dc.contributor.author | Valle Entrena, Pablo | |
dc.contributor.author | Riccio, Vincenzo | |
dc.contributor.author | Arrieta, Aitor | |
dc.contributor.author | Tonella, Paolo | |
dc.contributor.author | Arratibel, Maite | |
dc.date.accessioned | 2025-07-17T08:43:28Z | |
dc.date.available | 2025-07-17T08:43:28Z | |
dc.date.issued | 2025 | |
dc.identifier.issn | 1573-7616 | en |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=188560 | en |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/13918 | |
dc.description.abstract | Testing Cyber Physical Systems (CPS) is crucial, as they play a central role in modern society. In the complex input space of these systems, boundary test inputs provide a valuable asset for test engineers as they identify slight input modifications that dramatically impact Quality of Service. In this experience paper, we propose LiftJanus, the first search-based test generator for CPS that integrates test input minimization, boundary value detection, and automated system repair. We performed an empirical study involving two real-world elevator systems provided by our industrial collaborator, Orona. Our results proved that LiftJanus generated boundary inputs twice as effective as the baselines, with the repair algorithm successfully enhancing the system’s configuration in 76.25% of the cases. Interviews with domain experts confirmed that LiftJanus is a comprehensive solution for enhancing the quality of elevator systems. | en |
dc.language.iso | eng | en |
dc.publisher | Springer | en |
dc.rights | © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025 | en |
dc.subject | Cyber-Physical Systems | en |
dc.subject | Search-based test input generation | en |
dc.subject | Simulation-based testing | en |
dc.title | An industrial experience report on applying search-based boundary input generation to cyber-physical systems | en |
dcterms.accessRights | http://purl.org/coar/access_right/c_f1cf | en |
dcterms.source | Empirical Software Engineering | en |
local.contributor.group | Ingeniería del software y sistemas | es |
local.description.peerreviewed | true | en |
local.identifier.doi | https://doi.org/10.1007/s10664-025-10670-w | en |
local.embargo.enddate | 2145-12-31 | |
local.contributor.otherinstitution | https://ror.org/05ht0mh31 | es |
local.contributor.otherinstitution | https://ror.org/03c4atk17 | es |
local.contributor.otherinstitution | Orona | es |
local.source.details | Vol. 30. N. art, 112, 2025 | en |
oaire.format.mimetype | application/pdf | en |
oaire.file | $DSPACE\assetstore | en |
oaire.resourceType | http://purl.org/coar/resource_type/c_6501 | en |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | en |
dc.unesco.tesauro | http://vocabularies.unesco.org/thesaurus/concept450 | en |
oaire.funderName | Gobierno Vasco | en |
oaire.funderName | Gobierno de España | en |
oaire.funderIdentifier | https://ror.org/00pz2fp31 / http://data.crossref.org/fundingdata/funder/10.13039/501100003086 | en |
oaire.funderIdentifier | https://ror.org/038jjxj40 / http://data.crossref.org/fundingdata/funder/10.13039/501100010198 | en |
oaire.fundingStream | Ikertalde Convocatoria 2022-2023 | en |
oaire.fundingStream | Proyectos de Generación de Conocimento y Formación de Investigadores Predoctorales, Convocatoria 2023 | en |
oaire.awardNumber | IT1519-22 | en |
oaire.awardNumber | PID2023-152979OA-I00 | en |
oaire.awardTitle | Ingeniería de Software y Sistemas (IKERTALDE 2022-2023) | en |
oaire.awardTitle | Reparación Automática de Sistemas Ciberfísicos (ATRACT) | en |
oaire.awardURI | Sin información | en |
oaire.awardURI | Sin información | en |
dc.unesco.clasificacion | http://skos.um.es/unesco6/120317 | en |