ERD

Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks

Project: PRECRIME

Updated at: 31-07-2024

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Generating and detecting true ambiguity: a forgotten danger in DNN supervision testing

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Updated at: 31-07-2024

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Testing of Deep Reinforcement Learning Agents with Surrogate Models

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Updated at: 31-07-2024

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Two is better than one: digital siblings to improve autonomous driving testing

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Updated at: 31-07-2024

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In vivo test and rollback of Java applications as they are

Project: PRECRIME

Updated at: 31-07-2024

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Uncertainty quantification for deep neural networks: An empirical comparison and usage guidelines

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Updated at: 27-04-2024

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Taxonomy of real faults in deep learning systems

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Updated at: 27-04-2024

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A Survey of Field-based Testing Techniques

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Updated at: 27-04-2024

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Mind the Gap! A Study on the Transferability of Virtual Versus Physical-World Testing of Autonomous Driving Systems

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Updated at: 27-04-2024

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GAssert: A Fully Automated Tool to Improve Assertion Oracles

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Updated at: 27-04-2024

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Simulation-based Test Case Generation for Unmanned Aerial Vehicles in the Neighborhood of Real Flights

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Updated at: 27-04-2024

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Deep Reinforcement Learning for Black-Box Testing of Android Apps

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Updated at: 27-04-2024

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Data Management Plan

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Updated at: 27-04-2024

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IFRIT: Focused Testing through Deep Reinforcement Learning

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Updated at: 27-04-2024

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An Empirical Validation of Oracle Improvement

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Updated at: 27-04-2024

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Testing machine learning based systems: a systematic mapping

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Updated at: 27-04-2024

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Testing the Plasticity of Reinforcement Learning-based Systems

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Updated at: 27-04-2024

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Toward In-Vivo Testing of Mobile Applications

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Updated at: 27-04-2024

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DeepCrime: mutation testing of deep learning systems based on real faults

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Updated at: 27-04-2024

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Misbehaviour prediction for autonomous driving systems

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Updated at: 27-04-2024

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Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study...

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Updated at: 27-04-2024

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DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score

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Updated at: 27-04-2024

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ThirdEye: Attention Maps for Safe Autonomous Driving Systems

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Updated at: 27-04-2024

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Repairing DNN Architecture: Are We There Yet?

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Updated at: 27-04-2024

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A Framework for In-Vivo Testing of Mobile Applications

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Updated at: 27-04-2024

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Confidence-driven Weighted Retraining for Predicting Safety-Critical Failures in Autonomous Driving Systems

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Updated at: 27-04-2024

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Model vs System Level Testing of Autonomous Driving Systems: A Replication and Extension Study

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Updated at: 27-04-2024

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Model-based exploration of the frontier of behaviours for deep learning system testing

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Updated at: 27-04-2024

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An Empirical Evaluation of Mutation Operators for Deep Learning Systems

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Updated at: 27-04-2024

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Fail-Safe Execution of Deep Learning based Systems through Uncertainty Monitoring

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Updated at: 27-04-2024

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Resources

Selected filters:

Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks

Generating and detecting true ambiguity: a forgotten danger in DNN supervision testing

Testing of Deep Reinforcement Learning Agents with Surrogate Models

Two is better than one: digital siblings to improve autonomous driving testing

In vivo test and rollback of Java applications as they are

Uncertainty quantification for deep neural networks: An empirical comparison and usage guidelines

Taxonomy of real faults in deep learning systems

A Survey of Field-based Testing Techniques

Mind the Gap! A Study on the Transferability of Virtual Versus Physical-World Testing of Autonomous Driving Systems

GAssert: A Fully Automated Tool to Improve Assertion Oracles

Simulation-based Test Case Generation for Unmanned Aerial Vehicles in the Neighborhood of Real Flights

Deep Reinforcement Learning for Black-Box Testing of Android Apps

Data Management Plan

IFRIT: Focused Testing through Deep Reinforcement Learning

An Empirical Validation of Oracle Improvement

Testing machine learning based systems: a systematic mapping

Testing the Plasticity of Reinforcement Learning-based Systems

Toward In-Vivo Testing of Mobile Applications

DeepCrime: mutation testing of deep learning systems based on real faults

Misbehaviour prediction for autonomous driving systems

Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study...

DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score

ThirdEye: Attention Maps for Safe Autonomous Driving Systems

Repairing DNN Architecture: Are We There Yet?

A Framework for In-Vivo Testing of Mobile Applications

Confidence-driven Weighted Retraining for Predicting Safety-Critical Failures in Autonomous Driving Systems

Model vs System Level Testing of Autonomous Driving Systems: A Replication and Extension Study

Model-based exploration of the frontier of behaviours for deep learning system testing

An Empirical Evaluation of Mutation Operators for Deep Learning Systems

Fail-Safe Execution of Deep Learning based Systems through Uncertainty Monitoring