Mining internet payment development logs for reliability and security (MIPL – NWO)Current
We devise new principles, patterns, theories, and techniques that help the developer to unleash the full potential of log-files. To that end we focus on organizing log-files, providing logging guidelines, inventing new log line learning techniques, offering log-line information through abstract models, and evaluating our approach at industry scale. Besides the common happy path of successful execution scenarios, we will focus on (combinations) of exceptional scenarios that developers find hard to discover and handle. Eventually such scenarios end up as (run time) exceptions logged in log-lines, possibly pointing to omissions or incorrect assumptions in the source code. Next to exceptional behavior, we also use log-lines to search for possibly malicious scenarios. We propose novel algorithms that learn behavioral models (state machines) in real-time from log-lines. We subsequently analyze these machines and use them to discover logged behavior that deviates from expectation.
Contact person: Dr. Sicco Verwer