Identifying duplicate functionality in textual use cases by aligning semantic actions
- Autores
- Rago, Alejandro Miguel; Marcos, Claudia Andrea; Diaz Pace, Jorge Andres
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Developing high-quality requirements specifications often demands a thoughtful analysis and an adequate level of expertise from analysts. Although requirements modeling techniques provide mechanisms for abstraction and clarity, fostering the reuse of shared functionality (e.g., via UML relationships for use cases), they are seldom employed in practice. A particular quality problem of textual requirements, such as use cases, is that of having duplicate pieces of functionality scattered across the specifications. Duplicate functionality can sometimes improve readability for end users, but hinders development-related tasks such as effort estimation, feature prioritization, and maintenance, among others. Unfortunately, inspecting textual requirements by hand in order to deal with redundant functionality can be an arduous, time-consuming, and error-prone activity for analysts. In this context, we introduce a novel approach called ReqAligner that aids analysts to spot signs of duplication in use cases in an automated fashion. To do so, ReqAligner combines several text processing techniques, such as a use case-aware classifier and a customized algorithm for sequence alignment. Essentially, the classifier converts the use cases into an abstract representation that consists of sequences of semantic actions, and then these sequences are compared pairwise in order to identify action matches, which become possible duplications. We have applied our technique to five real-world specifications, achieving promising results and identifying many sources of duplication in the use cases.
Fil: Rago, Alejandro Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Marcos, Claudia Andrea. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina
Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina - Materia
-
Machine Learning
Natural Language Processing
Requirements Engineering
Sequence Alignment
Use Case Modeling
Use Case Refactoring - 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:11336/58417
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Identifying duplicate functionality in textual use cases by aligning semantic actionsRago, Alejandro MiguelMarcos, Claudia AndreaDiaz Pace, Jorge AndresMachine LearningNatural Language ProcessingRequirements EngineeringSequence AlignmentUse Case ModelingUse Case Refactoringhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Developing high-quality requirements specifications often demands a thoughtful analysis and an adequate level of expertise from analysts. Although requirements modeling techniques provide mechanisms for abstraction and clarity, fostering the reuse of shared functionality (e.g., via UML relationships for use cases), they are seldom employed in practice. A particular quality problem of textual requirements, such as use cases, is that of having duplicate pieces of functionality scattered across the specifications. Duplicate functionality can sometimes improve readability for end users, but hinders development-related tasks such as effort estimation, feature prioritization, and maintenance, among others. Unfortunately, inspecting textual requirements by hand in order to deal with redundant functionality can be an arduous, time-consuming, and error-prone activity for analysts. In this context, we introduce a novel approach called ReqAligner that aids analysts to spot signs of duplication in use cases in an automated fashion. To do so, ReqAligner combines several text processing techniques, such as a use case-aware classifier and a customized algorithm for sequence alignment. Essentially, the classifier converts the use cases into an abstract representation that consists of sequences of semantic actions, and then these sequences are compared pairwise in order to identify action matches, which become possible duplications. We have applied our technique to five real-world specifications, achieving promising results and identifying many sources of duplication in the use cases.Fil: Rago, Alejandro Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Marcos, Claudia Andrea. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; ArgentinaFil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaSpringer Heidelberg2016-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/58417Rago, Alejandro Miguel; Marcos, Claudia Andrea; Diaz Pace, Jorge Andres; Identifying duplicate functionality in textual use cases by aligning semantic actions; Springer Heidelberg; Software and Systems Modeling; 15; 2; 5-2016; 579-6031619-13661619-1374CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1007/s10270-014-0431-3info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10270-014-0431-3info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:48:33Zoai:ri.conicet.gov.ar:11336/58417instacron: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 09:48:33.778CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Identifying duplicate functionality in textual use cases by aligning semantic actions |
title |
Identifying duplicate functionality in textual use cases by aligning semantic actions |
spellingShingle |
Identifying duplicate functionality in textual use cases by aligning semantic actions Rago, Alejandro Miguel Machine Learning Natural Language Processing Requirements Engineering Sequence Alignment Use Case Modeling Use Case Refactoring |
title_short |
Identifying duplicate functionality in textual use cases by aligning semantic actions |
title_full |
Identifying duplicate functionality in textual use cases by aligning semantic actions |
title_fullStr |
Identifying duplicate functionality in textual use cases by aligning semantic actions |
title_full_unstemmed |
Identifying duplicate functionality in textual use cases by aligning semantic actions |
title_sort |
Identifying duplicate functionality in textual use cases by aligning semantic actions |
dc.creator.none.fl_str_mv |
Rago, Alejandro Miguel Marcos, Claudia Andrea Diaz Pace, Jorge Andres |
author |
Rago, Alejandro Miguel |
author_facet |
Rago, Alejandro Miguel Marcos, Claudia Andrea Diaz Pace, Jorge Andres |
author_role |
author |
author2 |
Marcos, Claudia Andrea Diaz Pace, Jorge Andres |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Machine Learning Natural Language Processing Requirements Engineering Sequence Alignment Use Case Modeling Use Case Refactoring |
topic |
Machine Learning Natural Language Processing Requirements Engineering Sequence Alignment Use Case Modeling Use Case Refactoring |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Developing high-quality requirements specifications often demands a thoughtful analysis and an adequate level of expertise from analysts. Although requirements modeling techniques provide mechanisms for abstraction and clarity, fostering the reuse of shared functionality (e.g., via UML relationships for use cases), they are seldom employed in practice. A particular quality problem of textual requirements, such as use cases, is that of having duplicate pieces of functionality scattered across the specifications. Duplicate functionality can sometimes improve readability for end users, but hinders development-related tasks such as effort estimation, feature prioritization, and maintenance, among others. Unfortunately, inspecting textual requirements by hand in order to deal with redundant functionality can be an arduous, time-consuming, and error-prone activity for analysts. In this context, we introduce a novel approach called ReqAligner that aids analysts to spot signs of duplication in use cases in an automated fashion. To do so, ReqAligner combines several text processing techniques, such as a use case-aware classifier and a customized algorithm for sequence alignment. Essentially, the classifier converts the use cases into an abstract representation that consists of sequences of semantic actions, and then these sequences are compared pairwise in order to identify action matches, which become possible duplications. We have applied our technique to five real-world specifications, achieving promising results and identifying many sources of duplication in the use cases. Fil: Rago, Alejandro Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Marcos, Claudia Andrea. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina |
description |
Developing high-quality requirements specifications often demands a thoughtful analysis and an adequate level of expertise from analysts. Although requirements modeling techniques provide mechanisms for abstraction and clarity, fostering the reuse of shared functionality (e.g., via UML relationships for use cases), they are seldom employed in practice. A particular quality problem of textual requirements, such as use cases, is that of having duplicate pieces of functionality scattered across the specifications. Duplicate functionality can sometimes improve readability for end users, but hinders development-related tasks such as effort estimation, feature prioritization, and maintenance, among others. Unfortunately, inspecting textual requirements by hand in order to deal with redundant functionality can be an arduous, time-consuming, and error-prone activity for analysts. In this context, we introduce a novel approach called ReqAligner that aids analysts to spot signs of duplication in use cases in an automated fashion. To do so, ReqAligner combines several text processing techniques, such as a use case-aware classifier and a customized algorithm for sequence alignment. Essentially, the classifier converts the use cases into an abstract representation that consists of sequences of semantic actions, and then these sequences are compared pairwise in order to identify action matches, which become possible duplications. We have applied our technique to five real-world specifications, achieving promising results and identifying many sources of duplication in the use cases. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-05 |
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/11336/58417 Rago, Alejandro Miguel; Marcos, Claudia Andrea; Diaz Pace, Jorge Andres; Identifying duplicate functionality in textual use cases by aligning semantic actions; Springer Heidelberg; Software and Systems Modeling; 15; 2; 5-2016; 579-603 1619-1366 1619-1374 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/58417 |
identifier_str_mv |
Rago, Alejandro Miguel; Marcos, Claudia Andrea; Diaz Pace, Jorge Andres; Identifying duplicate functionality in textual use cases by aligning semantic actions; Springer Heidelberg; Software and Systems Modeling; 15; 2; 5-2016; 579-603 1619-1366 1619-1374 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1007/s10270-014-0431-3 info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10270-014-0431-3 |
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 |
Springer Heidelberg |
publisher.none.fl_str_mv |
Springer Heidelberg |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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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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13.13397 |