Mining Timed Regular Expressions from System Traces

Dynamic behavior of a program can be assessed through examination of events emitted by the program during execution. Temporal properties define the order of occurrence and timing constraints on event occurrence. Such specifica- tions are important for safety-critical real-time systems for which a delayed response to an emitted event may lead to a fault in the system. Since temporal properties are rarely specified for programs and due to the complexity of the formalisms, it is desirable to suggest properties by extracting them from traces of program execution for testing, verification, anomaly detection, and debugging purposes.

We propose a framework for automatically mining proper- ties that are in the form of timed regular expressions (TREs) from system traces. Using an abstract structure of the property, the framework constructs a finite state machine to serve as an acceptor. As part of the framework, we propose two novel algorithms optimized for mining general TREs and a fragment without negation. The framework is evaluated on industrial strength safety-critical real-time applications (a deployed autonomous hexacopter system and a commercial vehicle in operation) using traces with more than 1 Million entries. Our framework is open source and available online: https://bitbucket.org/sfischme/tre-mining