Researchers build a faster way to learn what software systems are actually doing from live data streams

Scientists developed a method to understand how software and control systems behave by watching them operate in real time, rather than needing all the data upfront. This matters because most software systems are not designed for batch analysis — they run continuously, and the ability to understand their behavior on the fly could help diagnose problems, detect attacks, or verify that systems are doing what they're supposed to do without stopping them.

For decades, the algorithms that learn state machines from data assumed the data already existed in a complete form. This paper shows you can learn them from streaming data, which is how software actually runs. The method uses less memory and runs faster than existing approaches. This is structurally significant because it removes a constraint: anyone trying to monitor live systems, verify control logic, or detect anomalous behavior in network traffic or industrial systems no longer needs to collect everything first and analyze later.