LLMs正在重塑软件开发，改变开发者角色。
LLMs: A Game-Changer for Software Engineers?
- 分析LLMs在代码生成与理解中的技术优势与局限
- 通过案例研究展示其对开发效率的实际提升
- 为开发者和团队提供拥抱LLMs的实践指南
大型语言模型（如GPT-3和GPT-4）作为突破性技术，具备生成类人文本、回应复杂问题甚至编写与解析代码的能力。这些模型基于海量数据训练，其潜力正在深刻改变软件工程领域，引发关于其变革性影响的广泛讨论。本文通过批判性分析技术优势、实际案例及未来方向，论证LLMs不仅重塑了软件开发方式，更在重新定义开发者角色。尽管仍存在挑战，但其带来的创新与协作机遇前所未有。早期采用是保持竞争力的关键。本文旨在帮助开发者、组织与研究者理解如何有效利用LLMs优化工作流并掌握必要技能。
原文摘要 · Abstract (English)
Large Language Models (LLMs) like GPT-3 and GPT-4 have emerged as groundbreaking innovations with capabilities that extend far beyond traditional AI applications. These sophisticated models, trained on massive datasets, can generate human-like text, respond to complex queries, and even write and interpret code. Their potential to revolutionize software development has captivated the software engineering (SE) community, sparking debates about their transformative impact. Through a critical analysis of technical strengths, limitations, real-world case studies, and future research directions, this paper argues that LLMs are not just reshaping how software is developed but are redefining the role of developers. While challenges persist, LLMs offer unprecedented opportunities for innovation and collaboration. Early adoption of LLMs in software engineering is crucial to stay competitive in this rapidly evolving landscape. This paper serves as a guide, helping developers, organizations, and researchers understand how to harness the power of LLMs to streamline workflows and acquire the necessary skills.
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