AUCAD: Automated Construction of Alignment Dataset from Log-Related Issues for Enhancing LLM-based Log Generation

This replication package contains supplementary material for the paper "AUCAD: Automated Construction of Alignment Dataset from Log-Related Issues for Enhancing LLM-based Log Generation".

Dataset

The dataset is available in dataset.

• AucadLog Dataset: aucad_log.json
• LANCE Dataset
  • Training set: lance_train.json
    • Considering GitHub's file size limitations, please clone the repository using git-lfs.
    • Please join the lance_train.json.part* files by the following command to obtain the lance_train.json file: cat lance_train.json.part00 lance_train.json.part01 lance_train.json.part02 > lance_train.json
  • Validation set: lance_valid.json
  • Testing set: lance_test.json (for ours), lance_prompt_unilog.json (for UniLog)
  • See: https://doi.org/10.1145/3510003.3511561
• LogBench-T Dataset: logbench-t_test.json
  • See: https://doi.org/10.1109/ASE51524.2021.9678596

Original Response

The original response is available in original_response.

Citation

@inproceedings{zhang2025aucad,
  author = {Zhang, Hao and Yu, Dongjun and Zhang, Lei and Rong, Guoping and Yu, Yongda and Shen, Haifeng and Zhang, He and Shao, Dong and Kuang, Hongyu},
  title = {{AUCAD}: Automated Construction of Alignment Dataset from Log-Related Issues for Enhancing {LLM}-based Log Generation},
  booktitle = {Proceedings of the 16th International Conference on Internetware},
  keywords = {LLM, Log Statement Generation, Log-related Issues, Alignment},
  series = {Internetware '25},
  year = {2025},
  month = {June},
  pages = {413–425},
  numpages = {13},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  location = {Trondheim, Norway},
  doi = {10.1145/3755881.3755889},
  isbn = {9798400719264},
  url = {https://doi.org/10.1145/3755881.3755889}
}