Ming Yan

Orcid: 0000-0001-9757-7794

Affiliations:
  • Tianjin University, College of Intelligence and Computing, Tianjin, China


According to our database1, Ming Yan authored at least 11 papers between 2020 and 2025.

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

Timeline

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Bibliography

2025
Evaluating Spectrum-Based Fault Localization on Deep Learning Libraries.
IEEE Trans. Software Eng., May, 2025

Robustness evaluation of code generation systems via concretizing instructions.
Inf. Softw. Technol., 2025

2024
Revisiting deep neural network test coverage from the test effectiveness perspective.
J. Softw. Evol. Process., April, 2024

Stratified random sampling for neural network test input selection.
Inf. Softw. Technol., January, 2024

2023
COCO: Testing Code Generation Systems via Concretized Instructions.
CoRR, 2023

Achieving Last-Mile Functional Coverage in Testing Chip Design Software Implementations.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice, 2023

2022
An Empirical Study on Numerical Bugs in Deep Learning Programs.
Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 2022

2021
Exposing numerical bugs in deep learning via gradient back-propagation.
Proceedings of the ESEC/FSE '21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021

2020
Practical Accuracy Estimation for Efficient Deep Neural Network Testing.
ACM Trans. Softw. Eng. Methodol., 2020

Deep Neural Network Test Coverage: How Far Are We?
CoRR, 2020

Deep learning library testing via effective model generation.
Proceedings of the ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2020


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