97 citations · 156 across the 8 of their papers we have counts for
9 papers
Efficient Domain Augmentation for Autonomous Driving Testing Using Diffusion Models
Luciano Baresi, Davide Yi Xian Hu, Andrea Stocco +1
Simulation-based testing is widely used to assess the reliability of Autonomous Driving Systems (ADS), but its effectiveness is limited by the operational design domain (ODD) condi…
A Multi-Year Grey Literature Review on AI-assisted Test Automation
Filippo Ricca, Alessandro Marchetto, Andrea Stocco
Context: Test Automation (TA) techniques are crucial for quality assurance in software engineering but face limitations such as high test suite maintenance costs and the need for e…
Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantification
Ruben Grewal, Paolo Tonella, Andrea Stocco
The automated real-time recognition of unexpected situations plays a crucial role in the safety of autonomous vehicles, especially in unsupported and unpredictable scenarios. This…
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…
Two is Better Than One: Digital Siblings to Improve Autonomous Driving Testing
Matteo Biagiola, Andrea Stocco, Vincenzo Riccio +1
Simulation-based testing represents an important step to ensure the reliability of autonomous driving software. In practice, when companies rely on third-party general-purpose simu…
Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems
Andrea Stocco, Brian Pulfer, Paolo Tonella
Safe deployment of self-driving cars (SDC) necessitates thorough simulated and in-field testing. Most testing techniques consider virtualized SDCs within a simulation environment,…
Taxonomy of Real Faults in Deep Learning Systems
Nargiz Humbatova, Gunel Jahangirova, Gabriele Bavota +3
The growing application of deep neural networks in safety-critical domains makes the analysis of faults that occur in such systems of enormous importance. In this paper we introduc…
Misbehaviour Prediction for Autonomous Driving Systems
Andrea Stocco, Michael Weiss, Marco Calzana +1
Deep Neural Networks (DNNs) are the core component of modern autonomous driving systems. To date, it is still unrealistic that a DNN will generalize correctly in all driving condit…
Web Test Dependency Detection
Matteo Biagiola, Andrea Stocco, Ali Mesbah +2
E2E web test suites are prone to test dependencies due to the heterogeneous multi-tiered nature of modern web apps, which makes it difficult for developers to create isolated progr…