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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2018
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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. |
format | Online Article Text |
id | pubmed-6428225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
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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