Jacob-yen / LEMONLinks
This is the implement repository of our upcoming ESEC/FSE 2020 paper: Deep Learning Library Testing via Effective Model Generation.
☆54Updated last year
Alternatives and similar repositories for LEMON
Users that are interested in LEMON are comparing it to the libraries listed below
Sorting:
- Fuzzing Deep-Learning Libraries via Automated Relational API Inference (ESEC/FSE 2022)☆37Updated 2 years ago
- This is the implementation repository of our ICSE'22 paper: Muffin: Testing Deep Learning Libraries via Neural Architecture Fuzzing.☆30Updated 2 years ago
- For our ISSTA22 paper "DocTer: Documentation-Guided Fuzzing for Testing Deep Learning API Functions" by Danning Xie, Yitong Li, Mijung Ki…☆36Updated 2 years ago
- Artifact for ESEC/FSE'23 paper "NeuRI: Diversifying DNN Generation via Inductive Rule Inference"☆31Updated last year
- Free Lunch for Testing: Fuzzing Deep-Learning Libraries from Open Source (ICSE'22)☆78Updated 2 years ago
- This repository contains the implementation and the evaluation of our ESEC/FSE 2020 paper: Detecting Numerical Bugs in Neural Network Ar…☆26Updated 4 years ago
- For our ICSE22 paper "EAGLE: Creating Equivalent Graphs to Test Deep Learning Libraries" by Jiannan Wang, Thibaud Lutellier, Shangshu Qia…☆13Updated last year
- Fast and Precise On-the-fly Patch Validation for All☆10Updated 2 years ago
- Fuzzing Automatic Differentiation in Deep-Learning Libraries (ICSE'23)☆22Updated last year
- This is the implementation repository of our incoming ESEC/FSE 2021 paper: Exposing Numerical Bugs in Deep Learning via GradientBack-prop…☆14Updated 2 years ago
- ☆14Updated 2 years ago
- WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models (OOPSLA 2024)☆61Updated 6 months ago
- [ICSE 2023] Differentiable interpretation and failure-inducing input generation for neural network numerical bugs.☆12Updated last year
- ☆83Updated last year
- precision-error guided fuzz testing for deep learning operators☆8Updated 3 years ago
- This repository contains the dataset of our ISSTA 2018 paper: An Empirical Study on TensorFlow Program Bugs.☆30Updated 5 years ago
- We propose a novel DL-based mutation technique (LEAM), which adapts the syntax-guided encoder-decoder architecture to build two sub-model…☆27Updated 11 months ago
- ☆74Updated 2 years ago
- ADAPT is the open source white-box testing framework for deep neural networks☆22Updated 2 years ago
- DLFuzz: An Efficient Fuzzing Testing Framework of Deep Learning Systems☆52Updated 6 years ago
- For our ICSE21 paper "CURE: Code-Aware Neural Machine Translation for Automatic Program Repair" by Nan Jiang, Thibaud Lutellier, and Lin …☆56Updated 2 years ago
- A learning-guided approach for executing arbitrary Python code snippets☆18Updated last year
- For our ISSTA'23 paper ACETest: Automated Constraint Extraction for Testing Deep Learning Operators☆11Updated last year
- This is an evaluation set for the problem of directed/targeted test input generation. We use it to benchmark the ability of Large Languag…☆33Updated 2 months ago
- ☆25Updated last month
- For our ICSE23 paper "Impact of Code Language Models on Automated Program Repair" by Nan Jiang, Kevin Liu, Thibaud Lutellier, and Lin Tan☆60Updated 7 months ago
- Defect Library for LLM-enabled Software☆15Updated 2 months ago
- ☆12Updated last year
- ☆18Updated last year
- ☆11Updated 2 years ago