用大模型自动完成安全分析，省时省力。
An LLM-Integrated Framework for Completion, Management, and Tracing of STPA
- 利用大模型自动化构建STPA安全分析模型
- 实测在真实项目中准确率高，显著减少人工耗时
- 开源工具适合安全工程与需求工程师使用
在众多安全关键型工程领域，危险分析是需求获取的重要环节。在诸多方法中，系统理论过程分析（STPA）是该领域较新的发展。然而，完成、管理及追溯这一分析流程对需求和安全工程师而言仍是一项耗时挑战。本文提出一个免费开源软件框架，通过大语言模型（LLMs）驱动的自动化工作流来构建STPA模型。过往研究已证明LLMs可成功集成至多个领域的工作流中。本文验证了LLMs在高精度完成与STPA相关任务中的有效性，显著节省人力投入。我们在需求工程师与研究人员构建的真实世界STPA模型上进行了实验验证。代码已公开：https://github.com/blueskysolarracing/stpa。
原文摘要 · Abstract (English)
In many safety-critical engineering domains, hazard analysis techniques are an essential part of requirement elicitation. Of the methods proposed for this task, STPA (System-Theoretic Process Analysis) represents a relatively recent development in the field. The completion, management, and traceability of this hazard analysis technique present a time-consuming challenge to the requirements and safety engineers involved. In this paper, we introduce a free, open-source software framework to build STPA models with several automated workflows powered by large language models (LLMs). In past works, LLMs have been successfully integrated into a myriad of workflows across various fields. Here, we demonstrate that LLMs can be used to complete tasks associated with STPA with a high degree of accuracy, saving the time and effort of the human engineers involved. We experimentally validate our method on real-world STPA models built by requirement engineers and researchers. The source code of our software framework is available at the following link: https://github.com/blueskysolarracing/stpa.
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