An LLM-Integrated Framework for Completion, Management, and Tracing of STPA
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913738075930624 |
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| author | Raeisdanaei, Ali Kim, Juho Liao, Michael Kochhar, Sparsh |
| author_facet | Raeisdanaei, Ali Kim, Juho Liao, Michael Kochhar, Sparsh |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_12043 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An LLM-Integrated Framework for Completion, Management, and Tracing of STPA Raeisdanaei, Ali Kim, Juho Liao, Michael Kochhar, Sparsh Software Engineering Artificial Intelligence 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. |
| title | An LLM-Integrated Framework for Completion, Management, and Tracing of STPA |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2503.12043 |