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Teaching modeling in computer science is complicated. Many factors contribute, and are related in diverse ways. We regard some combinations as more successful than others, but we also value diversity, and we struggle to elucidate the relationships and our value structure. Similar remarks apply to the study of biological ecosystems. This contribution views teaching modeling as an ecosystem: we push the analogy as far as we can, with the intention of provoking readers' thought in unaccustomed directions, which may perhaps lead to interesting advances. We identify the factors that contribute to the ecosystem and establish some relationships between the constituent factors. We discuss some of the factors that need further work and improvement. Finally, we discuss what it should mean for the ecosystem of the teaching of modeling to be healthy.

Software build systems tackle the problem of building software from sources in a way which is sound (when a build completes successfully, the relations between the generated and source files are as specified) and optimal (only genuinely required rebuilding steps are done). In this paper, we explain and exploit the connection between software build and the megamodel consistency problem. The model-driven development of systems involves multiple models, metamodels and transformations. Transformations—which may be bidirectional—specify, and provide means to enforce, desired "consistency" relationships between models. We can describe the whole configuration using a megamodel. As development proceeds, and various models are modified, we need to be able to restore consistency in the megamodel, so that the consequences of decisions first recorded in one model are appropriately reflected in the others. At the same time, we need to minimise the amount of recomputation needed; in particular, we would like to avoid reapplying a transformation when no relevant changes have occurred in the models it relates. The megamodel consistency problem requires flexibility beyond what is found in conventional software build, because different results are obtained depending on which models are allowed to be modified and on the order and direction of transformation application. In this paper, we propose using an orientation model to make important choices explicit. We show how to extend the formalised build system pluto to provide a means of restoring consistency in a megamodel, that is, in appropriate senses, flexible, sound and optimal. [ABSTRACT FROM AUTHOR]

Binary associations between classifiers are among the most fundamental of UML concepts. However, there is considerable room for disagreement concerning what an association is, semantically; it turns out that at least two different notions are called Associations. This confusion of concepts gives rise to unnecessary complication and ambiguity in the language, which have implications for the modeller because they can result in serious misunderstandings of static structure diagrams; similarly, they have implications for tool developers. In this paper we explore these issues, suggest improvements and clarifications, and demonstrate side-benefits that would accrue. [ABSTRACT FROM AUTHOR]