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From the 1 of 7 linked papers with an AI index.

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7 papers

cs.SE2026

When Knowledge Changes: Metamorphic Testing of RAG Systems with Mutations

Jinhan Kim, Samuele Pasini, Paolo Tonella

The paper proposes a metamorphic testing framework that assesses how Retrieval‑Augmented Generation (RAG) systems behave when their underlying document corpora change, using a taxo…

cs.SE2026

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-…

cs.CR2026

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…

cs.AI2026

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…

cs.SE2026

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…

cs.SE2025

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…