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CVE2AP is proposed, an LLM-based approach for automatically generating PDDL-encoded attack paths from natural language CVE (Common Vulnerability Exposure) descriptions that leverages structured prompting and incorporates an error-feedback mechanism that iteratively refines the generated paths using planner-reported syn...
When developing complex, software-intensive or cyber-physical systems, uncertainty must be managed during all stages. Especially if made explicit, it can significantly affect the design decisions of various stakeholders. A necessary requirement for determining the effect of uncertainty on a system and deciding whether...
This roadmap paper reports the outcomes of the NII Shonan Seminar No. 232 on Uncertainty Interaction in Software-Intensive Systems (UNISON), held in March 2026 and develops a shared conceptual vocabulary for distinguishing uncertainty sources, propagation, confluence, interaction, and relevance; proposes an abstract wo...
Verify, Augment, and Improve (VAI), a framework that extends a standard MAPE–K architecture with an asynchronous self-improving loop that intercepts ineffective adaptation actions and turns explanations from a descriptive aid into a mechanism for continual improvement of the self-adaptation process.
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