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 engineers gain insights into large log data. These techniques have several steps, among which log abstraction is the most important because it transforms raw log-data into high-level information. Thus, log abstraction allows software engineers to perform further analyses. Existing log-abstraction techniques vary significantly in their designs and performances. To the best of our knowledge, there is no study that examines the performances of these techniques with respect to the following seven quality aspects concurrently: mode, coverage, delimiter independence, efficiency,scalability, system knowledge independence, and parameter tuning effort.