:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Guo, An, Gao, Xinyu, Fang, Chunrong, Tian, Haoxiang, Sun, Weisong, Mu, Yanzhou, Tang, Shuncheng, Ma, Lei, Chen, Zhenyu
Format:	Preprint
Publié:	2025
Sujets:	Software Engineering
Accès en ligne:	https://arxiv.org/abs/2506.07419
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

CooTest: An Automated Testing Approach for V2X Communication Systems
par: Guo, An, et autres
Publié: (2024)

When Autonomous Vehicle Meets V2X Cooperative Perception: How Far Are We?
par: Guo, An, et autres
Publié: (2025)

SoVAR: Building Generalizable Scenarios from Accident Reports for Autonomous Driving Testing
par: Guo, An, et autres
Publié: (2024)

Deep Learning Framework Testing via Heuristic Guidance Based on Multiple Model Measurements
par: Zou, Yinglong, et autres
Publié: (2025)

Improving Deep Learning Framework Testing with Model-Level Metamorphic Testing
par: Mu, Yanzhou, et autres
Publié: (2025)

DevMuT: Testing Deep Learning Framework via Developer Expertise-Based Mutation
par: Mu, Yanzhou, et autres
Publié: (2025)

Deep Learning Framework Testing via Model Mutation: How Far Are We?
par: Mu, Yanzhou, et autres
Publié: (2025)

A Systematic Literature Review on Large Language Models for Automated Program Repair
par: Zhang, Quanjun, et autres
Publié: (2024)

A Critical Review of Large Language Model on Software Engineering: An Example from ChatGPT and Automated Program Repair
par: Zhang, Quanjun, et autres
Publié: (2023)

APPT: Boosting Automated Patch Correctness Prediction via Fine-tuning Pre-trained Models
par: Zhang, Quanjun, et autres
Publié: (2023)

Understanding LLM-Centric Challenges for Deep Learning Frameworks: An Empirical Analysis
par: Mu, Yanzhou, et autres
Publié: (2025)

ACTesting: Automated Cross-modal Testing Method of Text-to-Image Software
par: Gu, Siqi, et autres
Publié: (2023)

A Survey on Large Language Models for Software Engineering
par: Zhang, Quanjun, et autres
Publié: (2023)

Test Script Intention Generation for Mobile Application via GUI Image and Code Understanding
par: Yu, Shengcheng, et autres
Publié: (2021)

Scalpel: Automotive Deep Learning Framework Testing via Assembling Model Components
par: Zou, Yinglong, et autres
Publié: (2025)

Machine Translation Testing via Syntactic Tree Pruning
par: Zhang, Quanjun, et autres
Publié: (2024)

MultiTest: Physical-Aware Object Insertion for Testing Multi-sensor Fusion Perception Systems
par: Gao, Xinyu, et autres
Publié: (2024)

Probing Privacy Leaks in LLM-based Code Generation via Test Generation
par: Ge, Yifei, et autres
Publié: (2026)

Log-based, Business-aware REST API Testing
par: Yang, Ding, et autres
Publié: (2026)

Towards Automated Crowdsourced Testing via Personified-LLM
par: Yu, Shengcheng, et autres
Publié: (2026)

Enhancing and Reporting Robustness Boundary of Neural Code Models for Intelligent Code Understanding
par: Han, Tingxu, et autres
Publié: (2026)

GPU Temperature Simulation-Based Testing for In-Vehicle Deep Learning Frameworks
par: Zou, Yinglong, et autres
Publié: (2025)

Train in Vain: Functionality-Preserving Poisoning to Prevent Unauthorized Use of Code Datasets
par: Xiao, Yuan, et autres
Publié: (2026)

TestBench: Evaluating Class-Level Test Case Generation Capability of Large Language Models
par: Zhang, Quanjun, et autres
Publié: (2024)

TestART: Improving LLM-based Unit Testing via Co-evolution of Automated Generation and Repair Iteration
par: Gu, Siqi, et autres
Publié: (2024)

Coverage Goal Selector for Combining Multiple Criteria in Search-Based Unit Test Generation
par: Zhou, Zhichao, et autres
Publié: (2023)

Practical, Automated Scenario-based Mobile App Testing
par: Yu, Shengcheng, et autres
Publié: (2024)

RUM: Rule+LLM-Based Comprehensive Assessment on Testing Skills
par: Wang, Yue, et autres
Publié: (2025)

Machine Learning for Actionable Warning Identification: A Comprehensive Survey
par: Ge, Xiuting, et autres
Publié: (2023)

ATTest: Agent-Driven Tensor Testing for Deep Learning Library Modules
par: Zhan, Zhengyu, et autres
Publié: (2026)

Large Language Models for Unit Testing: A Systematic Literature Review
par: Zhang, Quanjun, et autres
Publié: (2025)

An Empirical Study of Bugs in Modern LLM Agent Frameworks
par: Zhu, Xinxue, et autres
Publié: (2026)

Effective, Platform-Independent GUI Testing via Image Embedding and Reinforcement Learning
par: Yu, Shengcheng, et autres
Publié: (2022)

Breaking, Stale, or Missing? Benchmarking Coding Agents on Project-Level Test Evolution
par: Shang, Ye, et autres
Publié: (2026)

Mutation-Based Deep Learning Framework Testing Method in JavaScript Environment
par: Zou, Yinglong, et autres
Publié: (2024)

DeCoMa: Detecting and Purifying Code Dataset Watermarks through Dual Channel Code Abstraction
par: Xiao, Yuan, et autres
Publié: (2025)

A Large-scale Empirical Study on Fine-tuning Large Language Models for Unit Testing
par: Shang, Ye, et autres
Publié: (2024)

LeGEND: A Top-Down Approach to Scenario Generation of Autonomous Driving Systems Assisted by Large Language Models
par: Tang, Shuncheng, et autres
Publié: (2024)

Vision-Based Mobile App GUI Testing: A Survey
par: Yu, Shengcheng, et autres
Publié: (2023)

PuzzleMark: Implicit Jigsaw Learning for Robust Code Dataset Watermarking in Neural Code Completion Models
par: Huang, Haocheng, et autres
Publié: (2026)