AutoLog: Facing log redundancy and insufficiency

Cheng Zhang, Zhenyu Guo, Ming Wu, Longwen Lu, Yu Fan, Jianjun Zhao, Zheng Zhang

研究成果: 著書/レポートタイプへの貢献会議での発言

3 引用 (Scopus)

抜粋

Logs are valuable for failure diagnosis and software debugging in practice. However, due to the ad-hoc style of inserting logging statements, the quality of logs can hardly be guaranteed. In case of a system failure, the log file may contain a large number of irrelevant logs, while crucial clues to the root cause may still be missing. In this paper, we present an automated approach to log improvement based on the combination of information from program source code and textual logs. It selects the most relevant ones from an ocean of logs to help developers focus and reason along the causality chain, and generates additional informative logs to help developers discover the root causes of failures. We have conducted a preliminary case study using an implementation prototype to demonstrate the usefulness of our approach.

元の言語英語
ホスト出版物のタイトルProceedings of the 2nd Asia-Pacific Workshop on Systems, APSys'11
DOI
出版物ステータス出版済み - 12 1 2011
外部発表Yes
イベント2nd Asia-Pacific Workshop on Systems, APSys'11 - Shanghai, 中国
継続期間: 7 11 20117 12 2011

出版物シリーズ

名前Proceedings of the 2nd Asia-Pacific Workshop on Systems, APSys'11

その他

その他2nd Asia-Pacific Workshop on Systems, APSys'11
中国
Shanghai
期間7/11/117/12/11

    フィンガープリント

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

これを引用

Zhang, C., Guo, Z., Wu, M., Lu, L., Fan, Y., Zhao, J., & Zhang, Z. (2011). AutoLog: Facing log redundancy and insufficiency. : Proceedings of the 2nd Asia-Pacific Workshop on Systems, APSys'11 (Proceedings of the 2nd Asia-Pacific Workshop on Systems, APSys'11). https://doi.org/10.1145/2103799.2103811