Root cause identification of a problem in a distributed computing system using log files

This invention describes an automated way to figure out why a computer system is having problems, especially in complex, interconnected systems. It works by first learning what normal behavior looks like from healthy system logs. Then, when a problem occurs, it compares the new log files to its understanding of normal to pinpoint the specific messages that indicate the root cause. The method specifically focuses on identifying important keywords (tokens) in the logs and uses a statistical measure called inverse document frequency to weigh their significance.