8 citations · 19 across the 10 of their papers we have counts for
9 papers · 1 filter
Mitigating Uncertainty Interactions in GenAI-based Adaptive Systems: Vision, Challenges and Preliminary Guidelines
Karthik Vaidhyanathan, Norha Villegas, Raffaela Mirandola +5
Modern software-intensive systems increasingly incorporate GenAI components, including LLM and agentic subsystems, which introduce novel and compounding sources of uncertainty acro…
Runtime Enforcement for Operationalizing Ethics in Autonomous Systems
Martina De Sanctis, Gianluca Filippone, Paola Inverardi +3
This paper addresses the challenge of operationalizing ethics in autonomous systems through runtime enforcement. It first conceptualizes the system's ethical space and outlines a s…
Beyond Monolithic Models: Symbolic Seams for Composable Neuro-Symbolic Architectures
Nicolas Schuler, Vincenzo Scotti, Raffaela Mirandola
Current Artificial Intelligence (AI) systems are frequently built around monolithic models that entangle perception, reasoning, and decision-making, a design that often conflicts w…
A Research Roadmap for Augmenting Software Engineering Processes and Software Products with Generative AI
Domenico Amalfitano, Andreas Metzger, Marco Autili +8
Generative AI (GenAI) is rapidly transforming software engineering (SE) practices, influencing how SE processes are executed, as well as how software systems are developed, operate…
A Roadmap for Tamed Interactions with Large Language Models
Vincenzo Scotti, Jan Keim, Tobias Hey +3
Large Language Models (LLMs) are increasingly embedded in software systems ( GenAIware), enabling new forms of automation and interaction However, their probabilistic nature and re…
Specification Architectural Viewpoint for Benefit-Cost-Risk-Aware Decision-Making in Self-Adaptive Systems
Danny Weyns, Paris Avegriou, Radu Calinescu +3
Over the past two decades, researchers and engineers have extensively studied the problem of how to enable a software system to deal with uncertain operating conditions. One promin…
Quantitative Verification with Adaptive Uncertainty Reduction
Naif Alasmari, Radu Calinescu, Colin Paterson +1
Stochastic models are widely used to verify whether systems satisfy their reliability, performance and other nonfunctional requirements. However, the validity of the verification d…
Uncertainty in Self-Adaptive Systems: A Research Community Perspective
Sara M. Hezavehi, Danny Weyns, Paris Avgeriou +3
One of the primary drivers for self-adaptation is ensuring that systems achieve their goals regardless of the uncertainties they face during operation. Nevertheless, the concept of…
Perpetual Assurances for Self-Adaptive Systems
Danny Weyns, Nelly Bencomo, Radu Calinescu +10
Providing assurances for self-adaptive systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplet…