Departmental Papers (CIS)
Document Type
Conference Paper
Date of this Version
March 2007
Abstract
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.
Keywords
runtime verification, statistical monitoring, probabilistic properties
Date Posted: 24 January 2008
This document has been peer reviewed.
Comments
Postprint version. Published in Lecture Notes in Computer Science, Run-time Verification, 4839, March 2007, pages 164-175.
Publisher URL: http://dx.doi.org/10.1007/978-3-540-77395-5_14