The temporal logic of reactive and concurrent systems
The temporal logic of reactive and concurrent systems
A Network-Centric Approach to Embedded Software for Tiny Devices
EMSOFT '01 Proceedings of the First International Workshop on Embedded Software
The nesC language: A holistic approach to networked embedded systems
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Java-MaC: A Run-Time Assurance Approach for Java Programs
Formal Methods in System Design
Runtime Verification of Timing and Probabilistic Properties using WMI and .NET
EUROMICRO '04 Proceedings of the 30th EUROMICRO Conference
RT-MaC: Runtime Monitoring and Checking of Quantitative and Probabilistic Properties
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Collecting Statistics Over Runtime Executions
Formal Methods in System Design
On the expressiveness and complexity of randomization in finite state monitors
Journal of the ACM (JACM)
Monitoring probabilistic properties
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Independence from obfuscation: A semantic framework for diversity
Journal of Computer Security
An effective sequential statistical test for probabilistic monitoring
Information and Software Technology
Copilot: a hard real-time runtime monitor
RV'10 Proceedings of the First international conference on Runtime verification
Runtime verification of stochastic, faulty systems
RV'10 Proceedings of the First international conference on Runtime verification
Runtime verification with state estimation
RV'11 Proceedings of the Second international conference on Runtime verification
| Hi-index | 0.00 |
Probabilistic correctness is an important aspect of reliable systems. A soft real-time system, for instance, may be designed to tolerate some degree of deadline misses under a threshold. Since probabilistic systems may behave differently from their probabilistic models depending on their current environments, checking the systems at runtime can provide another level of assurance for their probabilistic correctness. This paper presents a statistical runtime verification for probabilistic properties using statistical analysis. However, while this statistical analysis collects a number of execution paths as samples to check probabilistic properties within some certain error bounds, runtime verification can only produce one single sample. This paper provides a technique to produce such a number of samples and applies this methodology to check probabilistic properties in wireless sensor network applications.