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ZENODO
Software . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
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Reproducing the Experiments of Automated Self-Explanation of Expected versus Perceived Behavior for Interacting Digital Systems

Authors: Alkhiyami, Mohammad; Martino, Gianluca; Fey, Goerschwin;

Reproducing the Experiments of Automated Self-Explanation of Expected versus Perceived Behavior for Interacting Digital Systems

Abstract

This repository contains the source code and experimental artifacts accompanying the paper: M. Alkhiyami, G. Martino, and G. Fey, Automated Self-Explanation of Expected versus Perceived Behavior for Interacting Digital Systems, Design, Automation and Test in Europe Conference (DATE), 2026. The artifacts implement the algorithm for automatically generating explanations of mismatches between expected and perceived behavior in interacting digital systems, as presented in the paper. The implementation follows the bounded model checking and SMT-based formulation described in Sections IV–V. The experimental artifacts make use of the DuRTL framework, which provides the infrastructure for hardware model parsing and SMT-based bounded model checking. Contents Source code implementing the explanation algorithm Models of interacting systems (Mealy machines and assumptions) Experimental setups for the wind park–turbine and traffic controller–autonomous vehicles case studies Scripts and configuration files used to reproduce the reported experiments and results PurposeThe artifacts are provided to support transparency, reproducibility, and further research on self-explaining interacting digital systems.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average