1 citations · 1 across the 7 of their papers we have counts for
7 papers
When Knowledge Changes: Metamorphic Testing of RAG Systems with Mutations
Jinhan Kim, Samuele Pasini, Paolo Tonella
Retrieval-Augmented Generation (RAG)-based LLM systems rely on external document corpora that can evolve and change over time. However, current evaluation methodologies (e.g., RAGA…
Testing Retrieval-Augmented Generation Systems with Chunk Coverage
Jinhan Kim, Samuele Pasini, Paolo Tonella
Retrieval-Augmented Generation (RAG)-based systems\footnote{For brevity, RAG-based systems are referred to as RAG systems throughout this paper.} are increasingly deployed in high-…
Detecting Trojaned DNNs via Spectral Regression Analysis
Samuele Pasini, Jinhan Kim, Paolo Tonella
Modern DNNs are repeatedly fine-tuned to incorporate new data and functionality. This evolutionary workflow introduces a security risk when updated data cannot be fully trusted, as…
DeepTest Tool Competition 2026: Benchmarking an LLM-Based Automotive Assistant
Lev Sorokin, Ivan Vasilev, Samuele Pasini
This report summarizes the results of the first edition of the Large Language Model (LLM) Testing competition, held as part of the DeepTest workshop at ICSE 2026. Four tools compet…
Rulebook: bringing co-routines to reinforcement learning environments
Massimo Fioravanti, Samuele Pasini, Giovanni Agosta
Reinforcement learning (RL) algorithms, due to their reliance on external systems to learn from, require digital environments (e.g., simulators) with very simple interfaces, which…
Cross-site scripting adversarial attacks based on deep reinforcement learning: Evaluation and extension study
Samuele Pasini, Gianluca Maragliano, Jinhan Kim +1
Cross-site scripting (XSS) poses a significant threat to web application security. While Deep Learning (DL) has shown remarkable success in detecting XSS attacks, it remains vulner…
Evaluating and Improving the Robustness of Security Attack Detectors Generated by LLMs
Samuele Pasini, Jinhan Kim, Tommaso Aiello +3
Large Language Models (LLMs) are increasingly used in software development to generate functions, such as attack detectors, that implement security requirements. A key challenge is…