2 citations · 5 across the 12 of their papers we have counts for
6 papers · 1 filter
Actionable Meta-Requirements for AI Robustness Auditing
Joshua Owotogbe, Roya Nasiri, Indika Kumara +2
AI-enabled systems must remain dependable when the conditions under which they operate change (e.g., due to input perturbations, distribution shifts, or changes in external depende…
Sustainability of Open-Source Machine Learning Robustness Assessment Tools: A Repository Mining Study
Joshua Owotogbe, Indika Kumara, Willem-Jan van den Heuvel +1
Robustness evaluation is essential for deploying machine-learning (ML) systems in real-world settings, where models may face adversarial perturbations, distribution shifts, and oth…
AIGen: Automating AI Bill of Materials Generation Through Hybrid MLOps Integration
Federica Pepe, Daniele Bifolco, Costantino Martignetti +4
The responsible development and deployment of artificial intelligence (AI) systems requires rigorous documentation of their constituent artifacts, e.g., datasets, model weights, tr…
Tiny Machine-Learning Operations within Cyber-Physical Systems: a Field Study
Filippo Scaramuzza, Damian A. Tamburri
Machine-Learning Operations (MLOps) is maturing into a software-engineering discipline, yet its tiny-scale variant (TinyMLOps)-targeting the resource-constrained microcontrollers e…
A Taxonomy of Runtime Faults in Model Context Protocol Servers
Joshua Owotogbe, Indika Kumara, Willem-Jan van den Heuvel +3
MCP (Model Context Protocol) enables LLMs (Large Language Models) to interact with external tools and data sources via a standardized protocol. Its rapid adoption in tool-augmented…
Privacy Engineering: A Systematic Literature Review
Nemania Borovits, Damian Andrew Tamburri, Willem-Jan van den Heuvel
Privacy obligations under GDPR increasingly shape software engineering. We synthesize 90 studies from 2018 to 2025 using a systematic review with thematic synthesis to chart privac…