Abstract
The RV system is the first system to merge the benefits of Runtime Monitoring with Predictive Analysis. The Runtime Monitoring portion of RV is based on the successful Monitoring Oriented Programming system developed at the University of Illinois [6,7,9,21,5], while the Predictive Analysis capability is a vastly expanded version of the jPredictor System also developed at the University of Illinois [11,14].
With the RV system, runtime monitoring is supported and encouraged as a fundamental principle for building reliable software: monitors are automatically synthesized from specified properties and integrated into the original system to check its dynamic behaviors. When certain conditions of interest occur, such as a violation of a specification, user-defined actions will be triggered, which can be any code from information logging to runtime recovery. The RV system supports the monitoring of parametric properties that may specify a relationship between objects. Properties may be defined using one of several logical formalisms, such as: extended regular languages, context-free patterns, deterministic finite state machines, linear temporal logic, and past time linear temporal logic. The system is designed in such a way that adding new logical formalisms is a relatively simple task.
The predictive capabilities allow any of these monitoring specifications to be extended to checking not just the actual runtime traces of program execution, but any trace that may be inferred from a constructed casual model. The Predictive Analysis also features built in algorithms for race detection and atomicity violations, that are both highly useful in concurrent system design and difficult to specify in terms of formal specification languages.
Supported in part by NSF grants CCF-0916893, CNS-0720512, and CCF-0448501, by NASA contract NNL08AA23C, by a Samsung SAIT grant, and by several Microsoft gifts.
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Meredith, P., Roşu, G. (2010). Runtime Verification with the RV System. In: Barringer, H., et al. Runtime Verification. RV 2010. Lecture Notes in Computer Science, vol 6418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16612-9_12
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