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Gaining certainty about uncertainty: Testing cyber-physical systems in the presence of uncertainties at the application level

 
: Schneider, Martin A.; Wendland, Marc-Florian; Bornemann, Leon

:
Postprint urn:nbn:de:0011-n-4524082 (1.3 MByte PDF)
MD5 Fingerprint: 84ea75720b93cf42809b1efb0a5a559c
Erstellt am: 22.2.2018


Großmann, Jürgen (Ed.); Felderer, Michael (Ed.); Seehusen, Fredrik (Ed.):
Risk Assessment and Risk-Driven Quality Assurance. 4th International Workshop, RISK 2016 : Held in Conjunction with ICTSS 2016, Graz, Austria, October 18, 2016, Revised Selected Papers
Cham: Springer International Publishing, 2017 (Lecture Notes in Computer Science 10224)
ISBN: 978-3-319-57857-6 (Print)
ISBN: 978-3-319-57858-3 (Online)
ISBN: 3-319-57857-X
DOI: 10.1007/978-3-319-57858-3
S.129-142
International Workshop on Risk Assessment and Risk-Driven Testing (RISK) <4, 2016, Graz>
International Conference on Testing Software and Systems (ICTSS) <28, 2016, Graz>
European Commission EC
H2020; 645463; U-Test
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer FOKUS ()

Abstract
A cyber-physical system (CPS) comprises several connected, embedded systems and is additionally equipped with sensors and actuators. Thus, CPSs can communicate with their cyber environment and measure and interact with their physical environment. Due to the complexity of their operational environment, assumptions the manufacturer have made may not hold in operation. During an unforeseen environmental situation, a CPS may expose behavior that negatively impactsits reliability. This may arise due to insufficiently considered environmental conditions during the design of a CPS, or – even worse – it is impossible to anticipate such conditions. In the U-Test project, we are developing a configurable search-based testing framework that exploits information from functional testing and from declarative descriptions of uncertainties. Itaims at revealing unintended behavior in the presence of uncertainties. This framework enables testing for different scenarios of uncertainty and thus, allows to achieve a certain coverage of those, and to find unknown uncertainty scenarios.

: http://publica.fraunhofer.de/dokumente/N-452408.html