Documenting requirements specifications using natural language requirements boilerplates

Ibrahim, Norazana; Kadir, Wan Hazli Wan; Deris, Safaai

doi:10.1109/mysec.2014.6985983

Cited by 10 publications

(4 citation statements)

References 14 publications

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“…Comparing NL with DFD, the NL group scored higher than the DFD group, and had fewer difficulties. Ibrahim et al [6] reported that the natural language is commonly used for documenting the stakeholders' statements in the requirements elicitation activity. In addition, it has also been found that using the language of the customers to describe the software requirements is most effective in gaining the customers understanding and agreement [7].…”

Section: Resultsmentioning

confidence: 99%

Identify the effective documentation method for representing the functional software architecture

Ibriwesh¹,

Ho²,

Chai³

2018

IJET

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Software architecture mainly focuses on the high-level structures of the proposed software, and how to document these structures. A documentation method that represents an incomplete picture is one reason for inadequate requirements. This leads to requirements engineers wasting their time arguing over what to do and how to do it. Four documentation methods are frequently used in order to document stakeholders' statements, particularly for representing the functional perspective, namely, Natural Language (NL), Data Flow Diagram (DFD), Use Case Diagram (UCD), and Activity Diagram (AD). This research was carried out using the electronic market application domain as a test context. A controlled experiment was conducted among 158 participants, comparing among NL, DFD, UCD, and AD methods, which aimed to find out which requirements documentation method is more effective, helpful, and easier to comprehend. The results from this empirical study reveal that the AD method is more effective, understandable, and easier to document the software requirements in the functional perspective. Furthermore, AD had better performance in representing the requirements engineering context, system context, and development context than the other functional documentation methods. These empirical results would help software companies and associated experts enhance the quality of their software products, as well as increase the chance of success of software projects.

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Section: Resultsmentioning

confidence: 99%

Identify the effective documentation method for representing the functional software architecture

Ibriwesh¹,

Ho²,

Chai³

2018

IJET

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“…Requirements originate from stakeholders in natural language [1]. Non-functional requirements (NFRs) are always associated with functional requirements (FRs) [2].…”

Section: Introductionmentioning

confidence: 99%

Multi-label Classifier to Deal with Misclassification in Non-functional Requirements

Sabir

Chrysoulas

Banissi

2020

Advances in Intelligent Systems and Computing

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Automatic classification of software requirements is an active research area; it can alleviate the tedious task of manual labeling and improves transparency in the requirements engineering process. Several attempts have been made towards the identification and classification by type of functional requirements (FRs) as well as non-functional requirements (NFRs). Previous work in this area suffers from misclassification. This study investigates issues with NFRs in particular the limitations of existing methods in the classification of NFRs. The goal of this work is to minimize misclassification and help stakeholders consider NFRs in early phases of development through automatically classifying requirements. In this study, we have proposed an improved requirement detection and classification technique. The following summarizes the proposed approach: A newly created labeled corpus. Textual semantics to augment user requirements by word2vec for automatically extracting features, and A convolution neural network-based multi-label requirement classifier that classifies NFRs into five classes: reliability, efficiency, portability, usability, and maintainability.

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“…Durante el proceso de educción de requisitos se ejecutan entrevistas, sin embargo, los stakeholders pueden estar obviando información importante [2]; como complemento, se puede obtener información desde otras fuentes, como documentos de negocio [3]. Algunos de los documentos de negocio contribuyen al conocimiento del dominio [4], son escritos en lenguaje natural y se reconocen como documentos de procesos, documentos de requisitos, especificación de diseño, escenarios de casos de uso, entre otros.…”

Section: Introductionunclassified

Método para la representación semi-automática de modelos conceptuales desde documentos de negocio escritos en lenguaje natural en español

Marín-Alvarez

Losada

Quintero

2020

Ingeniare. Rev. chil. ing.

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Actualmente la industria de desarrollo de software presenta grandes retos para el procesamiento de información de negocio, particularmente aquella contenida en documentos textuales. En el proceso de educción de requisitos de software una fuente potencial de información relevante son los documentos de negocio, pues a partir de éstos se puede facilitar la comprensión de conocimiento de un dominio, así como conocer la evolución de un producto. A pesar de su utilidad, los ingenieros de requisitos no siempre la usan para su labor por los tiempos y costos que implica. En el presente trabajo se aborda esta problemática y se reconoce por medio de una revisión sistemática, la potencialidad de usar técnicas de Procesamiento de Lenguaje Natural (NLP por sus siglas en inglés) para extraer información textual relevante de documentos de negocio, y la utilidad de representarla en modelos conceptuales. A partir de esto, se propone un método semi-automático de extracción de información desde documentos de negocio escritos en lenguaje natural en español y su representación en un modelo conceptual. El método se soporta en un marco metodológico de referencia para proyectos de Analítica de Texto, se fundamenta en técnicas de NLP, y se representa la salida en un diagrama de clases. El método fue evaluado mediante un caso de estudio con analistas de software en Medellín-Colombia, tomando como entrada documentos de resolución de telecomunicaciones. La evaluación permite concluir que el modelo es una satisfactoria aproximación a solucionar el problema planteado mejorando el tiempo de procesamiento y manteniendo un nivel de interpretación similar al proceso manual. Palabras clave: Procesamiento de lenguaje natural, POS Tagging, modelo conceptual, educción de requisitos.

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Documenting requirements specifications using natural language requirements boilerplates

Cited by 10 publications

References 14 publications

Identify the effective documentation method for representing the functional software architecture

Identify the effective documentation method for representing the functional software architecture

Multi-label Classifier to Deal with Misclassification in Non-functional Requirements

Método para la representación semi-automática de modelos conceptuales desde documentos de negocio escritos en lenguaje natural en español

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