models with the right approach
A1 - Xin PENG
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 24
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SP - 1513
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%@ 2095-9184
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2300537
Abstract: The emergence of large language models (LLMs), represented by ChatGPT, has had a profound impact on various fields, including software engineering, and has also aroused widespread concerns. To see a right way through the fog, we have recently been discussing and contemplating a theme of “software development in the age of LLMs,” or rather “the capability of LLMs in software development,” based on various technical literature, shared experiences, and our own preliminary explorations. Additionally, I have participated in several online interviews and discussions on the theme, which have triggered further insights and reflections. Based on the aforementioned thinking and discussions, this article has been composed to disseminate information and foster an open discussion within the academic community. LLMs still largely remain a black box, and the technology is still rapidly iterating and evolving. Moreover, the existing cases reported by practitioners and our own practical experiences with LLM-based software development are relatively limited. Therefore, many of the insights and reflections in this article may not be accurate, and they may be constantly refreshed as technology and practice continue to develop.
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