 | Up a level |
Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
Use the mouse wheel or scroll gestures to zoom into the graph.
You can click on the nodes and links to highlight them and move the nodes by dragging them.
Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
Chen, J., Ding, Z., Tang, Y., Sayagh, M., Li, H., Adams, B., & Shang, W. (2023, December). IoPV : on inconsistent option performance variations [Paper]. 2023 ESEC/FSE Conferences, San Francisco, CA, USA (13 pages). External link
Ding, Z., Tang, Y., Cheng, X., Li, H., & Shang, W. (2024). LoGenText-Plus : Improving Neural Machine Translation Based Logging Texts Generation with Syntactic Templates. ACM Transactions on Software Engineering and Methodology, 33(2), 38 (45 pages). External link
Ding, Z., Li, H., Shang, W., & Chen, T.-H. P. (2023). Towards Learning Generalizable Code Embeddings Using Task-agnostic Graph Convolutional Networks. ACM Transactions on Software Engineering and Methodology, 32(2), 1-43. External link
Ding, Z., Li, H., Shang, W., & Chen, T.-H. P. (2022). Can pre-trained code embeddings improve model performance? Revisiting the use of code embeddings in software engineering tasks. Empirical Software Engineering, 27(3), 38 pages. External link
Ding, Z., Li, H., & Shang, W. (2022, March). LoGenText: Automatically generating logging texts using neural machine translation [Paper]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022), Honolulu, HI, USA. External link
