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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/41842
Ver los metadatos del registro completo
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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 |
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2014-09 |
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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 |
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eng |
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eng |
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application/pdf 7-8 |
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