规范驱动开发作为人工智能原生企业软件工程的基础
Specification-Driven Development as the Foundation of AI-Native Enterprise Software Engineering
AI总结：
研究大语言模型和智能人工智能推动下软件工程范式转变，介绍规范驱动开发，提出规范治理参考模型，经评估能减少安全缺陷、缩短上市时间，证明企业软件需规范治理，vibe编码适用于构思和快速原型制作。
AI中文摘要：
大语言模型和智能人工智能正在将软件工程从手动编码转向意图规范、架构和治理。出现了两种范式：直觉驱动的vibe编码和使用结构化规范作为权威真理来源的规范驱动开发（SDD）。本文有三个贡献。首先，识别无治理对话生成的失败模式。其次，引入规范治理参考模型（SGRM），它定义了四组件规范合同等。第三，根据ISO/IEC 25010评估SGRM。实证证据支持此，通过规范治理交付，安全缺陷减少73%，上市时间减少50%。分析得出企业软件需要规范治理。还讨论了边界条件等。
英文摘要：
Large language models (LLMs) and agentic AI are shifting software engineering from manual coding toward intent specification, architecture, and governance. Two paradigms have emerged: vibe coding, an intuition-driven approach accepting AI artifacts via observed behavior, and Specification-Driven Development (SDD), which uses structured specifications as the authoritative source of truth. This article makes three contributions. First, based on a verified literature corpus, it identifies failure modes of ungoverned conversational generation: the productivity-reliability paradox, architectural erosion from limited context, security exposure, and technical debt. Second, it introduces the Specification Governance Reference Model (SGRM). This tool-independent framework defines four-component specification contracts, constrains stochastic generation via deterministic validation, formalizes three rigor levels, and integrates generation, verification, and governance into a closed-loop architecture. Third, it evaluates SGRM against ISO/IEC 25010, mapping quality characteristics to governance mechanisms. Empirical evidence supports this, reporting a 73% reduction in security defects under constitutional constraints and a 50% reduction in time-to-market through specification-governed agentic delivery. The analysis concludes that while vibe coding is valuable for ideation and rapid prototyping, enterprise software requires specification governance to transform probabilistic AI generation into deterministic, auditable engineering. Boundary conditions, threats to validity, and future research directions are discussed.
