Editing Model-based testing (section)

===Test case generation by using a Markov chain test model===
[[Markov chains]] are an efficient way to handle Model-based Testing. Test models realized with Markov chains can be understood as a usage model: it is referred to as Usage/Statistical Model Based Testing. Usage models, so Markov chains, are mainly constructed of 2 artifacts : the [[finite-state machine]] (FSM) which represents all possible usage scenario of the tested system and the Operational Profiles (OP) which qualify the FSM to represent how the system is or will be used statistically. The first (FSM) helps to know what can be or has been tested and the second (OP) helps to derive operational test cases.
Usage/Statistical Model-based Testing starts from the facts that is not possible to exhaustively test a system and that failure can appear with a very low rate.<ref>Helene Le Guen. Validation d'un logiciel par le test statistique d'usage : de la modelisation de la decision à la livraison, 2005. URL:ftp://ftp.irisa.fr/techreports/theses/2005/leguen.pdf</ref> This approach offers a pragmatic way to statically derive test cases which are focused on improving the reliability of the system under test. Usage/Statistical Model Based Testing was recently extended to be applicable to embedded software systems.<ref>{{Cite book | doi=10.1109/ICSTW.2011.11| chapter=Model Based Statistical Testing of Embedded Systems| title=2011 IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops| pages=18–25| year=2011| last1=Böhr| first1=Frank| isbn=978-1-4577-0019-4| s2cid=9582606}}</ref><ref>{{cite book |isbn=978-3843903486|title=Model-Based Statistical Testing of Embedded Real-Time Software with Continuous and Discrete Signals in a Concurrent Environment: The Usage Net Approach |last1=Böhr |first1=Frank |year=2012 |publisher=Verlag Dr. Hut }}</ref>