6 papers
Enhancing Understandability and Transparency of Research Software: Tracing Research to Code
Adrian Bajraktari, Andreas Vogelsang
Modern research heavily relies on software. A significant challenge researchers face is understanding the complex software used in specific research fields. We target two scenarios…
Disguising Topology and Side-Channel Information through Covert Gate- and ML-Enabled IP Camouflaging
Junling Fan, David Koblah, Domenic Forte
Semiconductor intellectual property (IP) theft incurs hundreds of billions in annual losses, driven by advanced reverse engineering (RE) techniques. Traditional ``cryptic'' IC camo…
V-SHiNE: A Virtual Smart Home Framework for Explainability Evaluation
Mersedeh Sadeghi, Simon Scholz, Max Unterbusch +1
Explanations are essential for helping users interpret and trust autonomous smart-home decisions, yet evaluating their quality and impact remains methodologically difficult in this…
From Issues to Insights: RAG-based Explanation Generation from Software Engineering Artifacts
Daniel Pöttgen, Mersedeh Sadeghi, Max Unterbusch +1
The increasing complexity of modern software systems has made understanding their behavior increasingly challenging, driving the need for explainability to improve transparency and…
Context-Adaptive Requirements Defect Prediction through Human-LLM Collaboration
Max Unterbusch, Andreas Vogelsang
Automated requirements assessment traditionally relies on universal patterns as proxies for defectiveness, implemented through rule-based heuristics or machine learning classifiers…
Description and Comparative Analysis of QuRE: A New Industrial Requirements Quality Dataset
Henning Femmer, Frank Houdek, Max Unterbusch +1
Requirements quality is central to successful software and systems engineering. Empirical research on quality defects in natural language requirements relies heavily on datasets, i…