Conclusions
Embracing LLMs is definitely a correct and even necessary direction for software enterprises to improve quality and efficiency. However, achieving systematic and comprehensive intelligent software development still requires careful consideration and there is much fundamental work to do. For enterprises, solidifying the digitization and knowledge accumulation of software development, as well as the fundamental capabilities of software engineering such as requirement analysis, design, and validation, remains crucial and is also a basic condition for achieving higher levels of intelligent development. For academic research, there is still much work to do in the direction of systematic and comprehensive intelligent software development. This also requires us have a deeper understanding of the complexity of software systems and software requirements and design, based on understanding the capabilities of LLMs.
摘要
以ChatGPT为代表的大语言模型技术对包括软件工程在内的很多领域都带来巨大冲击, 也引发广泛焦虑. 为在迷雾中看清一点方向, 近期我们基于各种技术文献和实践分享以及我们自身的初步探索不断讨论和思考“大模型时代的软件工程”或者“大模型的软件开发能力”这一命题. 同时我也参加了几次线上访谈, 触发了更多认识和思考, 在此基础上撰写了此篇文章, 希望与大家分享一些观点并激发相关讨论. 由于到目前为止大模型在很大程度上仍然是一个黑盒, 并且大模型技术还在快速迭代和发展之中, 同时目前看到的以及我们自己实践的基于大模型的软件开发案例还比较初步, 因此本文的很多认识和思考不一定准确, 未来还可能会随着技术和实践的发展而不断刷新.
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Xin PENG declares that he has no conflict of interest.
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Xin PENG is Professor and Deputy Dean of School of Computer Science at Fudan University, China. He received his PhD in Computer Science from Fudan University in 2006. He is Deputy Director of CCF (China Computer Federation) Technical Committee on Software Engineering. He is Co-Editor-in-Chief of Journal of Software: Evolution and Process and serves on the editorial boards of reputable journals, such as ACM Transactions on Software Engineering and Methodology, Empirical Software Engineering, and Chinese Journal of Software. His research interests include intelligent software development, cloud native and artificial intelligence for IT operations (AIOps), and software development and testing for smart vehicle. His works won the Best Paper Award of ICSM 2011, the ACM SIGSOFT Distinguished Paper Award of ASE 2018/2021 and ICPC 2022, the IEEE TCSE Distinguished Paper Award of ICSME 2018/2019/2020 and SANER 2023, and IEEE Transactions on Software Engineering Best Paper Award for 2018.
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Peng, X. Software development in the age of intelligence: embracing large language models with the right approach. Front Inform Technol Electron Eng 24, 1513–1519 (2023). https://doi.org/10.1631/FITEE.2300537
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DOI: https://doi.org/10.1631/FITEE.2300537