Abstract
We revisit Stream Runtime Verification for synchronous systems. Stream Runtime Verification (SRV) is a declarative formalism to express monitors using streams, which aims to be a simple and expressive specification language. The goal of SRV is to allow engineers to describe both correctness/failure assertions and interesting statistical measures for system profiling and coverage analysis. The monitors generated are useful for testing, under actual deployment, and to analyze logs.
The main observation that enables SRV is that the steps in the algorithms to monitor temporal logics (which generate Boolean verdicts) can be generalized to compute statistics of the trace if a different data domain is used. Hence, the fundamental idea of SRV is to separate the temporal dependencies in the monitoring algorithm from the concrete operations to be performed at each step.
In this paper we revisit the pioneer SRV specification language Lola and present in detail the online and offline monitoring algorithms. The algorithm for online monitoring Lola specifications uses a partial evaluation strategy, by incrementally constructing output streams from input streams, maintaining a storage of partially evaluated expressions. We identify syntactically a class of specifications for which the online algorithm is trace length independent, that is, the memory requirement does not depend on the length of the input streams. Then, we extend the principles of the online algorithm to create an efficient offline monitoring algorithm for large traces, which consist on scheduling trace length independent passes on a dumped log.
This research has been partially supported by: the EU H2020 project Elastest (num. 731535), by the Spanish MINECO Project “RISCO (TIN2015-71819-P)” and by the EU ICT COST Action IC1402 ARVI (Runtime Verification beyond Monitoring).
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Sánchez, C. (2018). Online and Offline Stream Runtime Verification of Synchronous Systems. In: Colombo, C., Leucker, M. (eds) Runtime Verification. RV 2018. Lecture Notes in Computer Science(), vol 11237. Springer, Cham. https://doi.org/10.1007/978-3-030-03769-7_9
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