Elaborating requirements using model checking and inductive learning

Autores
Uchitel, Sebastian; Alrajeh, Dalal; Kramer, Jeff; Russo, Alessandra
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The process of requirements engineering includes many activities, from goal elicitation to requirements specification. The aim is to develop an operational requirements specification that is guaranteed to satisfy the goals. In this paper, we propose a formal, systematic approach for generating a set of operational requirements that are complete with respect to given goals. We show how the integration of model checking and inductive learning can be effectively used to do this. The model checking formally verifies the satisfaction of the goals and produces counterexamples when incompleteness in the operational requirements is detected. The inductive learning process then computes operational requirements from the counterexamples and user-provided positive examples. These learned operational requirements are guaranteed to eliminate the counterexamples and be consistent with the goals. This process is performed iteratively until no goal violation is detected. The proposed framework is a rigorous, tool-supported requirements elaboration technique which is formally guided by the engineer´s knowledge of the domain and the envisioned system.
Fil: Uchitel, Sebastian. Imperial College London; Reino Unido. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Alrajeh, Dalal. Imperial College London; Reino Unido
Fil: Kramer, Jeff. Imperial College London; Reino Unido
Fil: Russo, Alessandra. Imperial College London; Reino Unido
Materia
Model Checking
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/2707
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/2707
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Elaborating requirements using model checking and inductive learningUchitel, SebastianAlrajeh, DalalKramer, JeffRusso, AlessandraModel Checkinghttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The process of requirements engineering includes many activities, from goal elicitation to requirements specification. The aim is to develop an operational requirements specification that is guaranteed to satisfy the goals. In this paper, we propose a formal, systematic approach for generating a set of operational requirements that are complete with respect to given goals. We show how the integration of model checking and inductive learning can be effectively used to do this. The model checking formally verifies the satisfaction of the goals and produces counterexamples when incompleteness in the operational requirements is detected. The inductive learning process then computes operational requirements from the counterexamples and user-provided positive examples. These learned operational requirements are guaranteed to eliminate the counterexamples and be consistent with the goals. This process is performed iteratively until no goal violation is detected. The proposed framework is a rigorous, tool-supported requirements elaboration technique which is formally guided by the engineer´s knowledge of the domain and the envisioned system.Fil: Uchitel, Sebastian. Imperial College London; Reino Unido. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Alrajeh, Dalal. Imperial College London; Reino UnidoFil: Kramer, Jeff. Imperial College London; Reino UnidoFil: Russo, Alessandra. Imperial College London; Reino UnidoIEEE Computer Society2012-06-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/2707Uchitel, Sebastian; Alrajeh, Dalal; Kramer, Jeff; Russo, Alessandra; Elaborating requirements using model checking and inductive learning; IEEE Computer Society; IEEE Transactions On Software Engineering; 39; 3; 3-2013; 361-3830098-5589enginfo:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/altIdentifier/url/http://www.computer.org/csdl/trans/ts/2013/03/tts2013030361-abs.htmlinfo:eu-repo/semantics/altIdentifier/doi/10.1109/TSE.2012.41info:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6216384info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:12:45Zoai:ri.conicet.gov.ar:11336/2707instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:12:45.372CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Elaborating requirements using model checking and inductive learning
title Elaborating requirements using model checking and inductive learning
spellingShingle Elaborating requirements using model checking and inductive learning
Uchitel, Sebastian
Model Checking
title_short Elaborating requirements using model checking and inductive learning
title_full Elaborating requirements using model checking and inductive learning
title_fullStr Elaborating requirements using model checking and inductive learning
title_full_unstemmed Elaborating requirements using model checking and inductive learning
title_sort Elaborating requirements using model checking and inductive learning
dc.creator.none.fl_str_mv Uchitel, Sebastian
Alrajeh, Dalal
Kramer, Jeff
Russo, Alessandra
author Uchitel, Sebastian
author_facet Uchitel, Sebastian
Alrajeh, Dalal
Kramer, Jeff
Russo, Alessandra
author_role author
author2 Alrajeh, Dalal
Kramer, Jeff
Russo, Alessandra
author2_role author
author
author
dc.subject.none.fl_str_mv Model Checking
topic Model Checking
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The process of requirements engineering includes many activities, from goal elicitation to requirements specification. The aim is to develop an operational requirements specification that is guaranteed to satisfy the goals. In this paper, we propose a formal, systematic approach for generating a set of operational requirements that are complete with respect to given goals. We show how the integration of model checking and inductive learning can be effectively used to do this. The model checking formally verifies the satisfaction of the goals and produces counterexamples when incompleteness in the operational requirements is detected. The inductive learning process then computes operational requirements from the counterexamples and user-provided positive examples. These learned operational requirements are guaranteed to eliminate the counterexamples and be consistent with the goals. This process is performed iteratively until no goal violation is detected. The proposed framework is a rigorous, tool-supported requirements elaboration technique which is formally guided by the engineer´s knowledge of the domain and the envisioned system.
Fil: Uchitel, Sebastian. Imperial College London; Reino Unido. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Alrajeh, Dalal. Imperial College London; Reino Unido
Fil: Kramer, Jeff. Imperial College London; Reino Unido
Fil: Russo, Alessandra. Imperial College London; Reino Unido
description The process of requirements engineering includes many activities, from goal elicitation to requirements specification. The aim is to develop an operational requirements specification that is guaranteed to satisfy the goals. In this paper, we propose a formal, systematic approach for generating a set of operational requirements that are complete with respect to given goals. We show how the integration of model checking and inductive learning can be effectively used to do this. The model checking formally verifies the satisfaction of the goals and produces counterexamples when incompleteness in the operational requirements is detected. The inductive learning process then computes operational requirements from the counterexamples and user-provided positive examples. These learned operational requirements are guaranteed to eliminate the counterexamples and be consistent with the goals. This process is performed iteratively until no goal violation is detected. The proposed framework is a rigorous, tool-supported requirements elaboration technique which is formally guided by the engineer´s knowledge of the domain and the envisioned system.
publishDate 2012
dc.date.none.fl_str_mv 2012-06-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/2707
Uchitel, Sebastian; Alrajeh, Dalal; Kramer, Jeff; Russo, Alessandra; Elaborating requirements using model checking and inductive learning; IEEE Computer Society; IEEE Transactions On Software Engineering; 39; 3; 3-2013; 361-383
0098-5589
url http://hdl.handle.net/11336/2707
identifier_str_mv Uchitel, Sebastian; Alrajeh, Dalal; Kramer, Jeff; Russo, Alessandra; Elaborating requirements using model checking and inductive learning; IEEE Computer Society; IEEE Transactions On Software Engineering; 39; 3; 3-2013; 361-383
0098-5589
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/
info:eu-repo/semantics/altIdentifier/url/http://www.computer.org/csdl/trans/ts/2013/03/tts2013030361-abs.html
info:eu-repo/semantics/altIdentifier/doi/10.1109/TSE.2012.41
info:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6216384
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv IEEE Computer Society
publisher.none.fl_str_mv IEEE Computer Society
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.069144

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