Details zur Publikation
|DOI / URL||Link|
|Titel (primär)||Visual debugging: a way of analyzing, understanding, and communicating bottom-up simulation models in ecology|
|Journal / Serie||Natural Resource Modeling|
Bottom-up simulation models, i.e.individual- based and spatially explicit models, are powerful new tools in ecology and natural resource management. However, they have to be implemented as more or less complex software and are therefore harder to analyze, understand, and communicate than mathematical models. Particularly critical is the problem of communication, which must be solved if bottom-up models are to be scientifically credible. As a pragmatic solution to this problem, "visual debugging" is proposed, which means equipping simulation programs with a graphical user interface that integrates elements of conventional debugging and graphical representations of the model 's state variables. The direct benefit of visual debugging is that the attitude of debugging, i.e.performing controlled experiments, is transferred to the overall development and analysis of the model. This facilitates acknowledging the hierarchical organization of ecological systems and using patterns observed in real systems for developing and validating the models. The benefit for communicating bottom-up models is that peers can download the executable program from the internet and test and analyze the model on their own. Visual debugging is not meant as an exclusive alternative to other approaches of communicating bottom-up simulation models, i.e.software libraries or general protocols of model description, but should be combined with these approaches. Overall, visual debugging integrates general principles of software engineering and specific requirements for modeling ecological systems and would therefore contribute to establishing an improved culture of analyzing, understanding, and communicating bottom-up simulation models.
|Grimm, V. (2002):
Visual debugging: a way of analyzing, understanding, and communicating bottom-up simulation models in ecology
Nat. Resour. Model. 15 (1), 23 - 38