SecurityLab-UCD / UniTSynLinks
[ISSTA'24] A Large-Scale Dataset Capable of Enhancing the Prowess of Large Language Models for Program Testing
☆11Updated 9 months ago
Alternatives and similar repositories for UniTSyn
Users that are interested in UniTSyn are comparing it to the libraries listed below
Sorting:
- ✅SRepair: Powerful LLM-based Program Repairer with $0.029/Fixed Bug☆70Updated last year
- For our ICSE22 paper "EAGLE: Creating Equivalent Graphs to Test Deep Learning Libraries" by Jiannan Wang, Thibaud Lutellier, Shangshu Qia…☆13Updated 2 years ago
- WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models (OOPSLA 2024)☆75Updated 2 months ago
- Fuzzing Automatic Differentiation in Deep-Learning Libraries (ICSE'23)☆25Updated last year
- Fuzzing Deep-Learning Libraries via Automated Relational API Inference (ESEC/FSE 2022)☆39Updated 2 years ago
- RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair http://arxiv.org/pdf/2312.15698☆35Updated last month
- ☆123Updated last year
- Artifact for ESEC/FSE'23 paper "NeuRI: Diversifying DNN Generation via Inductive Rule Inference"☆31Updated last year
- VulRepair: A T5-Based Automated Software Vulnerability Repair☆81Updated 5 months ago
- TeCo: an ML+Execution model for test completion☆31Updated last year
- Free Lunch for Testing: Fuzzing Deep-Learning Libraries from Open Source (ICSE'22)☆80Updated 2 years ago
- Large Language Models for Software Engineering☆250Updated 3 months ago
- [TOSEM 2023] A Survey of Learning-based Automated Program Repair☆72Updated last year
- For our ICSE23 paper "Impact of Code Language Models on Automated Program Repair" by Nan Jiang, Kevin Liu, Thibaud Lutellier, and Lin Tan☆62Updated last year
- This is the repository for the paper titled "ThinkRepair: Self-Directed Automated Program Repair" accepted by ISSTA'24.☆25Updated 3 months ago
- ☆159Updated 3 months ago
- For our ISSTA22 paper "DocTer: Documentation-Guided Fuzzing for Testing Deep Learning API Functions" by Danning Xie, Yitong Li, Mijung Ki…☆37Updated 3 years ago
- For our ISSTA23 paper "How Effective are Neural Networks for Fixing Security Vulnerabilities?" by Yi Wu, Nan Jiang, Hung Viet Pham, Thiba…☆39Updated last year
- This is the implement repository of our upcoming ESEC/FSE 2020 paper: Deep Learning Library Testing via Effective Model Generation.☆55Updated 2 years ago
- ☆38Updated 4 months ago
- ☆88Updated 2 years ago
- Dianshu-Liao / AAA-Code-Generation-Framework-for-Code-Repository-Local-Aware-Global-Aware-Third-Party-Aware☆21Updated last year
- Efficient APR with LLMs http://arxiv.org/pdf/2402.06598☆16Updated last year
- [ISSTA 2025] A Large-scale Empirical Study on Fine-tuning Large Language Models for Unit Testing☆13Updated 8 months ago
- [NeurIPS'24] SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning☆26Updated 11 months ago
- ☆31Updated 9 months ago
- We propose a novel adversarial example generation technique (i.e., CODA) for testing deep code models. Its key idea is to use code differ…☆16Updated 2 years ago
- [TSE 2024] APPT: Boosting Automated Patch Correctness Prediction via Fine-tuning Pre-trained Models☆15Updated 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 7 months ago
- ☆11Updated 9 months ago