Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2013

Abstract

Testing provides a probabilistic assurance of system correctness. In general, testing relies on the assumptions that the system under test is deterministic so that test cases can be sampled. However, a challenge arises when a system under test behaves non-deterministiclly in a dynamic operating environment because it will be unknown how to sample test cases.In this work, we propose a method combining hypothesis testing and probabilistic model checking so as to provide the ``assurance" and quantify the error bounds. The idea is to apply hypothesis testing to deterministic system components and use probabilistic model checking techniques to lift the results through non-determinism. Furthermore, if a requirement on the level of ``assurance" is given, we apply probabilistic model checking techniques to push down the requirement through non-determinism to individual components so that they can be verified using hypothesis testing. We motivate and demonstrate our method through an application of system reliability prediction and distribution. Our approach has been realized in a toolkit named RaPiD, which has been applied to investigate two real-world systems.

Keywords

MDP, hypothesis testing, reliability prediction, reliability distribution

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the 2013 International Symposium on Software Testing and Analysis, ISSTA '13, Lugano, Switzerland, July 15–20

First Page

101

Last Page

111

ISBN

9781450321594

Identifier

10.1145/2483760.2483779

Publisher

ACM

City or Country

Lugano, Switzerland

Additional URL

https://doi.org/10.1145/2483760.2483779

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