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A survey on automated log analysis for reliability engineering
Logs are semi-structured text generated by logging statements in software source code. In
recent decades, software logs have become imperative in the reliability assurance …
recent decades, software logs have become imperative in the reliability assurance …
A systematic literature review on automated log abstraction techniques
Context: Logs are often the first and only information available to software engineers to
understand and debug their systems. Automated log-analysis techniques help software …
understand and debug their systems. Automated log-analysis techniques help software …
The ABC of software engineering research
A variety of research methods and techniques are available to SE researchers, and while
several overviews exist, there is consistency neither in the research methods covered nor in …
several overviews exist, there is consistency neither in the research methods covered nor in …
Logram: Efficient Log Parsing Using -Gram Dictionaries
Software systems usually record important runtime information in their logs. Logs help
practitioners understand system runtime behaviors and diagnose field failures. As logs are …
practitioners understand system runtime behaviors and diagnose field failures. As logs are …
Loghub: A large collection of system log datasets for ai-driven log analytics
Logs have been widely adopted in software system development and maintenance because
of the rich runtime information they record. In recent years, the increase of software size and …
of the rich runtime information they record. In recent years, the increase of software size and …
Using deep learning to generate complete log statements
Logging is a practice widely adopted in several phases of the software lifecycle. For
example, during software development log statements allow engineers to verify and debug …
example, during software development log statements allow engineers to verify and debug …
Deep learning or classical machine learning? an empirical study on log-based anomaly detection
While deep learning (DL) has emerged as a powerful technique, its benefits must be
carefully considered in relation to computational costs. Specifically, although DL methods …
carefully considered in relation to computational costs. Specifically, although DL methods …
A qualitative study of the benefits and costs of logging from developers' perspectives
Software developers insert logging statements in their source code to collect important
runtime information of software systems. In practice, logging appropriately is a challenge for …
runtime information of software systems. In practice, logging appropriately is a challenge for …
Characterizing the natural language descriptions in software logging statements
Logging is a common programming practice of great importance in modern software
development, because software logs have been widely used in various software …
development, because software logs have been widely used in various software …
Logflash: Real-time streaming anomaly detection and diagnosis from system logs for large-scale software systems
Today, software systems are getting increasingly large and complex and a short failure time
may cause huge loss. Therefore, it is important to detect and diagnose anomalies accurately …
may cause huge loss. Therefore, it is important to detect and diagnose anomalies accurately …