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    28 repositories

    • adaptive-tg-qgrams

      Public
      Replication package for the arxiv submission: "Adaptive Test Generation with Qgrams".
      Java
      •
      MIT License
      •0•0•0•0•Updated Oct 23, 2024Oct 23, 2024

    • genbo

      Public
      Replication package for the paper "Boundary State Generation for Testing and Improvement of Autonomous Driving Systems"
      Python
      •
      MIT License
      •1•0•0•0•Updated Oct 10, 2024Oct 10, 2024

    • muPRL

      Public
      Replication package for the paper "μPRL: a Mutation Testing Pipeline for Deep Reinforcement Learning based on Real Faults" ICSE 2025.
      Python
      •
      MIT License
      •0•2•0•0•Updated Aug 15, 2024Aug 15, 2024

    • deepjanus

      Public
      Tools and data of the paper "Model-based Exploration of the Frontier of Behaviours for Deep Learning System Testing"
      Python
      •
      MIT License
      •8•15•0•0•Updated Jul 9, 2024Jul 9, 2024

    • maxitwo

      Public
      Replication package of the paper "Two is Better Than One: Digital Siblings to Improve Autonomous Driving Testing"
      Python
      •
      MIT License
      •1•3•0•0•Updated Mar 26, 2024Mar 26, 2024

    • adversarial-rl-icst-2024

      Public
      Replication package for the paper "Adversarial Testing with Reinforcement Learning: A Case Study on Autonomous Driving"
      Python
      •
      MIT License
      •0•0•0•0•Updated Jan 18, 2024Jan 18, 2024

    • tig-validity-icse23

      Public
      Python
      •
      MIT License
      •3•4•1•0•Updated Oct 31, 2023Oct 31, 2023

    • ambguess-src

      Public archive
      Python
      •
      MIT License
      •0•0•0•0•Updated Sep 23, 2023Sep 23, 2023

    • ambiguous-datasets

      Public
      MIT License
      •0•0•0•0•Updated Sep 23, 2023Sep 23, 2023

    • deepatash

      Public
      focused test generation for DL systems
      Python
      •
      MIT License
      •1•1•0•1•Updated Aug 28, 2023Aug 28, 2023

    • uncertainty-wizard

      Public
      Uncertainty-Wizard is a plugin on top of tensorflow.keras, allowing to easily and efficiently create uncertainty-aware deep neural networks. Also useful if you want to train multiple small models in parallel.
      testingkerasuncertaintyuncertainty-neural-networksuncertainty-quantificationkeras-tensorflow
      Python
      •
      MIT License
      •6•43•2•5•Updated May 24, 2023May 24, 2023

    • bisupervised

      Public archive
      TOSEM paper replication package
      PureBasic
      •
      MIT License
      •0•1•0•0•Updated May 24, 2023May 24, 2023

    • DeepHyperion

      Public
      Python
      •
      MIT License
      •7•9•0•0•Updated May 4, 2023May 4, 2023

    • fashion-mnist-c

      Public archive
      Python
      •
      MIT License
      •1•3•0•0•Updated Feb 3, 2023Feb 3, 2023

    • dnn-tip

      Public
      A collection of dnn test input prioritizers often used as benchmarks in recent literature.
      Python
      •
      MIT License
      •2•13•1•0•Updated Feb 3, 2023Feb 3, 2023

    • unboxer

      Public
      An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours
      HTML
      •0•1•0•0•Updated Jan 11, 2023Jan 11, 2023

    • repli-stvr2022-uncertainty

      Public archive
      Python
      •
      MIT License
      •0•0•0•0•Updated Dec 9, 2022Dec 9, 2022

    • rl-plasticity-experiments

      Public
      Source code and data for the paper "Testing the Plasticity of Reinforcement Learning Based Systems"
      Python
      •
      MIT License
      •0•2•0•0•Updated Aug 25, 2022Aug 25, 2022

    • simple-tip

      Public archive
      This is the reproduction package of the paper Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning by M.Weiss and P.Tonella, published at ISSTA 2022
      active-learningreplication-studytest-prioritizationissta-2022machine-learningdeep-learningreproducible-research
      Python
      •
      MIT License
      •3•4•0•0•Updated Jun 23, 2022Jun 23, 2022

    • surprise-adequacy

      Public archive
      Python
      •
      MIT License
      •0•11•0•0•Updated May 25, 2022May 25, 2022

    • corrupted-text

      Public
      A python library to generate out-of-distribution text datasets. Specifically, the library applies model-independent, commonplace corruptions (not model-specific, worst-case adversarial corruptions). We thus aim to allow benchmark-studies regarding robustness against realistic outliers.
      Python
      •
      MIT License
      •0•1•0•0•Updated Apr 26, 2022Apr 26, 2022

    • jsep2021-replication-package-material

      Public
      Python
      •
      MIT License
      •1•5•0•0•Updated Nov 12, 2021Nov 12, 2021

    • deepmetis

      Public
      Python
      •
      MIT License
      •0•9•0•0•Updated Aug 20, 2021Aug 20, 2021

    • deepthoughts

      Public
      0•1•0•0•Updated Jul 2, 2021Jul 2, 2021

    • selforacle

      Public archive
      The code of our paper "Misbehaviour Prediction for Autonomous Driving Systems", including our improved Udacity simulator
      Python
      •
      MIT License
      •11•21•0•0•Updated Jun 30, 2021Jun 30, 2021

    • urop-2021-exercise

      Public
      Repository for UROP 2021 exercise
      Python
      •6•0•0•0•Updated Mar 3, 2021Mar 3, 2021

    • repli-ensemble-bench

      Public archive
      Python
      •
      MIT License
      •0•0•0•0•Updated Dec 21, 2020Dec 21, 2020

    • repli-icst2021-uncertainty

      Public archive
      Source Code of the ICST 2021 paper "Fail-Safe Execution of Deep Learning based Systems through Uncertainty"
      Python
      •
      MIT License
      •0•0•0•0•Updated Dec 20, 2020Dec 20, 2020