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Chen, J., Ding, Z., Tang, Y., Sayagh, M., Li, H., Adams, B., & Shang, W. (décembre 2023). IoPV : on inconsistent option performance variations [Communication écrite]. 2023 ESEC/FSE Conferences, San Francisco, CA, USA (13 pages). Lien externe
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). Lien externe
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. Lien externe
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. Lien externe
Ding, Z., Li, H., & Shang, W. (mars 2022). LoGenText: Automatically generating logging texts using neural machine translation [Communication écrite]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022), Honolulu, HI, USA. Lien externe