Semantic Parsing for Log Analysis, Fault Detection, and Fault Diagnosis
Develop and evaluate log parsing techniques for extraction of semantic information in log messages.
Keywords: Log Parsing, Log Analysis
Description: Log parsing is deployed to extract structured templates and parameters from the semi-structured raw log messages. Most of the log parsers regard each message as a string to generate templates, ignoring the semantic information hidden in the original message. The goal of this project is to explore the inclusion of semantic meaning into log parsing and examine the efficacy of semantic log parsing in log analysis, fault detection, and fault diagnosis.
Learning outcome
- Application of log parsing in system states' analysis context
- Proficiency with implementing and evaluating log parsing and analysis techniques
- Gain appreciation for the state of the art in semantic parsing in log analysis
- Experience with working in an exciting and active research environment
- Excellent opportunities to publish your research results in the form of a scientific publication
Qualifications
- Interested in log parsing/log analysis
- Interested in semantic learning
- Preferably knowledge of python and LaTeX
Supervisors
- Merve Astekin
- Leon Moonen
References
- Huo, Y., Su, Y., Li, B., & Lyu, M. R. (2021). SemParser: A Semantic Parser for Log Analysis. arXiv preprint arXiv:2112.12636.
