A Question answering model for requirements elicitation in the context of software development

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dc.contributor.advisorZapata Jaramillo, Carlos Mario
dc.contributor.authorCalle Gallego, Johnathan Mauricio
dc.contributor.researchgroupLenguajes Computacionalesspa
dc.date.accessioned2023-01-18T15:51:17Z
dc.date.available2023-01-18T15:51:17Z
dc.date.issued2022-04-04
dc.descriptionilustraciones, gráficosspa
dc.description.abstractRequirements Elicitation (RE) is focused on identifying and characterizing the stakeholders and their requirements. Such an activity may be challenging as the scope of the software product domain grows, generating errors and delays. Natural Language Processing (NLP) deals with automatically analyzing, understanding, and generating natural language. Software analysts use NLP-based approaches for improving RE, making it more efficient and reliable. However, domain scope and limitation for understanding the writing styles of requirements documents generate significant drawbacks for such approaches. In this Ph.D. Thesis we propose SQUARE (Scalable QUestion Answering for Requirements Elicitation), a novel approach for improving the NLP-based approaches for RE based on Question Answering Systems (QASs), comprising a meta-restricted domain for RE and a rule-based approach for generating RE-related questions and answers. QASs are used for extracting precise and concise answers to natural language questions. The SQUARE model represents a contribution for the NLP-based approaches for RE, allowing software analysts for identifying, extracting, and structuring key abstractions from requirements documents such as actors, actions, and concepts in a more natural way due to its proximity to a real-life RE domain. We validate our proposal by using an experimental process. The SQUARE model is included as a new work product for eliciting requirements. Therefore, the SQUARE model is intended to be an NLP-based approach to RE for software analysts.eng
dc.description.abstractLa Educción de Requisitos (ER) se enfoca en identificar y caracterizar a los interesados y sus requisitos. Esta actividad puede ser desafiante a medida que el alcance del dominio del producto de software crece, generando errores y retrasos. El Procesamiento de Lenguaje Natural (PLN) se usa para analizar, entender y generar lenguaje natural automáticamente. Los analistas de software usan enfoques basados en PLN para mejorar la ER, haciéndola más eficiente y confiable. Sin embargo, el alcance del dominio y la limitación para comprender los estilos de escritura de los documentos de requisitos generan inconvenientes importantes para estos enfoques. En esta Tesis Doctoral se presenta SQUARE (Scalable QUestion Answering for Requirements Elicitation por sus siglas en inglés), un enfoque novedoso para mejorar los enfoques basados en PLN para ER basado en Sistemas Pregunta-Respuesta (SPR), que comprende un dominio meta-restringido para ER y un enfoque basado en reglas para generar preguntas y respuestas relacionadas con la ER. Los SPR se usan para extraer respuestas precisas y concisas a preguntas en lenguaje natural. El modelo SQUARE representa una contribución a los enfoques basados en PLN para ER, permitiendo a los analistas de software identificar, extraer y estructurar abstracciones clave a partir de documentos de requisitos tales como actores, acciones y conceptos de una manera más natural debido a su proximidad con un dominio real de ER. Esta propuesta se valida usando un proceso experimental. El modelo SQUARE se incluye como un nuevo producto de trabajo para educir requisitos. Por lo tanto, el modelo SQUARE se espera que sea un enfoque de ER basado en PLN para analistas de software. (texto tomado de la fuente)spa
dc.description.curricularareaÁrea Curricular de Ingeniería de Sistemas e Informáticaspa
dc.description.degreelevelDoctoradospa
dc.description.degreenameDoctor en Ingenieríaspa
dc.description.researchareaIngeniería de requisitosspa
dc.description.researchareaProcesamiento de lenguaje naturalspa
dc.description.sponsorshipConvocatoria Doctorados nacionales 785 de 2017, Colcienciasspa
dc.format.extentxv, 115 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/83008
dc.language.isoengspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Medellínspa
dc.publisher.departmentDepartamento de la Computación y la Decisiónspa
dc.publisher.facultyFacultad de Minasspa
dc.publisher.placeMedellín, Colombiaspa
dc.publisher.programMedellín - Minas - Doctorado en Ingeniería - Sistemasspa
dc.relation.indexedLaReferenciaspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseReconocimiento 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/spa
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::004 - Procesamiento de datos Ciencia de los computadoresspa
dc.subject.lembIngeniería de software
dc.subject.lembDesarrollo del software
dc.subject.lembProcesamiento del lenguaje natural (Ciencia de computador)
dc.subject.proposalRequirements elicitationspa
dc.subject.proposalQuestion answering systemseng
dc.subject.proposalNatural language processingeng
dc.subject.proposalNamed entity recognitioneng
dc.subject.proposalMeta-ontologyeng
dc.subject.proposalEducción de requisitosspa
dc.subject.proposalSistemas pregunta respuestaspa
dc.subject.proposalProcesamiento de lenguaje naturalspa
dc.subject.proposalReconocimiento de entidades nombradasspa
dc.subject.proposalMeta-ontologíaspa
dc.titleA Question answering model for requirements elicitation in the context of software developmenteng
dc.title.translatedUn modelo preguta-respuesta para la educción de requisitos en el contexto del desarrollo de softwarespa
dc.typeTrabajo de grado - Doctoradospa
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dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/doctoralThesisspa
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dcterms.audience.professionaldevelopmentPúblico generalspa
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oaire.awardtitleA question answering model for eliciting requirements in the context of software developmentspa
oaire.fundernameMincienciasspa

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