Mining Architectural Responsibilities and Components from Textual Specifications Written in Natural Language

Autores/as

  • A. Casamayor Universidad Nacional del Centro de la provincia de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina
  • D. Godoy Universidad Nacional del Centro de la provincia de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina
  • M. Campo Universidad Nacional del Centro de la provincia de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina

Palabras clave:

software design, architectural responsibilities, architectural components, requirements engineering, text mining techniques, part-of-speech tagging

Resumen

Given the enormous growth and complexity of modern software systems, architectural design has become an essential concern for almost every software development project. One of the most challenging steps for designing the best architecture for a certain piece of software is the analysis of requirements, usually written in natural language by engineers not familiar with specific design formalisms. The Use Case Map (UCM) notation can be used to map requirements into proper design concerns, usually known as responsibilities. In this paper, we introduce an approach for mining candidate architectural responsibilities and components from textual descriptions of requirements using natural language processing (NLP) techniques, in order to relieve software designers of this complex and time-consuming task. High accuracy and precision rates achieved by applying part-of-speech (POS) tagging with domain rules and semantic clustering to textual requirement documents, suggest a great potential for providing assistance to software designers during early stages of development.

Descargas

Publicado

2019-03-29

Cómo citar

Casamayor, A., Godoy, D., & Campo, M. (2019). Mining Architectural Responsibilities and Components from Textual Specifications Written in Natural Language. SADIO Electronic Journal of Informatics and Operations Research, 10, 4-19. https://revistas.unlp.edu.ar/ejs/article/view/17556