1 citations · 1 across the 2 of their papers we have counts for
10 papers
Simulator Ensembles for Trustworthy Autonomous Driving Systems Testing
Lev Sorokin, Matteo Biagiola, Andrea Stocco
Scenario-based testing with driving simulators is extensively used to identify failing conditions of automated driving assistance systems (ADAS). However, existing studies have sho…
The Alignment Problem in Constrained Code Generation
Matteo Biagiola, Jahrim Gabriele Cesario, Luca Di Grazia +2
Large Language Models (LLMs) have demonstrated strong capabilities in code generation, but their outputs frequently contain syntax or type errors that result in compilation failure…
AgentBound: Securing Execution Boundaries of AI Agents
Christoph Bühler, Matteo Biagiola, Luca Di Grazia +1
Large Language Models (LLMs) have evolved into AI agents that interact with external tools and environments to perform complex tasks. The Model Context Protocol (MCP) has become th…
Towards Automated Page Object Generation for Web Testing using Large Language Models
Betül Karagöz, Filippo Ricca, Matteo Biagiola +1
Page Objects (POs) are a widely adopted design pattern for improving the maintainability and scalability of automated end-to-end web tests. However, creating and maintaining POs is…
Neural Embeddings for Web Testing
Kasun Kanaththage, Luigi Libero Lucio Starace, Matteo Biagiola +2
Web test automation techniques often rely on crawlers to infer models of web applications for automated test generation. However, current crawlers rely on state equivalence algorit…
XMutant: XAI-based Fuzzing for Deep Learning Systems
Xingcheng Chen, Matteo Biagiola, Vincenzo Riccio +2
Semantic-based test generators are widely used to produce failure-inducing inputs for Deep Learning (DL) systems. They typically generate challenging test inputs by applying random…