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Quantitative monitoring of STL with edit distance

In cyber-physical systems (CPS), physical behaviors are typically controlled by digital hardware. As a consequence, continuous behaviors are discretized by sampling and quantization prior to their processing. Quantifying the similarity between CPS behaviors and their specification is an important in...

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Autores principales: Jakšić, Stefan, Bartocci, Ezio, Grosu, Radu, Nguyen, Thang, Ničković, Dejan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428225/
https://www.ncbi.nlm.nih.gov/pubmed/30956399
http://dx.doi.org/10.1007/s10703-018-0319-x
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author Jakšić, Stefan
Bartocci, Ezio
Grosu, Radu
Nguyen, Thang
Ničković, Dejan
author_facet Jakšić, Stefan
Bartocci, Ezio
Grosu, Radu
Nguyen, Thang
Ničković, Dejan
author_sort Jakšić, Stefan
collection PubMed
description In cyber-physical systems (CPS), physical behaviors are typically controlled by digital hardware. As a consequence, continuous behaviors are discretized by sampling and quantization prior to their processing. Quantifying the similarity between CPS behaviors and their specification is an important ingredient in evaluating correctness and quality of such systems. We propose a novel procedure for measuring robustness between digitized CPS signals and signal temporal logic (STL) specifications. We first equip STL with quantitative semantics based on the weighted edit distance, a metric that quantifies both space and time mismatches between digitized CPS behaviors. We then develop a dynamic programming algorithm for computing the robustness degree between digitized signals and STL specifications. In order to promote hardware-based monitors we implemented our approach in FPGA. We evaluated it on automotive benchmarks defined by research community, and also on realistic data obtained from magnetic sensor used in modern cars.
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spelling pubmed-64282252019-04-05 Quantitative monitoring of STL with edit distance Jakšić, Stefan Bartocci, Ezio Grosu, Radu Nguyen, Thang Ničković, Dejan Form Methods Syst Des Article In cyber-physical systems (CPS), physical behaviors are typically controlled by digital hardware. As a consequence, continuous behaviors are discretized by sampling and quantization prior to their processing. Quantifying the similarity between CPS behaviors and their specification is an important ingredient in evaluating correctness and quality of such systems. We propose a novel procedure for measuring robustness between digitized CPS signals and signal temporal logic (STL) specifications. We first equip STL with quantitative semantics based on the weighted edit distance, a metric that quantifies both space and time mismatches between digitized CPS behaviors. We then develop a dynamic programming algorithm for computing the robustness degree between digitized signals and STL specifications. In order to promote hardware-based monitors we implemented our approach in FPGA. We evaluated it on automotive benchmarks defined by research community, and also on realistic data obtained from magnetic sensor used in modern cars. Springer US 2018-03-27 2018 /pmc/articles/PMC6428225/ /pubmed/30956399 http://dx.doi.org/10.1007/s10703-018-0319-x Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Jakšić, Stefan
Bartocci, Ezio
Grosu, Radu
Nguyen, Thang
Ničković, Dejan
Quantitative monitoring of STL with edit distance
title Quantitative monitoring of STL with edit distance
title_full Quantitative monitoring of STL with edit distance
title_fullStr Quantitative monitoring of STL with edit distance
title_full_unstemmed Quantitative monitoring of STL with edit distance
title_short Quantitative monitoring of STL with edit distance
title_sort quantitative monitoring of stl with edit distance
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428225/
https://www.ncbi.nlm.nih.gov/pubmed/30956399
http://dx.doi.org/10.1007/s10703-018-0319-x
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