dc.contributor.author | Ayerdi, Jon | |
dc.contributor.author | Arrieta, Aitor | |
dc.contributor.author | Sagardui, Goiuria | |
dc.contributor.other | Terragni, Valerio | |
dc.contributor.other | Tonella, Paolo | |
dc.contributor.other | Arratibel, Maite | |
dc.date.accessioned | 2022-12-07T08:36:50Z | |
dc.date.available | 2022-12-07T08:36:50Z | |
dc.date.issued | 2022 | |
dc.identifier.isbn | 978-1-4503-9268-6 | en |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=169003 | en |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/5907 | |
dc.description.abstract | A problem when testing Cyber-Physical Systems (CPS) is the difficulty of determining whether a particular system output or behaviour is correct or not. Metamorphic testing alleviates such a problem by reasoning on the relations expected to hold among multiple executions of the system under test, which are known as Metamorphic Relations (MRs). However, the development of effective MRs is often challenging and requires the involvement of domain experts. This paper summarizes our recent publication: "Generating Metamorphic Relations for Cyber-Physical Systems with Genetic Programming: An Industrial Case Study", presented at ESEC/FSE 2021. In that publication we presented GAssertMRs, the first technique to automatically generate MRs for CPS, leveraging GP to explore the space of candidate solutions. We evaluated GAssertMRs in an industrial case study, outperforming other baselines. | en |
dc.description.sponsorship | Comisión Europea | es |
dc.description.sponsorship | Gobierno Vasco-Eusko Jaurlaritza | es |
dc.language.iso | eng | en |
dc.publisher | ACM | en |
dc.rights | © 2022 The Authors | en |
dc.subject | cyber physical systems | en |
dc.subject | Metamorphic Testing | en |
dc.subject | Quality of Service | en |
dc.subject | oracle generation | en |
dc.subject | oracle improvement | en |
dc.subject | evolutionary algorithm | en |
dc.subject | genetic programming | en |
dc.subject | mutation testing | en |
dc.title | Evolutionary generation of metamorphic relations for cyber-physical systems | es |
dcterms.accessRights | http://purl.org/coar/access_right/c_abf2 | en |
dcterms.source | Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '22) | en |
local.contributor.group | Ingeniería del software y sistemas | es |
local.description.peerreviewed | true | en |
local.description.publicationfirstpage | 15 | en |
local.description.publicationlastpage | 16 | en |
local.identifier.doi | https://doi.org/10.1145/3520304.3534077 | en |
local.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/871319/EU/Design-Operation Continuum Methods for Testing and Deployment under Unforeseen Conditions for Cyber-Physical Systems of Systems/ADEPTNESS | en |
local.relation.projectID | info:eu-repo/grantAgreement/EC/H2020. ERC Advanced Grant 2017 Program/787703/EU/Self-assessment Oracles for Anticipatory Testing/PRECRIME | en |
local.relation.projectID | info:eu-repo/grantAgreement/GV/Ikertalde Convocatoria 2022-2023/IT1519-22/CAPV/Ingeniería de Software y Sistemas/ | en |
local.contributor.otherinstitution | https://ror.org/03b94tp07 | en |
local.contributor.otherinstitution | https://ror.org/03c4atk17 | es |
local.contributor.otherinstitution | Orona S.Coop. | es |
local.source.details | Boston, 9-13 July 2022. Pp. 15–16. New York: Association for Computing Machinery, 2022 | en |
oaire.format.mimetype | application/pdf | |
oaire.file | $DSPACE\assetstore | |
oaire.resourceType | http://purl.org/coar/resource_type/c_c94f | en |
oaire.version | http://purl.org/coar/version/c_ab4af688f83e57aa | en |