Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

11-2017

Abstract

It is often necessary to estimate the probability of certain events occurring in a system. For instance, knowing the probability of events triggering a shutdown sequence allows us to estimate the availability of the system. One approach is to run the system multiple times and then construct a probabilistic model to estimate the probability. When the probability of the event to be estimated is low, many system runs are necessary in order to generate an accurate estimation. For complex cyber-physical systems, each system run is costly and time-consuming, and thus it is important to reduce the number of system runs while providing accurate estimation. In this work, we assume that the user can actively tune the initial configuration of the system before the system runs and answer the following research question: how should the user set the initial configuration so that a better estimation can be learned with fewer system runs. The proposed approach has been implemented and evaluated with a set of benchmark models, random generated models, and a real-world water treatment system.

Keywords

Embedded systems, Formal methods, Software engineering, Water treatment

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Formal Methods and Software Engineering: 19th International Conference on Formal Engineering Methods, ICFEM 2017, Xi'an, China, November 13-17: Proceedings

Volume

10610

First Page

379

Last Page

395

ISBN

9783319686899

Identifier

10.1007/978-3-319-68690-5_23

Publisher

Springer

City or Country

Cham

Additional URL

https://doi.org/10.1007/978-3-319-68690-5_23

Download

Share

COinS