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Probabilistic Worst-Case Timing Analysis: Taxonomy and Comprehensive Survey

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Probabilistic Worst-Case Timing Analysis: Taxonomy and Comprehensive Survey

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dc.contributor.author Cazorla, Francisco J. es_ES
dc.contributor.author Kosmidis, L. es_ES
dc.contributor.author Mezzetti, E. es_ES
dc.contributor.author Hernández Luz, Carles es_ES
dc.contributor.author Abella, Jaume es_ES
dc.contributor.author Vardanega, Tullio es_ES
dc.date.accessioned 2020-07-07T03:33:37Z
dc.date.available 2020-07-07T03:33:37Z
dc.date.issued 2019-02 es_ES
dc.identifier.issn 0360-0300 es_ES
dc.identifier.uri http://hdl.handle.net/10251/147545
dc.description "© ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Computing Surveys, {VOL 52, ISS 1, (February 2019)} https://dl.acm.org/doi/10.1145/3301283" es_ES
dc.description.abstract [EN] The unabated increase in the complexity of the hardware and software components of modern embedded real-time systems has given momentum to a host of research in the use of probabilistic and statistical techniques for timing analysis. In the last few years, that front of investigation has yielded a body of scientific literature vast enough to warrant some comprehensive taxonomy of motivations, strategies of application, and directions of research. This survey addresses this very need, singling out the principal techniques in the state of the art of timing analysis that employ probabilistic reasoning at some level, building a taxonomy of them, discussing their relative merit and limitations, and the relations among them. In addition to offering a comprehensive foundation to savvy probabilistic timing analysis, this article also identifies the key challenges to be addressed to consolidate the scientific soundness and industrial viability of this emerging field. es_ES
dc.description.sponsorship This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P, the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773), and the HiPEAC Network of Excellence. Jaume Abella was partially supported by the Ministry of Economy and Competitiveness under a Ramon y Cajal postdoctoral fellowship (RYC-2013-14717). Enrico Mezzetti has been partially supported by the Spanish Ministry of Economy and Competitiveness under Juan de la Cierva-Incorporación postdoctoral fellowship No. IJCI-2016-27396. es_ES
dc.language Inglés es_ES
dc.publisher Association for Computing Machinery es_ES
dc.relation info:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/ es_ES
dc.relation info:eu-repo/grantAgreement/MINECO//RYC-2013-14717/ES/RYC-2013-14717/ es_ES
dc.relation MINECO/IJCI-2016-27396 es_ES
dc.relation.ispartof ACM Computing Surveys es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Worst-case execution time es_ES
dc.subject Probabilistic analysis es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Probabilistic Worst-Case Timing Analysis: Taxonomy and Comprehensive Survey es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1145/3301283 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/772773/EU/Sustainable Performance for High-Performance Embedded Computing Systems/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.description.bibliographicCitation Cazorla, FJ.; Kosmidis, L.; Mezzetti, E.; Hernández Luz, C.; Abella, J.; Vardanega, T. (2019). Probabilistic Worst-Case Timing Analysis: Taxonomy and Comprehensive Survey. ACM Computing Surveys. 52(1):1-35. https://doi.org/10.1145/3301283 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1145/3301283 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 35 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 52 es_ES
dc.description.issue 1 es_ES
dc.relation.pasarela S\393379 es_ES
dc.contributor.funder HiPEAC Network of Excellence es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES


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