Towards recovering architectural information from images of architectural diagrams

The architecture of a software system is often described with diagrams embedded in the documentation. However, these diagrams are normally stored and shared as images, losing track of model-level architectural information and refraining software engineers from working on the architectural model later on. In this context, tools able to extract architectural information from images can be of great help. In this article, we present a framework called IMEAV for processing architectural diagrams (based on speci c viewtypes) and recovering information from them. We have instantiated our framework to analyze \\module views and evaluated this prototype with an image dataset. Results have been encouraging, showing a good accuracy for recognizing modules, relations and textual features.XV Simposio Argentino de Ingeniería de Softwar

Towards recovering architectural information from images of architectural diagrams

The architecture of a software system is often described with diagrams embedded in the documentation. However, these diagrams are normally stored and shared as images, losing track of model-level architectural information and refraining software engineers from working on the architectural model later on. In this context, tools able to extract architectural information from images can be of great help. In this article, we present a framework called IMEAV for processing architectural diagrams (based on speci c viewtypes) and recovering information from them. We have instantiated our framework to analyze \module views" and evaluated this prototype with an image dataset. Results have been encouraging, showing a good accuracy for recognizing modules, relations and textual features.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Towards recovering architectural information from images of architectural diagrams

The architecture of a software system is often described with diagrams embedded in the documentation. However, these diagrams are normally stored and shared as images, losing track of model-level architectural information and refraining software engineers from working on the architectural model later on. In this context, tools able to extract architectural information from images can be of great help. In this article, we present a framework called IMEAV for processing architectural diagrams (based on speci c viewtypes) and recovering information from them. We have instantiated our framework to analyze \module views" and evaluated this prototype with an image dataset. Results have been encouraging, showing a good accuracy for recognizing modules, relations and textual features.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Towards recovering architectural information from images of architectural diagrams

The architecture of a software system is often described with diagrams embedded in the documentation. However, these diagrams are normally stored and shared as images, losing track of model-level architectural information and refraining software engineers from working on the architectural model later on. In this context, tools able to extract architectural information from images can be of great help. In this article, we present a framework called IMEAV for processing architectural diagrams (based on speci c viewtypes) and recovering information from them. We have instantiated our framework to analyze \module views" and evaluated this prototype with an image dataset. Results have been encouraging, showing a good accuracy for recognizing modules, relations and textual features.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Análisis de secuencias discretas para la detección de patrones de diseño de software

Los patrones de diseño de software son una herramienta que permite re utilizar las experiencias previas en el diseño actual. Los diseñadores inexpertos en dicha área se ven obligados a leer catálogos de patrones a fin de nutrirse de este conocimiento, perdiendo el aprendizaje que da la práctica. Partiendo de este problema, en el presente artículo se propone la utilización de Modelos de Markov de Orden Variable para brindar, a partir de un conjunto acotado de actividades desarrolladas por un diseñador y una base de conocimiento preestablecida (plan corpus), toda aquella información necesaria para que un agente de Interfaz pueda aconsejar a un usuario durante el proceso de diseño de software.Sociedad Argentina de Informática e Investigación Operativ