在LGPD背景下简化需求工程：一项基于大语言模型（LLM）的研究
Simplifying Requirements Engineering in the Context of the LGPD: An LLM-Based Investigation
AI总结：
本研究针对隐私法规合规转化为软件需求的挑战，探究LLM在LGPD框架下简化需求工程的可行性，提出利用法规自动生成用户故事和验收测试场景的方法，验证其能从软件初期确保合规。
AI中文摘要：
隐私法规合规对需求工程（RE）构成复杂挑战，需将法律规范转化为软件需求。本研究在巴西通用数据保护法（LGPD）框架下，探究大语言模型（LLM）能否简化需求工程。所提方法利用现行法规自动生成用户故事和验收测试场景。评估结果显示性能优异，证实LLM具备从软件设计初期确保监管合规的潜力。
英文摘要：
Compliance with privacy legislation poses a complex challenge to Requirements Engineering (RE): translating legal norms into software requirements. In this context, this study investigates whether Large Language Models (LLMs) can simplify RE within the framework of the Brazilian General Data Protection Law (LGPD). The proposed approach utilizes current legislation to automatically generate User Stories and Acceptance Test Scenarios. The evaluation results demonstrated high performance, confirming the potential of LLMs to ensure regulatory compliance from the software's inception.
