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Publikation

On the Origins of Self-Explainability in Cyber-Physical Systems: Model-Based and Data-Driven Approaches

Laleh Akbari; Rolf Drechsler
In: 29. Workshop zu Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (MBMV). ITG/GMM/GI-Workshop "Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen" (MBMV-2026), March 17-18, 2026.

Zusammenfassung

Cyber-Physical Systems (CPS) operate in complex environments where system behavior results from the interaction of software, physical processes, and changing external conditions. This inherent complexity makes it difficult to fully understand, verify, or explain how such systems behave. Explainability has therefore become an important system property, helping users make sense of system decisions, supporting developers in diagnosing unexpected behavior, and enabling systems to justify actions of other cooperating systems. This review classifies work in explainability according to a fundamental question: which system artifact is used to generate an explanation? Based on this criterion, we distinguish between model-based and data-driven approaches. The discussion considers how these approaches generate explanations, what assumptions they rely on, and the constraints that affect their practical use, while also pointing to issues that remain insufficiently addressed.