Activity modeling in practice: a case-based guide to human-centered software engineering

The purpose of this study was to identify whether activity modeling framework supports problem analysis and provides a traceable and tangible connection from the problem identification up to solution modeling. Methodology validation relied on a real problem from a Portuguese teaching syndicate (ASPE), regarding courses development and management. The study was carried out with a perspective to elaborate a complete tutorial of how to apply activity modeling framework to a real world problem. Within each step of activity modeling, we provided a summary elucidation of the relevant elements required to perform it, pointed out some improvements and applied it to ASPE’s real problem. It was found that activity modeling potentiates well structured problem analysis as well as provides a guiding thread between problem and solution modeling. It was concluded that activity-based task modeling is key to shorten the gap between problem and solution. The results revealed that the solution obtained using activity modeling framework solved the core concerns of our customer and allowed them to enhance the quality of their courses development and management. The principal conclusion was that activity modeling is a properly defined methodology that supports software engineers in problem analysis, keeping a traceable guide among problem and solution.

Using Neo4J geospatial data storage and integration

Online geographic-databases have been growing increasingly as they have become a crucial source of information for both social networks and safety-critical systems. Since the quality of such applications is largely related to the richness and completeness of their data, it becomes imperative to develop adaptable and persistent storage systems, able to make use of several sources of information as well as enabling the fastest possible response from them. This work will create a shared and extensible geographic model, able to retrieve and store information from the major spatial sources available. A geographic-based system also has very high requirements in terms of scalability, computational power and domain complexity, causing several difficulties for a traditional relational database as the number of results increases. NoSQL systems provide valuable advantages for this scenario, in particular graph databases which are capable of modeling vast amounts of inter-connected data while providing a very substantial increase of performance for several spatial requests, such as finding shortestpath routes and performing relationship lookups with high concurrency. In this work, we will analyze the current state of geographic information systems and develop a unified geographic model, named GeoPlace Explorer (GE). GE is able to import and store spatial data from several online sources at a symbolic level in both a relational and a graph databases, where several stress tests were performed in order to find the advantages and disadvantages of each database paradigm.