Markov analysis of software specifications
ACM Transactions on Software Engineering and Methodology (TOSEM)
Statistical testing of software based on a usage model
Software—Practice & Experience
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
Using Markov Chain Usage Models to Test Complex Systems
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences - Volume 09
Software Testing Research: Achievements, Challenges, Dreams
FOSE '07 2007 Future of Software Engineering
Automated Testing of Generic Computational Science Libraries
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
Scenario-Based statistical testing of quality of service requirements
SMTT'03 Proceedings of the 2003 international conference on Scenarios: models, Transformations and Tools
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The systematic generation of test cases from statistical usage models has been investigated recently for specific application domains, such as wireless communications or automotive applications. For Markov chain usage models, the expected usage of a hardware/software system is represented by transitions between usage states and a usage profile, meaning probability values that are attached to the state transitions. In this paper, we explain how to calculate the profile probabilities for the Markov chain usage model from a set of linear usage constraints and by optimizing a convex polyhedron that represents the constrained solution space. Comparing the computed probability distributions of our polyhedron approach with the maximum entropy technique, which is the main technique used so far, illustrates that our results are more obvious to the intented constraint semantics. 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 has provided promising results.