Markov analysis of software specifications
ACM Transactions on Software Engineering and Methodology (TOSEM)
A Markov Chain Model for Statistical Software Testing
IEEE Transactions on Software Engineering
Statistical testing of software based on a usage model
Software—Practice & Experience
Cleanroom software engineering: technology and process
Cleanroom software engineering: technology and process
Generating transition probabilities to support model-based software testing
Software—Practice & Experience
Improved techniques for software testing based on markov chain usage models
Improved techniques for software testing based on markov chain usage models
MaTeLo - Statistical Usage Testing by Annotated Sequence Diagrams, Markov Chains and TTCN-3
QSIC '03 Proceedings of the Third International Conference on Quality Software
Scenario-Based statistical testing of quality of service requirements
SMTT'03 Proceedings of the 2003 international conference on Scenarios: models, Transformations and Tools
A comfortable testplayer for analyzing statistical usage testing strategies
Proceedings of the 6th International Workshop on Automation of Software Test
Veritas - a versatile modeling environment for test-driven agile simulation
Proceedings of the Winter Simulation Conference
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Statistical usage testing of hardware/software systems is based in the main on a Markov chain usage model. This kind of model represents the expected use of the system by a usage profile, i.e. appropriate probability values that are attached to the state transitions. In this paper we present a constraint-based polyhedron approach to calculate the probability distribution for the MCUM from a given set of usage constraints. Comparing the computed probability distributions of our polyhedron approach with the maximum entropy technique shows that our result is much closer to the intented constraint semantics. Using the polyhedron method, customer profiles can be calculated so that they reflect the intended system usage of different customers or customer types much better. In order to demonstrate the applicability of our approach, workflow testing of a complex RIS/PACS system in the medical domain was carried through and yielded very promising results.