dc.creator | Heradio, Ruben | es |
dc.creator | Fernández Amorós, David | es |
dc.creator | Galindo Duarte, José Ángel | es |
dc.creator | Benavides Cuevas, David Felipe | es |
dc.creator | Batory, Don | es |
dc.date.accessioned | 2022-06-30T09:52:18Z | |
dc.date.available | 2022-06-30T09:52:18Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Heradio, R., Fernández Amorós, D., Galindo Duarte, J.Á., Benavides Cuevas, D.F. y Batory, D. (2022). Uniform and scalable sampling of highly configurable systems. Empirical Software Engineering, 27 (2 - art. nº44) | |
dc.identifier.issn | 1382-3256 | es |
dc.identifier.uri | https://hdl.handle.net/11441/134837 | |
dc.description.abstract | Many analyses on confgurable software systems are intractable when confronted with
colossal and highly-constrained confguration spaces. These analyses could instead use
statistical inference, where a tractable sample accurately predicts results for the entire
space. To do so, the laws of statistical inference requires each member of the population
to be equally likely to be included in the sample, i.e., the sampling process needs to be
“uniform”. SAT-samplers have been developed to generate uniform random samples at a
reasonable computational cost. However, there is a lack of experimental validation over
colossal spaces to show whether the samplers indeed produce uniform samples or not. This
paper (i) proposes a new sampler named BDDSampler, (ii) presents a new statistical test
to verify sampler uniformity, and (iii) reports the evaluation of BDDSampler and fve
other state-of-the-art samplers: KUS, QuickSampler, Smarch, Spur, and Unigen2. Our
experimental results show only BDDSampler satisfes both scalability and uniformity. | es |
dc.description.sponsorship | Universidad Nacional de Educación a Distancia (UNED) OPTIVAC 096-034091 2021V/PUNED/008 | es |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades RTI2018-101204-B-C22 (OPHELIA) | es |
dc.description.sponsorship | Comunidad Autónoma de Madrid ROBOCITY2030-DIH-CM S2018/NMT-4331 | es |
dc.description.sponsorship | Agencia Estatal de Investigación TIN2017-90644-REDT | es |
dc.format | application/pdf | es |
dc.format.extent | 34 | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | Empirical Software Engineering, 27 (2 - art. nº44) | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Uniform sampling | es |
dc.subject | Confgurable systems | es |
dc.subject | Software product lines | es |
dc.subject | Binary decision diagrams | es |
dc.subject | SAT-solvers | es |
dc.title | Uniform and scalable sampling of highly configurable systems | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | OPTIVAC 096-034091 2021V/PUNED/008 | es |
dc.relation.projectID | RTI2018-101204-B-C22 (OPHELIA) | es |
dc.relation.projectID | ROBOCITY2030-DIH-CM S2018/NMT-4331 | es |
dc.relation.projectID | TIN2017-90644-REDT | es |
dc.relation.publisherversion | https://link.springer.com/article/10.1007/s10664-021-10102-5 | es |
dc.identifier.doi | 10.1007/s10664-021-10102-5 | es |
dc.contributor.group | Universidad de Sevilla. TIC258: Data-centric Computing Research Hub | es |
dc.journaltitle | Empirical Software Engineering | es |
dc.publication.volumen | 27 | es |
dc.publication.issue | 2 - art. nº44 | es |
dc.contributor.funder | Universidad Nacional de Educación a Distancia (UNED) | es |
dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades (MICINN). España | es |
dc.contributor.funder | Comunidad Autónoma de Madrid | es |
dc.contributor.funder | Agencia Estatal de Investigación. España | es |