An expressive and enriched specification language to synthesize behavior in BIG DATA systems
- Autores
- Asteasuain, Fernando; Rodriguez Caldeira, Luciana
- Año de publicación
- 2021
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- In this work we extend our behavioral specification and controller synthesis framework FVS to deal with BIG DATA requirements. For one side, we enriched FVS expressive power by exhibiting how our language can handle fluents and partial specifications. For the other side, we combined FVS with a parallel model checker in order to automatically obtain a controller given the behavior specification. In this way, FVS can be presented as an attractive tool to formally verify and synthesize behavior for BIG DATA systems. Our approach is compared to other well known parallel tool analyzing a complex big data system.
Workshop: WIS - Ingeniería de Software
Red de Universidades con Carreras en Informática - Materia
-
Ciencias Informáticas
Formal verification
Big data
Parallel model checkers - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/130421
Ver los metadatos del registro completo
| id |
SEDICI_178ce69e14b94c843077da544a5c0011 |
|---|---|
| oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/130421 |
| network_acronym_str |
SEDICI |
| repository_id_str |
1329 |
| network_name_str |
SEDICI (UNLP) |
| spelling |
An expressive and enriched specification language to synthesize behavior in BIG DATA systemsAsteasuain, FernandoRodriguez Caldeira, LucianaCiencias InformáticasFormal verificationBig dataParallel model checkersIn this work we extend our behavioral specification and controller synthesis framework FVS to deal with BIG DATA requirements. For one side, we enriched FVS expressive power by exhibiting how our language can handle fluents and partial specifications. For the other side, we combined FVS with a parallel model checker in order to automatically obtain a controller given the behavior specification. In this way, FVS can be presented as an attractive tool to formally verify and synthesize behavior for BIG DATA systems. Our approach is compared to other well known parallel tool analyzing a complex big data system.Workshop: WIS - Ingeniería de SoftwareRed de Universidades con Carreras en Informática2021-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf357-366http://sedici.unlp.edu.ar/handle/10915/130421enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-633-574-4info:eu-repo/semantics/reference/hdl/10915/129809info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:32:47Zoai:sedici.unlp.edu.ar:10915/130421Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:32:48.038SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
An expressive and enriched specification language to synthesize behavior in BIG DATA systems |
| title |
An expressive and enriched specification language to synthesize behavior in BIG DATA systems |
| spellingShingle |
An expressive and enriched specification language to synthesize behavior in BIG DATA systems Asteasuain, Fernando Ciencias Informáticas Formal verification Big data Parallel model checkers |
| title_short |
An expressive and enriched specification language to synthesize behavior in BIG DATA systems |
| title_full |
An expressive and enriched specification language to synthesize behavior in BIG DATA systems |
| title_fullStr |
An expressive and enriched specification language to synthesize behavior in BIG DATA systems |
| title_full_unstemmed |
An expressive and enriched specification language to synthesize behavior in BIG DATA systems |
| title_sort |
An expressive and enriched specification language to synthesize behavior in BIG DATA systems |
| dc.creator.none.fl_str_mv |
Asteasuain, Fernando Rodriguez Caldeira, Luciana |
| author |
Asteasuain, Fernando |
| author_facet |
Asteasuain, Fernando Rodriguez Caldeira, Luciana |
| author_role |
author |
| author2 |
Rodriguez Caldeira, Luciana |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas Formal verification Big data Parallel model checkers |
| topic |
Ciencias Informáticas Formal verification Big data Parallel model checkers |
| dc.description.none.fl_txt_mv |
In this work we extend our behavioral specification and controller synthesis framework FVS to deal with BIG DATA requirements. For one side, we enriched FVS expressive power by exhibiting how our language can handle fluents and partial specifications. For the other side, we combined FVS with a parallel model checker in order to automatically obtain a controller given the behavior specification. In this way, FVS can be presented as an attractive tool to formally verify and synthesize behavior for BIG DATA systems. Our approach is compared to other well known parallel tool analyzing a complex big data system. Workshop: WIS - Ingeniería de Software Red de Universidades con Carreras en Informática |
| description |
In this work we extend our behavioral specification and controller synthesis framework FVS to deal with BIG DATA requirements. For one side, we enriched FVS expressive power by exhibiting how our language can handle fluents and partial specifications. For the other side, we combined FVS with a parallel model checker in order to automatically obtain a controller given the behavior specification. In this way, FVS can be presented as an attractive tool to formally verify and synthesize behavior for BIG DATA systems. Our approach is compared to other well known parallel tool analyzing a complex big data system. |
| publishDate |
2021 |
| dc.date.none.fl_str_mv |
2021-10 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
| format |
conferenceObject |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/130421 |
| url |
http://sedici.unlp.edu.ar/handle/10915/130421 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/isbn/978-987-633-574-4 info:eu-repo/semantics/reference/hdl/10915/129809 |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
| dc.format.none.fl_str_mv |
application/pdf 357-366 |
| dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
| reponame_str |
SEDICI (UNLP) |
| collection |
SEDICI (UNLP) |
| instname_str |
Universidad Nacional de La Plata |
| instacron_str |
UNLP |
| institution |
UNLP |
| repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
| repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
| _version_ |
1844616207490088960 |
| score |
13.070432 |