Abstract
Log anomaly detection has become a common practice for software engineers to analyze software system behavior. Despite significant research efforts in log anomaly detection over the past decade, it remains unclear what are practitioners' expectations on log anomaly detection and whether current research meets their needs. To fill this gap, we conduct an empirical study, surveying 312 practitioners from 36 countries about their expectations on log anomaly detection. In particular, we investigate various factors influencing practitioners' willingness to adopt log anomaly detection tools. We then perform a literature review on log anomaly detection, focusing on publications in premier venues from 2015 to 2025, to compare practitioners' needs with the current state of research. Based on this comparison, we highlight the directions for researchers to focus on to develop log anomaly detection techniques that better meet practitioners' expectations. © 2025 IEEE.
| Original language | English |
|---|---|
| Pages (from-to) | 2455-2471 |
| Number of pages | 17 |
| Journal | IEEE Transactions on Software Engineering |
| Volume | 51 |
| Issue number | 9 |
| Online published | 8 Jul 2025 |
| DOIs | |
| Publication status | Published - Sept 2025 |
Funding
This work obtained ethics approval by the Research Ethics Committee of the Hong Kong Metropolitan University (HE-SF2025/19).
Research Keywords
- Anomaly detection
- Interviews
- Surveys
- Monitoring
- Systematic literature review
- Computer science
- Real-time systems
- Manuals
- Debugging
- Training
- Automated log anomaly detection
- empirical study
- practitioners' expectations
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