Saved in:
| Main Authors: | Zhang, Quanjun, Zhai, Juan, Fang, Chunrong, Liu, Jiawei, Sun, Weisong, Hu, Haichuan, Wang, Qingyu |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.00751 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Breaking, Stale, or Missing? Benchmarking Coding Agents on Project-Level Test Evolution
by: Shang, Ye, et al.
Published: (2026)
by: Shang, Ye, et al.
Published: (2026)
A Critical Review of Large Language Model on Software Engineering: An Example from ChatGPT and Automated Program Repair
by: Zhang, Quanjun, et al.
Published: (2023)
by: Zhang, Quanjun, et al.
Published: (2023)
EvoRepair: Enhancing Vulnerability Repair Agents Through Experience-Based Self-Evolution
by: Hu, Haichuan, et al.
Published: (2026)
by: Hu, Haichuan, et al.
Published: (2026)
ComPass: Contrastive Learning for Automated Patch Correctness Assessment in Program Repair
by: Zhang, Quanjun, et al.
Published: (2026)
by: Zhang, Quanjun, et al.
Published: (2026)
APPT: Boosting Automated Patch Correctness Prediction via Fine-tuning Pre-trained Models
by: Zhang, Quanjun, et al.
Published: (2023)
by: Zhang, Quanjun, et al.
Published: (2023)
ATTest: Agent-Driven Tensor Testing for Deep Learning Library Modules
by: Zhan, Zhengyu, et al.
Published: (2026)
by: Zhan, Zhengyu, et al.
Published: (2026)
Repair-R1: Better Test Before Repair
by: Hu, Haichuan, et al.
Published: (2025)
by: Hu, Haichuan, et al.
Published: (2025)
CL4SE: Benchmarking Context Learning on Software Engineering
by: Hu, Haichuan, et al.
Published: (2026)
by: Hu, Haichuan, et al.
Published: (2026)
TSAPR: A Tree Search Framework For Automated Program Repair
by: Hu, Haichuan, et al.
Published: (2025)
by: Hu, Haichuan, et al.
Published: (2025)
Scalpel: Automotive Deep Learning Framework Testing via Assembling Model Components
by: Zou, Yinglong, et al.
Published: (2025)
by: Zou, Yinglong, et al.
Published: (2025)
ACTesting: Automated Cross-modal Testing Method of Text-to-Image Software
by: Gu, Siqi, et al.
Published: (2023)
by: Gu, Siqi, et al.
Published: (2023)
A Systematic Literature Review on Large Language Models for Automated Program Repair
by: Zhang, Quanjun, et al.
Published: (2024)
by: Zhang, Quanjun, et al.
Published: (2024)
Deep Learning Framework Testing via Heuristic Guidance Based on Multiple Model Measurements
by: Zou, Yinglong, et al.
Published: (2025)
by: Zou, Yinglong, et al.
Published: (2025)
SCOPE: Tree-based Self-Correcting Online Log Parsing via Syntactic-Semantic Collaboration
by: Fan, Dongyi, et al.
Published: (2026)
by: Fan, Dongyi, et al.
Published: (2026)
On the Effectiveness of Code Representation in Deep Learning-Based Automated Patch Correctness Assessment
by: Zhang, Quanjun, et al.
Published: (2026)
by: Zhang, Quanjun, et al.
Published: (2026)
A Survey on Large Language Models for Software Engineering
by: Zhang, Quanjun, et al.
Published: (2023)
by: Zhang, Quanjun, et al.
Published: (2023)
Mutation-Based Deep Learning Framework Testing Method in JavaScript Environment
by: Zou, Yinglong, et al.
Published: (2024)
by: Zou, Yinglong, et al.
Published: (2024)
Probing Privacy Leaks in LLM-based Code Generation via Test Generation
by: Ge, Yifei, et al.
Published: (2026)
by: Ge, Yifei, et al.
Published: (2026)
TestBench: Evaluating Class-Level Test Case Generation Capability of Large Language Models
by: Zhang, Quanjun, et al.
Published: (2024)
by: Zhang, Quanjun, et al.
Published: (2024)
Machine Learning for Actionable Warning Identification: A Comprehensive Survey
by: Ge, Xiuting, et al.
Published: (2023)
by: Ge, Xiuting, et al.
Published: (2023)
CooTest: An Automated Testing Approach for V2X Communication Systems
by: Guo, An, et al.
Published: (2024)
by: Guo, An, et al.
Published: (2024)
Large Language Models for Unit Testing: A Systematic Literature Review
by: Zhang, Quanjun, et al.
Published: (2025)
by: Zhang, Quanjun, et al.
Published: (2025)
A Large-scale Empirical Study on Fine-tuning Large Language Models for Unit Testing
by: Shang, Ye, et al.
Published: (2024)
by: Shang, Ye, et al.
Published: (2024)
TestART: Improving LLM-based Unit Testing via Co-evolution of Automated Generation and Repair Iteration
by: Gu, Siqi, et al.
Published: (2024)
by: Gu, Siqi, et al.
Published: (2024)
Vision-Based Mobile App GUI Testing: A Survey
by: Yu, Shengcheng, et al.
Published: (2023)
by: Yu, Shengcheng, et al.
Published: (2023)
Security of Language Models for Code: A Systematic Literature Review
by: Chen, Yuchen, et al.
Published: (2024)
by: Chen, Yuchen, et al.
Published: (2024)
GPU Temperature Simulation-Based Testing for In-Vehicle Deep Learning Frameworks
by: Zou, Yinglong, et al.
Published: (2025)
by: Zou, Yinglong, et al.
Published: (2025)
GUI Test Migration via Abstraction and Concretization
by: Zhang, Yakun, et al.
Published: (2024)
by: Zhang, Yakun, et al.
Published: (2024)
TestExplora: Benchmarking LLMs for Proactive Bug Discovery via Repository-Level Test Generation
by: Liu, Steven, et al.
Published: (2026)
by: Liu, Steven, et al.
Published: (2026)
Generate Realistic Test Scenes for V2X Communication Systems
by: Guo, An, et al.
Published: (2025)
by: Guo, An, et al.
Published: (2025)
No Man is an Island: Towards Fully Automatic Programming by Code Search, Code Generation and Program Repair
by: Zhang, Quanjun, et al.
Published: (2024)
by: Zhang, Quanjun, et al.
Published: (2024)
SoVAR: Building Generalizable Scenarios from Accident Reports for Autonomous Driving Testing
by: Guo, An, et al.
Published: (2024)
by: Guo, An, et al.
Published: (2024)
SWE-Pruner: Self-Adaptive Context Pruning for Coding Agents
by: Wang, Yuhang, et al.
Published: (2026)
by: Wang, Yuhang, et al.
Published: (2026)
Seed-Guided Fine-Grained Entity Typing in Science and Engineering Domains
by: Zhang, Yu, et al.
Published: (2024)
by: Zhang, Yu, et al.
Published: (2024)
Can GPT-O1 Kill All Bugs? An Evaluation of GPT-Family LLMs on QuixBugs
by: Hu, Haichuan, et al.
Published: (2024)
by: Hu, Haichuan, et al.
Published: (2024)
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Object-Oriented Programming
by: Wang, Tianyang, et al.
Published: (2024)
by: Wang, Tianyang, et al.
Published: (2024)
CodeContests+: High-Quality Test Case Generation for Competitive Programming
by: Wang, Zihan, et al.
Published: (2025)
by: Wang, Zihan, et al.
Published: (2025)
HarnessLLM: Automatic Testing Harness Generation via Reinforcement Learning
by: Liu, Yujian, et al.
Published: (2025)
by: Liu, Yujian, et al.
Published: (2025)
English Please: Evaluating Machine Translation with Large Language Models for Multilingual Bug Reports
by: Patil, Avinash, et al.
Published: (2025)
by: Patil, Avinash, et al.
Published: (2025)
Investigating Markers and Drivers of Gender Bias in Machine Translations
by: Barclay, Peter J, et al.
Published: (2024)
by: Barclay, Peter J, et al.
Published: (2024)
Similar Items
-
Breaking, Stale, or Missing? Benchmarking Coding Agents on Project-Level Test Evolution
by: Shang, Ye, et al.
Published: (2026) -
A Critical Review of Large Language Model on Software Engineering: An Example from ChatGPT and Automated Program Repair
by: Zhang, Quanjun, et al.
Published: (2023) -
EvoRepair: Enhancing Vulnerability Repair Agents Through Experience-Based Self-Evolution
by: Hu, Haichuan, et al.
Published: (2026) -
ComPass: Contrastive Learning for Automated Patch Correctness Assessment in Program Repair
by: Zhang, Quanjun, et al.
Published: (2026) -
APPT: Boosting Automated Patch Correctness Prediction via Fine-tuning Pre-trained Models
by: Zhang, Quanjun, et al.
Published: (2023)