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Chapter 5: Automated Statistical Testing for Embedded Systems

: Poore, J.H.; Lin, L.; Eschbach, R.; Bauer, T.

Zander, J.:
Model-based testing for embedded systems
Boca Raton, Fla.: CRC Press, 2017 (Computational analysis, synthesis, and design of dynamic systems)
ISBN: 978-1-4398-1847-3
ISBN: 978-1-4398-1845-9
ISBN: 978-1-280-12171-5
Aufsatz in Buch
Fraunhofer IESE ()

Embedded systems have become quite large over the years, with systems of 10 million lines of code now common. However, many organizations are struggling with the development and testing methods of times gone by when a small team of engineers could retain the modules of an embedded system. Any large, complex, expensive process with myriad ways to do most activities, as is the case with embedded systems development, can have its costbenefit profile dramatically improved by the use of statistical science. Statistics provide a structure for collecting data and transforming it into information that can improve decision making under uncertainty.