Risk-based Statistical Testing: A Refinement-based Approach to the Reliability Analysis of Safety-Critical Systems

Fabian Zimmermann (1) , Robert Eschbach (1) , Johannes Kloos (1) , Thomas Bauer (1)

1 Fraunhofer IESE - Fraunhofer Institute for Experimental Software Engineering

In this paper, a method is presented that allows to automatically generate test cases for risk-based testing of safety-critical systems. This is done through the systematic construction or refinement of risk-based test models. Our approach works for almost all kinds of model-based testing. In this paper, we use Model-based Statistical Testing as model-based test technique. Statistical testing uses Markov chain test models to describe the stimulation and usage profile of the system under test (SUT). In our method, the test models are refined in such a way that only critical test cases can be generated. The reliability of the SUT can be estimated for critical situations

Keywords: Model-based testing; regular languages; risk-based testing; software testing

Domains: Software Engineering [cs.SE]

Fabian Zimmermann, Robert Eschbach, Johannes Kloos, Thomas Bauer. Risk-based Statistical Testing: A Refinement-based Approach to the Reliability Analysis of Safety-Critical Systems. 12th European Workshop on Dependable Computing, EWDC 2009, May 2009, Toulouse, France. 8 p. ⟨hal-00381556⟩