Improving requirements with NLP techniques

Autores
Rago, Alejandro
Año de publicación
2014
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Elaborating “good” requirements specifications is an important factor for the success of a software project. Requirements are normally expressed using textual descriptions in natural language, but not without problems. Some requirements documentation techniques, such as use cases specifications, often focus on functionality and leave many concerns understated in the text and scattered through several documents. These concerns, commonly known as crosscutting or architecturally-relevant concerns, often come from business goals or quality attributes that must be clearly identified by analysts and developers, as these concerns can have a far-reaching effect in the development process. Not treating these concerns at early development stages can lead to poor design solutions that become difficult (and costly) to fix afterwards. Unfortunately, searching for concerns in textual requirements is a difficult and time-consuming task for analysts, because requirements are often poorly modularized and there is text duplicated across documents. (Párrafo extraído del texto a modo de resumen)
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
Requirements/Specifications
Software
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/41842

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spelling Improving requirements with NLP techniquesRago, AlejandroCiencias InformáticasRequirements/SpecificationsSoftwareElaborating “good” requirements specifications is an important factor for the success of a software project. Requirements are normally expressed using textual descriptions in natural language, but not without problems. Some requirements documentation techniques, such as use cases specifications, often focus on functionality and leave many concerns understated in the text and scattered through several documents. These concerns, commonly known as crosscutting or architecturally-relevant concerns, often come from business goals or quality attributes that must be clearly identified by analysts and developers, as these concerns can have a far-reaching effect in the development process. Not treating these concerns at early development stages can lead to poor design solutions that become difficult (and costly) to fix afterwards. Unfortunately, searching for concerns in textual requirements is a difficult and time-consuming task for analysts, because requirements are often poorly modularized and there is text duplicated across documents. <i>(Párrafo extraído del texto a modo de resumen)</i>Sociedad Argentina de Informática e Investigación Operativa (SADIO)2014-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf7-8http://sedici.unlp.edu.ar/handle/10915/41842enginfo:eu-repo/semantics/altIdentifier/url/http://43jaiio.sadio.org.ar/proceedings/IJCAI/7-8.pdfinfo:eu-repo/semantics/altIdentifier/issn/2362-5120info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:33:55Zoai:sedici.unlp.edu.ar:10915/41842Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:33:56.141SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Improving requirements with NLP techniques
title Improving requirements with NLP techniques
spellingShingle Improving requirements with NLP techniques
Rago, Alejandro
Ciencias Informáticas
Requirements/Specifications
Software
title_short Improving requirements with NLP techniques
title_full Improving requirements with NLP techniques
title_fullStr Improving requirements with NLP techniques
title_full_unstemmed Improving requirements with NLP techniques
title_sort Improving requirements with NLP techniques
dc.creator.none.fl_str_mv Rago, Alejandro
author Rago, Alejandro
author_facet Rago, Alejandro
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Requirements/Specifications
Software
topic Ciencias Informáticas
Requirements/Specifications
Software
dc.description.none.fl_txt_mv Elaborating “good” requirements specifications is an important factor for the success of a software project. Requirements are normally expressed using textual descriptions in natural language, but not without problems. Some requirements documentation techniques, such as use cases specifications, often focus on functionality and leave many concerns understated in the text and scattered through several documents. These concerns, commonly known as crosscutting or architecturally-relevant concerns, often come from business goals or quality attributes that must be clearly identified by analysts and developers, as these concerns can have a far-reaching effect in the development process. Not treating these concerns at early development stages can lead to poor design solutions that become difficult (and costly) to fix afterwards. Unfortunately, searching for concerns in textual requirements is a difficult and time-consuming task for analysts, because requirements are often poorly modularized and there is text duplicated across documents. <i>(Párrafo extraído del texto a modo de resumen)</i>
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description Elaborating “good” requirements specifications is an important factor for the success of a software project. Requirements are normally expressed using textual descriptions in natural language, but not without problems. Some requirements documentation techniques, such as use cases specifications, often focus on functionality and leave many concerns understated in the text and scattered through several documents. These concerns, commonly known as crosscutting or architecturally-relevant concerns, often come from business goals or quality attributes that must be clearly identified by analysts and developers, as these concerns can have a far-reaching effect in the development process. Not treating these concerns at early development stages can lead to poor design solutions that become difficult (and costly) to fix afterwards. Unfortunately, searching for concerns in textual requirements is a difficult and time-consuming task for analysts, because requirements are often poorly modularized and there is text duplicated across documents. <i>(Párrafo extraído del texto a modo de resumen)</i>
publishDate 2014
dc.date.none.fl_str_mv 2014-09
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