Automated Author ProfileZengyang Li
Zengyang Li
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 7.0 (sum of 4 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This is the replication package for the paper: "Potential Technical Debt and Its Resolution in Code Reviews: An Exploratory Study of the OpenStack and Qt Communities", including the dataset and its description (README.md): PTD-related Comments in Code Review and Data Extraction Results.xlsx is the dataset of our paper, which contains 2,030 review comments collected from the Nova project and Neutron project of OpenStack community. Among all the review comments, 163 review comments indicate PTD. For the rows of review comments that are related to PTD, we filled them with blue color as an indicator. README.md
Authors
- Liming Fu ;
- Liang, Peng ;
- Rasheed, Zeeshan ;
- Zengyang Li ;
- Amjed Tahir ;
- Xiaofeng Han
This is the replication package for the paper: "Potential Technical Debt and Its Resolution in Code Reviews: An Exploratory Study of the OpenStack and Qt Communities", including the dataset and its description (README.md): PTD-related Comments in Code Review and Data Extraction Results.xlsx is the dataset of our paper, which contains 2,030 review comments collected from the Nova project and Neutron project of OpenStack community. Among all the review comments, 163 review comments indicate PTD. For the rows of review comments that are related to PTD, we filled them with blue color as an indicator. README.md
Authors
- Liming Fu ;
- Liang, Peng ;
- Rasheed, Zeeshan ;
- Zengyang Li ;
- Amjed Tahir ;
- Xiaofeng Han
This is the dataset for the paper: "Self-Claimed Assumptions in Deep Learning Frameworks: An Exploratory Study". It contains 3084 Self-Claimed Assumptions (SCAs) extracted from nine deep learning frameworks (i.e., TensorFlow, Theano, PyTorch, Caffe, MXNet, Keras, CNTK, DL4J, and PaddlePaddle).
Authors
- Yang, Chen ;
- Liang, Peng ;
- Liming Fu ;
- Zengyang Li
This is the dataset for the paper: "Self-Claimed Assumptions in Deep Learning Frameworks: An Exploratory Study". It contains 3084 Self-Claimed Assumptions (SCAs) extracted from nine deep learning frameworks (i.e., TensorFlow, Theano, PyTorch, Caffe, MXNet, Keras, CNTK, DL4J, and PaddlePaddle).
Authors
- Yang, Chen ;
- Liang, Peng ;
- Liming Fu ;
- Zengyang Li