TrustAI / DeepCover
Testing Deep Neural Networks
☆15Updated 6 years ago
Related projects ⓘ
Alternatives and complementary repositories for DeepCover
- ☆24Updated 3 years ago
- Code release of a paper "Guiding Deep Learning System Testing using Surprise Adequacy"☆46Updated 2 years ago
- Code release for RobOT (ICSE'21)☆15Updated last year
- ☆24Updated 4 years ago
- ☆18Updated 5 years ago
- Vision based algorithms for falsification of convolutional neural networks☆12Updated 6 years ago
- ☆26Updated last year
- Concolic Testing for Deep Neural Networks☆117Updated 3 years ago
- Reward Guided Test Generation for Deep Learning☆20Updated 3 months ago
- DLFuzz: An Efficient Fuzzing Testing Framework of Deep Learning Systems☆51Updated 6 years ago
- The released code of Neurify in NIPS 2018☆46Updated last year
- The released code of ReluVal in USENIX Security 2018☆56Updated 4 years ago
- ☆9Updated last year
- DNN Coverage Based Testing Study☆16Updated 4 years ago
- This repository contains the implementation and the evaluation of our ESEC/FSE 2020 paper: Detecting Numerical Bugs in Neural Network Ar…☆26Updated 3 years ago
- CC: Causality-Aware Coverage Criterion for Deep Neural Networks☆10Updated last year
- The library for symbolic interval☆20Updated 4 years ago
- A systematic testing tool for automatically detecting erroneous behaviors of DNN-driven vehicles☆79Updated 5 years ago
- Fourth edition of VNN COMP (2023)☆16Updated last year
- This is the implementation repository of our incoming ESEC/FSE 2021 paper: Exposing Numerical Bugs in Deep Learning via GradientBack-prop…☆13Updated 2 years ago
- EvalDNN: A Toolbox for Evaluating Deep Neural Network Models☆15Updated 4 years ago
- The official repo for GCP-CROWN paper☆12Updated 2 years ago
- Safety Verification of Deep Neural Networks☆50Updated 6 years ago
- ADAPT is the open source white-box testing framework for deep neural networks☆21Updated last year
- DeepInspect code release☆11Updated 4 years ago
- ☆9Updated 3 years ago
- ☆47Updated 6 years ago
- This repository is for NeurIPS 2018 spotlight paper "Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples."☆31Updated 2 years ago
- MODE: Automated Neural Network Model Debugging via State Differential Analysis and Input Selection - Replication Project☆15Updated last year
- ☆8Updated 4 years ago