College of Computing and Data Science (CCDS)

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4,771 to 4,780 of 4,932 Results

images.7z.013 Sep 18, 2020 - Panda images dataset Unknown - 120.4 MB - MD5: ad4884fe16534ab72e7b446fcffd15ed The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip.
Supplementary Materials for: Marble: Model-based Robustness Analysis of Stateful Deep Learning Systems Aug 26, 2020 - Software Reliability and Security Lab Du, Xiaoning; Li, Yi; Xie, Xiaofei; Ma, Lei; Liu, Yang; Zhao, Jianjun, 2020, "Supplementary Materials for: Marble: Model-based Robustness Analysis of Stateful Deep Learning Systems", https://doi.org/10.21979/N9/TTTSFK, DR-NTU (Data), V1 This supplementary material contains additional proofs for the paper: "Marble: Model-based Robustness Analysis of Stateful DeepLearning Systems".
MARBLE_appendix.pdf Aug 26, 2020 - Supplementary Materials for: Marble: Model-based Robustness Analysis of Stateful Deep Learning Systems Adobe PDF - 561.3 KB - MD5: 6e9098c1634463be20919cf4a3451b34 Additional proofs
Replication Data for: GenSlice: Generalized Semantic History Slicing Aug 21, 2020 - Software Reliability and Security Lab Zhu, Chenguang; Li, Yi; Rubin, Julia; Chechik, Marsha, 2020, "Replication Data for: GenSlice: Generalized Semantic History Slicing", https://doi.org/10.21979/N9/LPHCUS, DR-NTU (Data), V3 This dataset contains the raw experiment data and replication package for the ICSME'20 paper: "GenSlice: Generalized Semantic History Slicing". The replication package is also available at: https://github.com/Chenguang-Zhu/icsme20-artifact (2020-08-06)
replication-package.tar.gz Aug 21, 2020 - Replication Data for: GenSlice: Generalized Semantic History Slicing Gzip Archive - 22.1 MB - MD5: bad1a6b6e9e480248a69937f75e3c8ff Replication package for GenSlice experiments
raw-results.tar Aug 7, 2020 - Replication Data for: GenSlice: Generalized Semantic History Slicing TAR Archive - 165.3 MB - MD5: 7daf37461207cb15da0d96121e626e0c Raw data obtained in the GenSlice experiments
Replication Data for: Towards Automated Verification of Smart Contract Fairness May 27, 2020 - Software Reliability and Security Lab Liu, Ye; Li, Yi; Lin, Shang-Wei, 2020, "Replication Data for: Towards Automated Verification of Smart Contract Fairness", https://doi.org/10.21979/N9/0BEVRT, DR-NTU (Data), V1 Software artifacts created for the paper titled "Towards Automated Verification of Smart Contract Fairness" accepted at FSE'20.
faircon_data.tar May 27, 2020 - Replication Data for: Towards Automated Verification of Smart Contract Fairness TAR Archive - 4.8 MB - MD5: 9c829d07a4d2a0208aa442b159087a67 Tarball containing contract code and raw console logs from the experiments.
Obtain_FairCon.md May 27, 2020 - Replication Data for: Towards Automated Verification of Smart Contract Fairness Markdown Text - 11.5 KB - MD5: bc233c7fde39d83eccec490a7de3ba14 Information on how to obtain FairCon.
README.md May 27, 2020 - Replication Data for: Towards Automated Verification of Smart Contract Fairness Markdown Text - 8.2 KB - MD5: c0a424f42840678f2362a5cf23ae6513 Information about the dataset usage.

images.7z.013

Sep 18, 2020 - Panda images dataset

Unknown - 120.4 MB -

The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip.

Supplementary Materials for: Marble: Model-based Robustness Analysis of Stateful Deep Learning Systems

Aug 26, 2020 - Software Reliability and Security Lab

Du, Xiaoning; Li, Yi; Xie, Xiaofei; Ma, Lei; Liu, Yang; Zhao, Jianjun, 2020, "Supplementary Materials for: Marble: Model-based Robustness Analysis of Stateful Deep Learning Systems", https://doi.org/10.21979/N9/TTTSFK, DR-NTU (Data), V1

This supplementary material contains additional proofs for the paper: "Marble: Model-based Robustness Analysis of Stateful DeepLearning Systems".

MARBLE_appendix.pdf

Aug 26, 2020 - Supplementary Materials for: Marble: Model-based Robustness Analysis of Stateful Deep Learning Systems

Adobe PDF - 561.3 KB -

Additional proofs

Replication Data for: GenSlice: Generalized Semantic History Slicing

Aug 21, 2020 - Software Reliability and Security Lab

Zhu, Chenguang; Li, Yi; Rubin, Julia; Chechik, Marsha, 2020, "Replication Data for: GenSlice: Generalized Semantic History Slicing", https://doi.org/10.21979/N9/LPHCUS, DR-NTU (Data), V3

This dataset contains the raw experiment data and replication package for the ICSME'20 paper: "GenSlice: Generalized Semantic History Slicing". The replication package is also available at: https://github.com/Chenguang-Zhu/icsme20-artifact (2020-08-06)

replication-package.tar.gz

Aug 21, 2020 - Replication Data for: GenSlice: Generalized Semantic History Slicing

Gzip Archive - 22.1 MB -

Replication package for GenSlice experiments

raw-results.tar

Aug 7, 2020 - Replication Data for: GenSlice: Generalized Semantic History Slicing

TAR Archive - 165.3 MB -

Raw data obtained in the GenSlice experiments

Replication Data for: Towards Automated Verification of Smart Contract Fairness

May 27, 2020 - Software Reliability and Security Lab

Liu, Ye; Li, Yi; Lin, Shang-Wei, 2020, "Replication Data for: Towards Automated Verification of Smart Contract Fairness", https://doi.org/10.21979/N9/0BEVRT, DR-NTU (Data), V1

Software artifacts created for the paper titled "Towards Automated Verification of Smart Contract Fairness" accepted at FSE'20.

faircon_data.tar

May 27, 2020 - Replication Data for: Towards Automated Verification of Smart Contract Fairness

TAR Archive - 4.8 MB -

Tarball containing contract code and raw console logs from the experiments.

Obtain_FairCon.md

May 27, 2020 - Replication Data for: Towards Automated Verification of Smart Contract Fairness

Markdown Text - 11.5 KB -

Information on how to obtain FairCon.

README.md

May 27, 2020 - Replication Data for: Towards Automated Verification of Smart Contract Fairness

Markdown Text - 8.2 KB -

Information about the dataset usage.

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