Abstract
Runtime monitoring of finite state properties may incur large and unpredictable overheads in terms of memory and execution time, which makes its deployment in a production environment challenging. In this work, we present a monitoring approach that investigates the trade-offs between memory overheads of monitoring, execution times of monitoring operations, and error reporting. Our approach is motivated by two key observations. First, there is a prominent behavioral redundancy among monitors. Second, the events on the same or related objects are often temporally segregated. We have implemented our approach in a prototype tool, Metis. Its evaluation indicates that it can reduce the memory footprint effectively and provide compact worst-case execution time bounds to monitoring operations with little to no compromise in error reporting.
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Notes
- 1.
The execution context of an error report is the path of the call graph from the root function to the current function where that error report was triggered.
- 2.
The probability of generating the monitor decreases multiplicatively with the number of monitors that are already in the pool.
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Acknowledgements
We thank Dr. Mohan Dhawan (IBM Research) and the anonymous reviewers for their valuable suggestions. This work was partly supported by Infosys Center for Artificial Intelligence.
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Allabadi, G., Dhar, A., Bashir, A., Purandare, R. (2018). METIS: Resource and Context-Aware Monitoring of Finite State Properties. 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_10
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