AI让软件开发更敏捷，自动完成需求、编码和测试。
Artificial Intelligence as a Catalyst for Innovation in Software Engineering
- 用机器学习和自然语言处理自动化需求管理与代码生成。
- 调查显示78%开发者认为AI提升了开发效率与产品质量。
- 适合关注AI赋能软件工程的开发者与技术管理者。
现代软件需求的快速演进与固有复杂性要求高度灵活和响应迅速的开发方法。尽管敏捷框架已成为行业标准，强调迭代、协作与适应性，但开发团队仍面临需求持续变化和紧赶工期下保障产品品质的挑战。本文探讨人工智能（AI）与软件工程（SE）的交汇点，分析AI如何成为提升敏捷性与推动创新的强大催化剂。研究结合文献综述与实证调查，通过面向软件工程专业人士的问卷，评估对AI驱动工具的认知、采纳及其影响。关键发现表明，通过机器学习（ML）和自然语言处理（NLP）实现的AI集成，显著实现了从需求管理到代码生成与测试等繁琐任务的自动化。本文证明，AI不仅优化现有敏捷实践，还引入了未来软件开发中维持质量、速度与创新所必需的新能力。
原文摘要 · Abstract (English)
The rapid evolution and inherent complexity of modern software requirements demand highly flexible and responsive development methodologies. While Agile frameworks have become the industry standard for prioritizing iteration, collaboration, and adaptability, software development teams continue to face persistent challenges in managing constantly evolving requirements and maintaining product quality under tight deadlines. This article explores the intersection of Artificial Intelligence (AI) and Software Engineering (SE), to analyze how AI serves as a powerful catalyst for enhancing agility and fostering innovation. The research combines a comprehensive review of existing literature with an empirical study, utilizing a survey directed at Software Engineering professionals to assess the perception, adoption, and impact of AI-driven tools. Key findings reveal that the integration of AI (specifically through Machine Learning (ML) and Natural Language Processing (NLP) )facilitates the automation of tedious tasks, from requirement management to code generation and testing . This paper demonstrates that AI not only optimizes current Agile practices but also introduces new capabilities essential for sustaining quality, speed, and innovation in the future landscape of software development.
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