Detecting event anomalies in event-based systems

Event-based interaction is an attractive paradigm because its use can lead to highly flexible and adaptable systems. One problem in this paradigm is that events are sent, received, and processed nondeterministically, due to the systems ’ reliance on implicit in-vocation and implicit concurrency. This nondeterminism can lead to event anomalies, which occur when an event-based system re-ceives multiple events that lead to the write of a shared field or memory location. Event anomalies can lead to unreliable, error-prone, and hard to debug behavior in an event-based system. To de-tect these anomalies, this paper presents a new static analysis tech-nique, DEvA, for automatically detecting event anomalies. DEvA has been evaluated on a set of open-source event-based systems against a state-of-the-art technique for detecting data races in multi-threaded systems, and a recent technique for solving a similar prob-lem with event processing in Android applications. DEvA exhibited high precision with respect to manually constructed ground truths, and was able to locate event anomalies that had not been detected by the existing solutions