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Object-oriented programming languages do not contain syntax or semantics to express associations directly. Therefore, UML associations have to be implemented by an adequate combination of classes, attributes and methods. This paper presents some principles for the implementation of UML binary associations in Java, paying special attention to multiplicity, navigability and visibility. Our analysis has encountered some paradoxes in the specification of visibility for bidirectional associations. These principles have been used to write a series of code patterns that we use in combination with a tool that generates code for associations, which are read from a model stored in XMI format.

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This paper describes the development of a decision support system (DSS) for prevention planning and emergency management of forest fire events that incorporates weather data management, a geographical data viewer, a priori danger forecasting and fire propagation modeling, automatic fire detection, and optimal resource dispatching. Collection, input, storage, management, and analysis of the information rely on advanced and automated methodologies using remote sensing, GPS, digital mapping, and geographic information systems. The results included short-term dynamic fire danger indices developed for improved and realistic prevention and pre-suppression planning. An automatic fire detection technology based on infrared video was developed and successfully tested on site. Several models for understanding fire propagation on forest fires have been proposed for practical application. Additionally, a DSS was developed with the innovation of covering wildland fire hazard management entirely, providing a complete coverage of technical and administrative activities that support decision makers in real time. The DSS was tested for high fire seasons in two different sites in South Europe.