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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/2707
Ver los metadatos del registro completo
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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 Técnicas2025-09-03T10:00:38Zoai: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:34982025-09-03 10:00:38.348CONICET 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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1842269650276057088 |
score |
13.13397 |