Log-driven intelligent software reliability engineering


Ms. HUO Yintong
Ph.D. candidate
The Chinese University of Hong Kong


Software systems are serving various aspects of our daily activities, from search engines to communication platforms. Traditional software reliability engineering (SRE) practices, which heavily rely on manual efforts, encounter challenges due to 1) sheer volume, 2) high variety, and 3) rapid evolution of modern software.  My research is centered on enhancing software reliability through automated fault management. In this talk, I will present my work on intelligent SRE, with a focus on utilizing log data for the three major fault management phases: fault prevention, fault removal, and fault tolerance.

The talk starts with the development of an initial investigation on a semantic-aware log analysis framework tailored for identifying system failures during software operation, so that proper fault tolerance mechanisms can be invoked.  The resulting work, SemParser, is inspired by an insightful understanding of the distinctions between human-written language (log events) and machine-generated tokens (variables).  Then, we will discuss “AutoLog” – a novel log sequence simulation framework leveraging program analysis to overcome the limitations of insufficient log data. Unlike existing log data gathered from a limited number of workloads, AutoLog for the first time acquires far more comprehensive and scalable log datasets, paving the way for proactive and practical anomaly detection solutions.  Finally, I will discuss my recent research progress in LLM-powered SRE that demonstrates the possibility of new designs, which integrate LLMs into resolving real-world software engineering challenges.

My past research has showcased the effectiveness of log-driven methods in advancing SRE. To conclude, I will outline my research roadmap with various directions, which extends from intelligent log operations to diverse applications in software development.


HUO Yintong is currently a Ph.D. candidate at the Chinese University of Hong Kong, advised by Michael R. Lyu.  Her research area is intelligent Software Engineering (SE), with a focus on software reliability by promoting automated software development, testing, and operations. She has published 12 papers in all top-tier SE conferences, including ICSE, FSE, ASE, ISSTA, and ISSRE.  She is the recipient of an IEEE Open Software Services Award for the LogPAI project (3k+ Stars, 70k+ Downloads).


Mr. WONG O-Bong (obong@cse.cuhk.edu.hk)

Ms. FUNG Wing Chi Mary (maryfung@cse.cuhk.edu.hk)


Apr 12, 2024


11:30 am - 12:30 pm


ERB404, William M W Mong Engineering Building (ERB)

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