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A growing body of research has been dedicated to DL model testing.
Algorithms for the assignment and transportation problems
J. Munkres · 1957
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Learning to forget: Continual prediction with lstm
F. A. Gers, J. Schmidhuber, and F. Cummins · 2000
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Snowball: A language for stemming algorithms, 2001
M. F. Porter · 2001
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Practical, low-effort equivalence verification of real code
D. A. Ramos and D. R. Engler · 2011
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Speech recognition with deep recurrent neural networks
A. Graves, A.-r. Mohamed, and G. Hinton · 2013
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Search-based synthesis of equivalent method sequences
A. Goffi, A. Gorla, A. Mattavelli, M. Pezzè, and P. Tonella · 2014
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Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2014
Earlier work this paper cites.
Techniques for automatic detection of metamorphic relations
U. Kanewala · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Search-based inference of polynomial metamorphic relations
J. Zhang, J. Chen, D. Hao, Y. Xiong, B. Xie, L. Zhang, and H. Mei · 2014
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https://keras.io
Keras, 2015 · 2015
Earlier work this paper cites.
Multimodal deep learning for robust rgb-d object recognition
A. Eitel, J. T. Springenberg, L. Spinello, M. Riedmiller, and W. Burgard · 2015
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Deep learning for detecting robotic grasps
I. Lenz, H. Lee, and A. Saxena · 2015
Earlier work this paper cites.
Synthesis of equivalent method calls in guava
A. Mattavelli, A. Goffi, and A. Gorla · 2015
Earlier work this paper cites.
Automatic generation of oracles for exceptional behaviors
A. Goffi, A. Gorla, M. D. Ernst, and M. Pezzè · 2016
Earlier work this paper cites.
Deep Residual Learning for Image Recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
Deepfool: a simple and accurate method to fool deep neural networks
S.-M. Moosavi-Dezfooli, A. Fawzi, and P. Frossard · 2016
Earlier work this paper cites.
Mapping api elements for code migration with vector representations
T. D. Nguyen, A. T. Nguyen, and T. N. Nguyen · 2016
Earlier work this paper cites.
The limitations of deep learning in adversarial settings
N. Papernot, P. McDaniel, S. Jha, M. Fredrikson, Z. B. Celik, and A. Swami · 2016
Earlier work this paper cites.
Deep learning for health informatics
D. Ravì, C. Wong, F. Deligianni, M. Berthelot, J. Andreu-Perez, B. Lo, and G.-Z. Yang · 2016
Earlier work this paper cites.
Deep learning code fragments for code clone detection
M. White, M. Tufano, C. Vendome, and D. Poshyvanyk · 2016
Earlier work this paper cites.
Coverage-based greybox fuzzing as markov chain
M. Böhme, V.-T. Pham, and A. Roychoudhury · 2017
Earlier work this paper cites.
Automated testing of graphics shader compilers
A. F. Donaldson, H. Evrard, A. Lascu, and P. Thomson · 2017
Earlier work this paper cites.
Towards deep learning models resistant to adversarial attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2017
Earlier work this paper cites.
Deep learning in bioinformatics
S. Min, B. Lee, and S. Yoon · 2017
Earlier work this paper cites.
Exploring api embedding for api usages and applications
T. D. Nguyen, A. T. Nguyen, H. D. Phan, and T. N. Nguyen · 2017
Earlier work this paper cites.
Deepxplore: Automated whitebox testing of deep learning systems
K. Pei, Y. Cao, J. Yang, and S. Jana · 2017
Earlier work this paper cites.
Threat of adversarial attacks on deep learning in computer vision: A survey
N. Akhtar and A. Mian · 2018
Earlier work this paper cites.
Path-based function embedding and its application to error-handling specification mining
D. DeFreez, A. V. Thakur, and C. Rubio-González · 2018
Earlier work this paper cites.
Deep code search
X. Gu, H. Zhang, and S. Kim · 2018
Cited alongside, same era.
Deepgauge: Multi-granularity testing criteria for deep learning systems
L. Ma, F. Juefei-Xu, F. Zhang, J. Sun, M. Xue, B. Li, C. Chen, T. Su, L. Li, Y. Liu, et al · 2018
Cited alongside, same era.
Deeptest: Automated testing of deep-neural-network-driven autonomous cars
Y. Tian, K. Pei, S. Jana, and B. Ray · 2018
Cited alongside, same era.
Automated inference of likely metamorphic relations for model transformations
J. Troya, S. Segura, and A. Ruiz-Cortés · 2018
Cited alongside, same era.
Deeproad: Gan-based metamorphic testing and input validation framework for autonomous driving systems
M. Zhang, Y. Zhang, L. Zhang, C. Liu, and S. Khurshid · 2018
Cited alongside, same era.
Towards zero knowledge learning for cross language api mappings
N. Bui · 2019
Deepbillboard: Systematic physical-world testing of autonomous driving systems
H. Zhou, W. Li, Z. Kong, J. Guo, Y. Zhang, B. Yu, L. Zhang, and C. Liu · 2020
Later among the works it cites.
https://pypi.org/project/beautifulsoup4/
bs4, 2021 · 2021
Later among the works it cites.
https://pytorch.org/docs/stable/generated/torch.broadcast_shapes.html
Definition of torch.broadcast_shapes from Pytorch official documentation, 2021 · 2021
Later among the works it cites.
https://www.vice.com/en_us/article/9kga85/uber-is-giving-up-on-self-driving-cars-in-california-after-deadly-crash
News, 2021 · 2021
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https://en.wikipedia.org/wiki/Topological_sorting
Topological Sorting, 2021 · 2021
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Memo: Automatically identifying metamorphic relations in javadoc comments for test automation
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Cited alongside, same era.
On evaluating adversarial robustness
N. Carlini, A. Athalye, N. Papernot, W. Brendel, J. Rauber, D. Tsipras, I. Goodfellow, A. Madry, and A. Kurakin · 2019
Cited alongside, same era.
Guiding deep learning system testing using surprise adequacy
J. Kim, R. Feldt, and S. Yoo · 2019
Cited alongside, same era.
Deepfl: Integrating multiple fault diagnosis dimensions for deep fault localization
X. Li, W. Li, Y. Zhang, and L. Zhang · 2019
Cited alongside, same era.
Algorithms for verifying deep neural networks
C. Liu, T. Arnon, C. Lazarus, C. Strong, C. Barrett, and M. J. Kochenderfer · 2019
Cited alongside, same era.
Deepdelta: learning to repair compilation errors
A. Mesbah, A. Rice, E. Johnston, N. Glorioso, and E. Aftandilian · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, et al · 2019
Cited alongside, same era.
A. Blasi, A. Gorla, M. D. Ernst, M. Pezzè, and A. Carzaniga · 2021
Later among the works it cites.
Fully automated functional fuzzing of android apps for detecting non-crashing logic bugs
T. Su, Y. Yan, J. Wang, J. Sun, Y. Xiong, G. Pu, K. Wang, and Z. Su · 2021
Later among the works it cites.
Maximum weight matching — Wikipedia, the free encyclopedia
Wikipedia contributors · 2021
Later among the works it cites.
Wikipedia for backpropagation, 2021
Wikipedia contributors · 2021
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Wikipedia for Supervised Learning, 2021
Wikipedia contributors · 2021
Later among the works it cites.
Automated conformance testing for javascript engines via deep compiler fuzzing
G. Ye, Z. Tang, S. H. Tan, S. Huang, D. Fang, X. Sun, L. Bian, H. Wang, and Z. Wang · 2021
Later among the works it cites.
Deep just-in-time defect prediction: how far are we?
Z. Zeng, Y. Zhang, H. Zhang, and L. Zhang · 2021
Later among the works it cites.
Predoo: precision testing of deep learning operators
X. Zhang, N. Sun, C. Fang, J. Liu, J. Liu, D. Chai, J. Wang, and Z. Chen · 2021
Later among the works it cites.
Neoflow: A flexible framework for enabling efficient compilation for high performance dnn training
S. Zheng, R. Chen, Y. Jin, A. Wei, B. Wu, X. Li, S. Yan, and Y. Liang · 2021
Later among the works it cites.
https://pytorch.org/docs/stable/tensors.html#torch.Tensor
Class torch.Tensor from PyTorch official documentation, 2022 · 2022
Closest in time.
https://github.com/ise-uiuc/DeepREL
DeepREL Repository, 2022 · 2022
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https://www.tensorflow.org/api_docs/python/tf/parallel_stack
Definition of tf.parallel_stack from TensorFlow official documentation, 2022 · 2022
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https://www.tensorflow.org/api_docs/python/tf/compat
Module tf.compat from TensorFlow official documentation, 2022 · 2022
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https://www.tensorflow.org/api_docs/python/tf/raw_ops
Module tf.raw_ops from TensorFlow official documentation, 2022 · 2022
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https://pypi.org/project/munkres/
munkres, 2022 · 2022
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https://github.com/pytorch/pytorch
PyTorch Repository, 2022 · 2022
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https://www.sbert.net/
SentenceTransformer, 2022 · 2022
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Coverage-guided tensor compiler fuzzing with joint ir-pass mutation
J. Liu, Y. Wei, S. Yang, Y. Deng, and L. Zhang · 2022
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Free lunch for testing: Fuzzing deep-learning libraries from open source
A. Wei, Y. Deng, C. Yang, and L. Zhang · 2022
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Levenshtein distance — Wikipedia, the free encyclopedia, 2022
Wikipedia contributors · 2022
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Tf–idf — Wikipedia, the free encyclopedia, 2022
Wikipedia contributors · 2022
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Docter: Documentation-guided fuzzing for testing deep learning api functions
D. Xie, Y. Li, M. Kim, H. V. Pham, L. Tan, X. Zhang, and M. W. Godfrey · 2022
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An extensive study on pre-trained models for program understanding and generation
Z. Zeng, H. Tan, H. Zhang, J. Li, Y. Zhang, and L. Zhang · 2022
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