Deeper Notions of Correctness in Image-Based DNNs: Lifting Properties from Pixel to Entities
Felipe Toledo,
David Shriver,
Sebastian Elbaum,
Matthew B. Dwyer
Foundations of Software Engineering
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2023
Felipe Toledo, David Shriver, Sebastian Elbaum, Matthew B. Dwyer. 2023. Deeper Notions of Correctness in Image-Based DNNs: Lifting Properties from Pixel to Entities. In Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2023). Association for Computing Machinery, New York, NY, USA, 2122–2126. https://doi.org/10.1145/3611643.3613079
DeepManeuver: Adversarial Test Generation for Trajectory Manipulation of Autonomous Vehicles
Meriel von Stein,
David Shriver,
Sebastian Elbaum
IEEE Transactions on Software Engineering
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2023
Meriel von Stein, David Shriver, Sebastian Elbaum. 2023. DeepManeuver: Adversarial Test Generation for Trajectory Manipulation of Autonomous Vehicles. In IEEE Transactions on Software Engineering, vol. 49, no. 10, pp. 4496-4509. https://doi.org/10.1109/TSE.2023.3301443
Increasing the Applicability of Verification Tools for Neural Networks
David Shriver
University of Virginia
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2022
David Shriver. Increasing the Applicability of Verification Tools for Neural Networks. PhD Thesis. University of Virginia. 2022.
Distribution Models for Falsification and Verification of DNNs
Felipe Toledo,
David Shriver,
Sebastian Elbaum,
Matthew B. Dwyer
International Conference on Automated Software Engineering (ASE)
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2021
Felipe Toledo, David Shriver, Sebastian Elbaum, Matthew B. Dwyer. 2021. Distribution Models for Falsification and Verification of DNNs. In 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE). 317-329. https://doi.org/10.1109/ASE51524.2021.9678590
DNNV: A Framework for Deep Neural Network Verification
David Shriver,
Sebastian Elbaum,
Matthew B. Dwyer
Computer Aided Verification
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2021
David Shriver, Sebastian Elbaum, Matthew B. Dwyer. 2021. DNNV: A Framework for Deep Neural Network Verification. In Computer Aided Verification. 137--150. https://doi.org/10.1007/978-3-030-81685-8_6
Reducing DNN Properties to Enable Falsification with Adversarial Attacks
David Shriver,
Sebastian Elbaum,
Matthew B. Dwyer
International Conference on Software Engineering (ICSE)
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2021
David Shriver, Sebastian Elbaum, Matthew B. Dwyer. 2021. Reducing DNN Properties to Enable Falsification with Adversarial Attacks. In 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE). 275-287. https://doi.org/10.1109/ICSE43902.2021.00036
Systematic Generation of Diverse Benchmarks for DNN Verification
Dong Xu,
David Shriver,
Matthew B. Dwyer,
Sebastian Elbaum
Computer Aided Verification
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2020
Dong Xu, David Shriver, Matthew B. Dwyer, Sebastian Elbaum. 2020. Systematic Generation of Diverse Benchmarks for DNN Verification. In Computer Aided Verification - 32nd International Conference, CAV 2020, Los Angeles, CA, USA, July 21-24, 2020, Proceedings, Part I. 97-121. https://doi.org/10.1007/978-3-030-53288-8_5
Poster: Differencing Neural Networks
David Shriver,
Sebastian Elbaum,
Matthew B. Dwyer
University of Virginia CS Research Symposium
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2019
David Shriver, Sebastian Elbaum, Matthew B. Dwyer. 2019. Differencing Neural Networks. In the 2019 University of Virginia Computer Science Research Symposium.
Refactoring Neural Networks for Verification
David Shriver,
Dong Xu,
Sebastian Elbaum,
Matthew B. Dwyer
arXiv preprint arXiv:1908.08026
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2019
David Shriver, Dong Xu, Sebastian Elbaum, Matthew B. Dwyer. 2019. Refactoring Neural Networks for Verification. arXiv:1908.08026. https://arxiv.org/abs/1908.08026
Evaluating Recommender System Stability with Influence-Guided Fuzzing
David Shriver,
Sebastian Elbaum,
Matthew B. Dwyer,
David S. Rosenblum
AAAI Conference on Artificial Intelligence
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2019
David Shriver, Sebastian Elbaum, Matthew B. Dwyer, David S. Rosenblum. 2019. Evaluating Recommender System Stability with Influence-Guided Fuzzing. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019. 4934-4942. https://doi.org/10.1609/aaai.v33i01.33014934
Toward the development of richer properties for recommender systems
David Shriver
International Conference on Software Engineering: Companion Proceedings
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2018
David Shriver. 2018. Toward the development of richer properties for recommender systems. In Proceedings of the 40th International Conference on Software Engineering: Companion Proceedings, ICSE 2018, Gothenburg, Sweden, May 27 - June 03, 2018. 173-174. https://doi.acm.org/10.1145/3183440.3195082
Assessing the Quality and Stability of Recommender Systems
David Shriver
University of Nebraska-Lincoln
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2018
David Shriver. Assessing the Quality and Stability of Recommender Systems. MS Thesis, University of Nebraska-Lincoln, 2018.
At the End of Synthesis: Narrowing Program Candidates
David Shriver,
Sebastian G. Elbaum,
Kathryn T. Stolee
International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track
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2017
David Shriver, Sebastian G. Elbaum, Kathryn T. Stolee. 2017. At the End of Synthesis: Narrowing Program Candidates. In 39th IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track, ICSE-NIER 2017, Buenos Aires, Argentina, May 20-28, 2017. 19-22. https://doi.org/10.1109/ICSE-NIER.2017.7