DataMock: An Agile Approach for Building Data Models from User Interface Mockups

• Autores: Rivero, José Matías; Grigera, Julián; Distante, Damiano; Montero, Francisco; Rossi, Gustavo Héctor
• Año de publicación: 2019
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Ciencias de la Computación e Información; Data modeling; Agile methods; Mockups; Annotations; Requirements engineering; Requirements traceability; Model-driven development
• Institución: Comisión de Investigaciones Científicas de la Provincia de Buenos Aires

In modern software development, much time is devoted and much attention is paid to the activity of data modeling and the translation of data models into databases. This has motivated the proposal of different approaches and tools to support this activity, such as semiautomatic approaches that generate data models from requirements artifacts using text analysis and sets of heuristics, among other techniques. However, these approaches still suffer from important limitations, including the lack of support for requirements traceability, the poor support for detecting and solving conflicts in domain-specific requirements, and the considerable effort required for manually checking the generated models. This paper introduces DataMock, an Agile approach that enables the iterative building of data models from requirements specifications, while supporting traceability and allowing inconsistencies detection in data requirements and specifications. The paper also describes how the approach effectively allows improving traceability and reducing errors and effort to build data models in comparison with traditional, state-of-the-art, data modeling approaches.