Logs have been an imperative resource to ensure the reliability and continuity of many
software systems, especially large-scale distributed systems. They faithfully record runtime …

Artificial Intelligence for IT operations (AIOps) aims to combine the power of AI with the big
data generated by IT Operations processes, particularly in cloud infrastructures, to provide …

Software-intensive systems produce logs for troubleshooting purposes. Recently, many
deep learning models have been proposed to automatically detect system anomalies based …

Log data is an essential and valuable resource of online service systems, which records
detailed information of system running status and user behavior. Log anomaly detection is …

Modern information and communication systems have become increasingly challenging to
manage. The ubiquitous system logs contain plentiful information and are thus widely …

Log parsing, which extracts log templates and parameters, is a critical prerequisite step for
automated log analysis techniques. Though existing log parsers have achieved promising …

Log parsing, which involves log template extraction from semi-structured logs to produce
structured logs, is the first and the most critical step in automated log analysis. However …

Test case prioritization (TCP) has been widely studied in regression testing, which aims to
optimize the execution order of test cases so as to detect more faults earlier. TCP has been …

Logs, being run-time information automatically generated by software, record system events
and activities with their timestamps. Before obtaining more insights into the run-time status of …

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 …