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Model Based Statistical Testing of Embedded Systems

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1 Author(s)

Model Based Statistical Testing is a highly automated test approach. It allows the fully automated test case generation, execution, evaluation and estimation of the test objects reliability. This can be done after building a test model which is called a usage model. These models do neither support a notion of time, nor do they allow to model concurrency, which both are of great concern in testing embedded systems. This paper proposes an extension to Model Based Statistical Testing which deals with the mentioned problems and maintains all mentioned advantages of Model Based Statistical Testing. This is done by using an advanced kind of Petri nets as test model. A usage model can be generated out of these Petri nets. The direct creation of a usage model without the use of the proposed Petri nets is not possible in practice if it is necessary to deal with time and concurrency. This is the case because usage models tend to get very large in this very common situation. The paper does also show that it is possible to generate executable test cases (including oracle information) from the Petri nets. Tool support for the presented approach is available.

Published in:

Software Testing, Verification and Validation Workshops (ICSTW), 2011 IEEE Fourth International Conference on

Date of Conference:

21-25 March 2011