:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Merabishvili, Giorgi, Weißl, Oliver, Stocco, Andrea
Format:	Preprint
Publié:	2026
Sujets:	Software Engineering Machine Learning
Accès en ligne:	https://arxiv.org/abs/2602.15552
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Targeted Deep Learning System Boundary Testing
par: Weißl, Oliver, et autres
Publié: (2024)

HyperNet-Adaptation for Diffusion-Based Test Case Generation
par: Weißl, Oliver, et autres
Publié: (2026)

Feature-Aware Test Generation for Deep Learning Models
par: Chen, Xingcheng, et autres
Publié: (2026)

Benchmarking Generative AI Models for Deep Learning Test Input Generation
par: Maryam, et autres
Publié: (2024)

Generating Realistic, Diverse, and Fault-Revealing Inputs with Latent Space Interpolation for Testing Deep Neural Networks
par: Duan, Bin, et autres
Publié: (2025)

Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantification
par: Grewal, Ruben, et autres
Publié: (2024)

Clotho: Measuring Task-Specific Pre-Generation Test Adequacy for LLM Inputs
par: Yoon, Juyeon, et autres
Publié: (2025)

Assessing Quality Metrics for Neural Reality Gap Input Mitigation in Autonomous Driving Testing
par: Lambertenghi, Stefano Carlo, et autres
Publié: (2024)

Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing
par: Xiao, Yisong, et autres
Publié: (2023)

GIST: Generated Inputs Sets Transferability in Deep Learning
par: Tambon, Florian, et autres
Publié: (2023)

Towards Assessing Deep Learning Test Input Generators
par: Mzoughi, Seif, et autres
Publié: (2025)

System Safety Monitoring of Learned Components Using Temporal Metric Forecasting
par: Sharifi, Sepehr, et autres
Publié: (2024)

Combining Neuroevolution with the Search for Novelty to Improve the Generation of Test Inputs for Games
par: Feldmeier, Patric, et autres
Publié: (2024)

Latent Space Class Dispersion: Effective Test Data Quality Assessment for DNNs
par: Vekariya, Vivek, et autres
Publié: (2025)

Efficient Domain Augmentation for Autonomous Driving Testing Using Diffusion Models
par: Baresi, Luciano, et autres
Publié: (2024)

Learning-Based Testing for Deep Learning: Enhancing Model Robustness with Adversarial Input Prioritization
par: Rahman, Sheikh Md Mushfiqur, et autres
Publié: (2025)

Towards Automated Page Object Generation for Web Testing using Large Language Models
par: Karagöz, Betül, et autres
Publié: (2026)

TopoMap: A Feature-based Semantic Discriminator of the Topographical Regions in the Test Input Space
par: De Vita, Gianmarco, et autres
Publié: (2025)

Generative AI to Generate Test Data Generators
par: Baudry, Benoit, et autres
Publié: (2024)

Grounding Data Science Code Generation with Input-Output Specifications
par: Wen, Yeming, et autres
Publié: (2024)

Automated Factual Benchmarking for In-Car Conversational Systems using Large Language Models
par: Giebisch, Rafael, et autres
Publié: (2025)

Otter: Generating Tests from Issues to Validate SWE Patches
par: Ahmed, Toufique, et autres
Publié: (2025)

ExplainFuzz: Explainable and Constraint-Conditioned Test Generation with Probabilistic Circuits
par: Baiget, Annaëlle, et autres
Publié: (2026)

PrismaDV: Automated Task-Aware Data Unit Test Generation
par: Chen, Hao, et autres
Publié: (2026)

Using Large Language Models to Generate JUnit Tests: An Empirical Study
par: Siddiq, Mohammed Latif, et autres
Publié: (2023)

PRIMG : Efficient LLM-driven Test Generation Using Mutant Prioritization
par: Bouafif, Mohamed Salah, et autres
Publié: (2025)

LLM-Powered Test Case Generation for Detecting Bugs in Plausible Programs
par: Liu, Kaibo, et autres
Publié: (2024)

Can Search-Based Testing with Pareto Optimization Effectively Cover Failure-Revealing Test Inputs?
par: Sorokin, Lev, et autres
Publié: (2024)

PPO guided Agentic Pipeline for Adaptive Prompt Selection and Test Case Generation
par: Koushik, Gourisetty Venkata Sai, et autres
Publié: (2026)

Reinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation
par: Steenhoek, Benjamin, et autres
Publié: (2023)

Reinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation
par: Steenhoek, Benjamin, et autres
Publié: (2024)

Toward Efficient Testing of Graph Neural Networks via Test Input Prioritization
par: Yang, Lichen, et autres
Publié: (2025)

From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing
par: Liang, Linfeng, et autres
Publié: (2026)

Enabling Global, Human-Centered Explanations for LLMs:From Tokens to Interpretable Code and Test Generation
par: Khati, Dipin, et autres
Publié: (2025)

Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM
par: Ryan, Gabriel, et autres
Publié: (2024)

A Multi-Year Grey Literature Review on AI-assisted Test Automation
par: Ricca, Filippo, et autres
Publié: (2024)

Understanding LLM-Driven Test Oracle Generation
par: Bodicoat, Adam, et autres
Publié: (2026)

Code Generation by Differential Test Time Scaling
par: He, Yifeng, et autres
Publié: (2026)

Test Code Generation for Telecom Software Systems using Two-Stage Generative Model
par: Nabeel, Mohamad, et autres
Publié: (2024)

DANDI: Diffusion as Normative Distribution for Deep Neural Network Input
par: Kim, Somin, et autres
Publié: (2025)