Assurance Cases (ACs) are structured arguments intended to show that a system is safe. ACs require continuous maintenance through their life cycle, and manual review is often required to determine how an AC may be impacted by different update scenarios. This is expensive and error-prone as ACs can be large and complex. In this vision paper, we present challenges and opportunities for leveraging large language models to support change impact assessment for ACs.

(2024). Supporting Change Impact Assessment with LLMs . Retrieved from https://hdl.handle.net/10446/293230

Supporting Change Impact Assessment with LLMs

Menghi, Claudio;
2024-01-01

Abstract

Assurance Cases (ACs) are structured arguments intended to show that a system is safe. ACs require continuous maintenance through their life cycle, and manual review is often required to determine how an AC may be impacted by different update scenarios. This is expensive and error-prone as ACs can be large and complex. In this vision paper, we present challenges and opportunities for leveraging large language models to support change impact assessment for ACs.
2024
Viger, Torin; Murphy, Logan; Diemert, Simon; Menghi, Claudio; Chechik, Marsha
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/293230
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