2018
,
Drabek, Christian
,
Weiß, Gereon
,
Bauer, Bernhard
Runtime verification checks if the behavior of a system under observation in a certain run satisfies a given correctness property. While a positive description of the system's behavior is often available from specification, it contains no information for the monitor how it should continue in case the system deviates from this behavior. If the monitor does not resume its operation in the right way, test coverage will be unnecessarily low or further observations are misclassified. To close this gap, we present a new method for extending state-based runtime monitors in an automated way, called resumption. Therefore, this paper examines how runtime verification monitors based on a positive behavior description can be resumed to find all detectable deviations instead of reporting only invalid traces. Moreover, we examine when resumption can be applied successfully and we present alternative resumption algorithms. Using an evaluation framework, their precision and recall for detecting different kinds of deviations are compared. While the algorithm seeking expected behavior for resumption works very well in all evaluated cases, the framework can also be used to find the best suited resumption extension for a specific application scenario. Further, two real world application scenarios are introduced where resumption has been successfully applied.
2017
,
Drabek, Christian
,
Weiß, Gereon
,
Bauer, Bernhard
In networked embedded systems created with parts from different suppliers, deviations from the expected communication behavior often cause integration problems. Therefore, runtime verification monitors are used to detect if observed communication behavior fulfills defined correctness properties. However, in order to resume verification if unspecified behavior is observed, the runtime monitor needs a definition of the resumption. Otherwise, further deviations may be overlooked. We present a method for extending state-based runtime monitors with resumption in an automated way. This enables continuous monitoring without interruption. The method may exploit diverse resumption algorithms. In an evaluation, we show how to find the best suited resumption extension for a specific application scenario and compare the algorithms.