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07/20/2023
Boundary State Generation for Testing and Improvement of Autonomous Driving Systems
Recent advances in Deep Neural Networks (DNNs) and sensor technologies a...
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06/12/2023
Neural Embeddings for Web Testing
Web test automation techniques employ web crawlers to automatically prod...
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05/22/2023
Testing of Deep Reinforcement Learning Agents with Surrogate Models
Deep Reinforcement Learning (DRL) has received a lot of attention from t...
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05/14/2023
Two is Better Than One: Digital Siblings to Improve Autonomous Driving Testing
Simulation-based testing represents an important step to ensure the reli...
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04/05/2023
Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks
Recent decades have seen the rise of large-scale Deep Neural Networks (D...
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01/27/2023
Repairing DNN Architecture: Are We There Yet?
As Deep Neural Networks (DNNs) are rapidly being adopted within large so...
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12/21/2022
When and Why Test Generators for Deep Learning Produce Invalid Inputs: an Empirical Study
Testing Deep Learning (DL) based systems inherently requires large and r...
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12/14/2022
Uncertainty Quantification for Deep Neural Networks: An Empirical Comparison and Usage Guidelines
Deep Neural Networks (DNN) are increasingly used as components of larger...
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07/21/2022
A Forgotten Danger in DNN Supervision Testing: Generating and Detecting True Ambiguity
Deep Neural Networks (DNNs) are becoming a crucial component of modern s...
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05/02/2022
Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study)
Test Input Prioritizers (TIP) for Deep Neural Networks (DNN) are an impo...
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12/21/2021
Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems
Safe deployment of self-driving cars (SDC) necessitates thorough simulat...
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09/15/2021
DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score
Deep Learning (DL) components are routinely integrated into software sys...
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07/05/2021
DeepHyperion: Exploring the Feature Space of Deep Learning-Based Systems through Illumination Search
Deep Learning (DL) has been successfully applied to a wide range of appl...
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03/10/2021
A Review and Refinement of Surprise Adequacy
Surprise Adequacy (SA) is one of the emerging and most promising adequac...
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03/04/2021
GAssert: A Fully Automated Tool to Improve Assertion Oracles
This demo presents the implementation and usage details of GASSERT, the ...
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02/01/2021
Fail-Safe Execution of Deep Learning based Systems through Uncertainty Monitoring
Modern software systems rely on Deep Neural Networks (DNN) when processi...
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01/07/2021
Deep Reinforcement Learning for Black-Box Testing of Android Apps
The state space of Android apps is huge and its thorough exploration dur...
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12/29/2020
Uncertainty-Wizard: Fast and User-Friendly Neural Network Uncertainty Quantification
Uncertainty and confidence have been shown to be useful metrics in a wid...
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11/21/2020
An Empirical Study on Failed Error Propagation in Java Programs with Real Faults
During testing, developers can place oracles externally or internally wi...
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07/06/2020
Model-based Exploration of the Frontier of Behaviours for Deep Learning System Testing
With the increasing adoption of Deep Learning (DL) for critical tasks, s...
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02/05/2020
A Framework for In-Vivo Testing of Mobile Applications
The ecosystem in which mobile applications run is highly heterogeneous a...
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10/24/2019
Taxonomy of Real Faults in Deep Learning Systems
The growing application of deep neural networks in safety-critical domai...
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10/10/2019
Misbehaviour Prediction for Autonomous Driving Systems
Deep Neural Networks (DNNs) are the core component of modern autonomous ...
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05/01/2019