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Uncertainty-aware Robustness Assessment of Industrial Elevator Systems.pdf (3.265Mb)
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Izenburua
Uncertainty-aware Robustness Assessment of Industrial Elevator Systems
Egilea
Arrieta, AitorMondragon Unibertsitatea
Egilea (beste erakunde batekoa)
Han, Liping
Ali, Shaukat
Yue, Tao
Arratibel, Maite
Ikerketa taldea
Ingeniería del software y sistemas
Argitalpen data
2022
Argitaratzailea
ACM
Gako-hitzak
Uncertainty-aware
Robustness Assessment
Empirical Study
Laburpena
Industrial elevator systems are commonly used software systems in our daily lives, which operate in uncertain environments such as unpredictable passenger traffic, uncertain passenger attributes and b ... [+]
Industrial elevator systems are commonly used software systems in our daily lives, which operate in uncertain environments such as unpredictable passenger traffic, uncertain passenger attributes and behaviors, and hardware delays. Understanding and assessing the robustness of such systems under various uncertainties enable system designers to reason about uncertainties, especially those leading to low system robustness, and consequently improve their designs and implementations in terms of handling uncertainties. To this end, we present a comprehensive empirical study conducted with industrial elevator systems provided by our industrial partner Orona, which focuses on assessing the robustness of a dispatcher, i.e., a software component responsible for elevators’ optimal scheduling. In total, we studied 90 industrial dispatchers in our empirical study. Based on the experience gained from the study, we derived an uncertainty-aware robustness assessment method (named UncerRobua) comprising a set of guidelines on how to conduct the robustness assessment and a newly proposed ranking algorithm, for supporting the robustness assessment of industrial elevator systems against uncertainties. [-]
URI
https://hdl.handle.net/20.500.11984/5948
Argitaratzailearen bertsioa
https://doi.org/10.1145/3576041
ISSN
1557-7392
Non argitaratua
ACM Transactions on Software Engineering and Methodology 
Dokumentu-mota
Artikulua
Bertsioa
Postprinta – Accepted Manuscript
Eskubideak
© 2022 Association for Computing Machinery
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Sarbide irekia
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  • Artikuluak - Ingeniaritza [486]

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