A user profiling approach to optomize the production of architectural documentation

The Software Architecture Document (SAD) is a key artifact in the early stages of software development, as it serves to share the architectural knowledge among the key project stakeholders and to keep record of the main design decisions for satisfying the stakeholders’ concerns. Even the best architectural solution could fail its purpose if it is not properly documented, distributed and understood by the stakeholders. However, documenting an architecture is a non-trivial and time-consuming activity, usually performed with limited resources. Thus, documenting a SAD should be planned to ensure that the invested efforts are worth the cost in terms of SAD quality. (Párrafo extraído del texto a modo de resumen)Sociedad Argentina de Informática e Investigación Operativa (SADIO

A user profiling approach to optomize the production of architectural documentation

The Software Architecture Document (SAD) is a key artifact in the early stages of software development, as it serves to share the architectural knowledge among the key project stakeholders and to keep record of the main design decisions for satisfying the stakeholders’ concerns. Even the best architectural solution could fail its purpose if it is not properly documented, distributed and understood by the stakeholders. However, documenting an architecture is a non-trivial and time-consuming activity, usually performed with limited resources. Thus, documenting a SAD should be planned to ensure that the invested efforts are worth the cost in terms of SAD quality. (Párrafo extraído del texto a modo de resumen)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.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

How organisation of architecture documentation affects architectural knowledge retrieval

A common approach to software architecture documentation in industry projects is the use of file-based documents. This approach offers a single-dimensional arrangement of the architectural knowledge. Knowledge retrieval from file-based architecture documentation is efficient if the organisation of knowledge supports the needs of the readers; otherwise it can be difficult. In this paper, we compare the organisation and retrieval of architectural knowledge in a file-based documentation approach and an ontology-based documentation approach. The ontology-based approach offers a multi-dimensional organisation of architectural knowledge by means of a software ontology and semantic wiki, whereas file-based documentation typically uses hierarchical organisation by directory structure and table of content. We conducted case studies in two companies to study the efficiency and effectiveness of retrieving architectural knowledge from the different organisations of knowledge. We found that the use of better knowledge organisation correlates with the efficiency and effectiveness of AK retrieval. Professionals who used the knowledge organisation found this beneficial