Automated self-explanation of expected versus perceived behavior for interacting digital systems

Modern interacting digital systems are becoming increasingly complex, making it difficult to ensure their actual behavior aligns with design-time expectations, particularly in uncertain or dynamic environments, even when specifications are correct. This misalignment affects system scalability, reliability, and increases maintenance costs. We introduce a conceptual framework for identifying and self-explaining mismatches between expected and observed system behavior, together with an algorithm that generates explanations and case studies that apply the conceptual framework for explanation generation in an interacting digital systems setting.

Subjects

action-oriented explanation

and cyber-physical systems

Formal methods

knowledge representation and reasoning

logic and verification

model checking

DDC Class

004: Computer Sciences

600: Technology

Options

Automated self-explanation of expected versus perceived behavior for interacting digital systems