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DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep
Neural Networks

v1v2v3v4v5 (latest)

DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep Neural Networks

ACM Transactions on Software Engineering and Methodology (TOSEM), 2023

8 March 2023

Zohreh Aghababaeyan

Manel Abdellatif

Mahboubeh Dadkhah

Lionel C. Briand

ArXiv (abs)PDF HTML Github (6★)

Papers citing "DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep Neural Networks"

4 / 4 papers shown

Bias Testing and Mitigation in Black Box LLMs using Metamorphic Relations

Bias Testing and Mitigation in Black Box LLMs using Metamorphic Relations

129

0

0

29 Nov 2025

MetaSel: A Test Selection Approach for Fine-tuned DNN Models

MetaSel: A Test Selection Approach for Fine-tuned DNN ModelsIEEE Transactions on Software Engineering (TSE), 2025

Amin Abbasishahkoo

Mahboubeh Dadkhah

Lionel C. Briand

570

1

0

21 Mar 2025

DiffGAN: A Test Generation Approach for Differential Testing of Deep Neural Networks for Image Analysis

DiffGAN: A Test Generation Approach for Differential Testing of Deep Neural Networks for Image AnalysisIEEE Transactions on Software Engineering (TSE), 2024

Zohreh Aghababaeyan

Manel Abdellatif

Lionel C. Briand

564

0

0

15 Oct 2024

SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning
Agents

SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning AgentsIEEE Transactions on Software Engineering (TSE), 2023

Amirhossein Zolfagharian

Manel Abdellatif

Lionel C. Briand

411

14

0

03 Aug 2023

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