TY - GEN
T1 - Robustness of Specifications and Its Applications to Falsification, Parameter Mining, and Runtime Monitoring with S-TaLiRo
AU - Fainekos, Georgios
AU - Hoxha, Bardh
AU - Sankaranarayanan, Sriram
N1 - Funding Information:
Acknowledgments. GF acknowledges support from NSF award 1350420. SS acknowledges support from NSF award numbers 1646556, 1815983 and the Air Force Research Laboratory (AFRL). All opinions expressed are those of the authors and not necessarily of the US NSF or AFRL.
Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Logical specifications have enabled formal methods by carefully describing what is correct, desired or expected of a given system. They have been widely used in runtime monitoring and applied to domains ranging from medical devices to information security. In this tutorial, we will present the theory and application of robustness of logical specifications. Rather than evaluate logical formulas to Boolean valuations, robustness interpretations attempt to provide numerical valuations that provide degrees of satisfaction, in addition to true/false valuations to models. Such a valuation can help us distinguish between behaviors that “barely” satisfy a specification to those that satisfy it in a robust manner. We will present and compare various notions of robustness in this tutorial, centered primarily around applications to safety-critical Cyber-Physical Systems (CPS). We will also present key ways in which the robustness notions can be applied to problems such as runtime monitoring, falsification search for finding counterexamples, and mining design parameters for synthesis.
AB - Logical specifications have enabled formal methods by carefully describing what is correct, desired or expected of a given system. They have been widely used in runtime monitoring and applied to domains ranging from medical devices to information security. In this tutorial, we will present the theory and application of robustness of logical specifications. Rather than evaluate logical formulas to Boolean valuations, robustness interpretations attempt to provide numerical valuations that provide degrees of satisfaction, in addition to true/false valuations to models. Such a valuation can help us distinguish between behaviors that “barely” satisfy a specification to those that satisfy it in a robust manner. We will present and compare various notions of robustness in this tutorial, centered primarily around applications to safety-critical Cyber-Physical Systems (CPS). We will also present key ways in which the robustness notions can be applied to problems such as runtime monitoring, falsification search for finding counterexamples, and mining design parameters for synthesis.
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U2 - 10.1007/978-3-030-32079-9_3
DO - 10.1007/978-3-030-32079-9_3
M3 - Conference contribution
AN - SCOPUS:85075724660
SN - 9783030320782
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 27
EP - 47
BT - Runtime Verification - 19th International Conference, RV 2019, Proceedings
A2 - Finkbeiner, Bernd
A2 - Mariani, Leonardo
PB - Springer
T2 - 19th International Conference on Runtime Verification, RV 2019 held as part of the 3rd World Congress on Formal Methods, FM 2019
Y2 - 8 October 2019 through 11 October 2019
ER -