Tahereh Zohdinasab

Orcid: 0000-0002-0191-1151

According to our database1, Tahereh Zohdinasab authored at least 20 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
ICST Tool Competition 2025 - UAV Testing Track.
Proceedings of the IEEE Conference on Software Testing, Verification and Validation, 2025

2024
Focused Test Generation for Autonomous Driving Systems.
ACM Trans. Softw. Eng. Methodol., July, 2024

DeepHyperion-UAV at the SBFT Tool Competition 2024 - CPS-UAV Test Case Generation Track.
Proceedings of the 17th ACM/IEEE International Workshop on Search-Based and Fuzz Testing, 2024

2023
Replication Package: DeepAtash-LR: Focused Test Generation for Autonomous Driving Systems.
Dataset, December, 2023

Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems.
Dataset, July, 2023

Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems.
Dataset, July, 2023

Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems.
Dataset, July, 2023

Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems.
Dataset, July, 2023

Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems.
Dataset, July, 2023

Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems.
Dataset, July, 2023

Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems.
Dataset, July, 2023

Replication Package: DeepAtash: Focused Test Generation for Deep Learning Systems.
Dataset, July, 2023

Replication Package: An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours.
Dataset, July, 2023

Replication Package: An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours.
Dataset, July, 2023

Efficient and Effective Feature Space Exploration for Testing Deep Learning Systems.
ACM Trans. Softw. Eng. Methodol., April, 2023

DeepHyperion: Exploring the Feature Space of Deep Learning-based Systems through Illumination Search.
Proceedings of the Software Engineering 2023, 2023

DeepAtash: Focused Test Generation for Deep Learning Systems.
Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2023

An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours.
Proceedings of the ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2023

2021
Replication Package: DeepHyperion: Exploring the Feature Space of Deep Learning-Based Systems through Illumination Search.
Dataset, July, 2021

Replication Package: DeepHyperion: Exploring the Feature Space of Deep Learning-Based Systems through Illumination Search.
Dataset, July, 2021


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