2 citations · 5 across the 12 of their papers we have counts for
5 papers · 1 filter
IaC Generation with LLMs: An Error Taxonomy and A Study on Configuration Knowledge Injection
Roman Nekrasov, Stefano Fossati, Indika Kumara +2
Large Language Models (LLMs) currently exhibit low success rates in generating correct and intent-aligned Infrastructure as Code (IaC). This research investigated methods to improv…
"Show Me You Comply... Without Showing Me Anything": Zero-Knowledge Software Auditing for AI-Enabled Systems
Filippo Scaramuzza, Renato Cordeiro Ferreira, Giovanni Quattrocchi +2
Classical software verification and validation techniques, such as procedural audits, formal methods, or model documentation, are the traditional mechanisms used to achieve the ver…
Accountability of Robust and Reliable AI-Enabled Systems: A Preliminary Study and Roadmap
Filippo Scaramuzza, Damian A. Tamburri, Willem-Jan van den Heuvel
This vision paper presents initial research on assessing the robustness and reliability of AI-enabled systems, and key factors in ensuring their safety and effectiveness in practic…
Chaos Engineering in the Wild: Findings from GitHub
Joshua Owotogbe, Indika Kumara, Dario Di Nucci +2
Chaos Engineering (CE) enhances system resilience by deliberately injecting faults to uncover weaknesses before they cause outages. Despite the availability of many CE tools, littl…
Recursive Self-Similarity in Deep Weight Spaces of Neural Architectures: A Fractal and Coarse Geometry Perspective
Ambarish Moharil, Indika Kumara, Damian Andrew Tamburri +2
This paper conceptualizes the Deep Weight Spaces (DWS) of neural architectures as hierarchical, fractal-like, coarse geometric structures observable at discrete integer scales thro…