activity
20112026
most citedA Research Roadmap for Augmenting Software Engineering Processes and Software Products with Generative AI

8 citations · 19 across the 10 of their papers we have counts for

collaborators

13 papers

cs.SE2026

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…

cs.AI2026

CVE2AP: Automated Generation of PDDL-Encoded Attack Paths via Large Language Models

Lin Cui, Vincenzo Scotti, Raffaela Mirandola

Attack Path (AP) modeling is fundamental to cybersecurity analysis, where the Planning Domain Definition Language (PDDL) has been widely adopted to encode APs into formal and machi…

cs.SE2026

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…

cs.SE2026

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…

cs.SE2025★ 8 cited

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…

cs.SE2025

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…

eess.SY2025

Surveying Uncertainty Representation: A Unified Model for Cyber-Physical Systems

Johannes Mäkelburg, Diego Perez-Palacin, Raffaela Mirandola +1

Cyber-Physical Systems (CPS) operate in dynamic environments, leading to different types of uncertainty. This work provides a comprehensive review of uncertainty representations an…

cs.SE2022

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…

cs.SE2021

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…

cs.SE2021★ 4 cited

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…

cs.CY2019★ 7 cited

Gender Balance in Computer Science and Engineering in Italian Universities

Moreno Marzolla, Raffaela Mirandola

Multiple studies have shown that gender balance in the fields of Science, Technology, Engineering and Maths -- and in particular in ICT -- is still far to be achieved. Several init…

cs.SE2019

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…

cs.DC2011

A Framework for QoS-aware Execution of Workflows over the Cloud

Moreno Marzolla, Raffaela Mirandola

The Cloud Computing paradigm is providing system architects with a new powerful tool for building scalable applications. Clouds allow allocation of resources on a "pay-as-you-go" m…