Model based Incrementalization

Again similar to EMF, NMF provides elementary change notifications, offered through the industry standard interfaces INotifyPropertyChanged and INotify- CollectionChanged. These interfaces are required by many modern user interface libraries, hence the model representation code can directly be used for these techniques.

However, NMF is also able to combine these elementary change notifications to determine when the result of analyses based on a model has changed. Furthermore, an incremental algorithm is inferred to recalculate the analysis upon a model change more efficiently by the implicit introduction and management of buffers to save intermediate results. This incrementalization works online, i.e. the model needs to be kept in memory and changes must be made on the model elements in memory.

The incrementalization has a sound theoretical foundation based on category theory and is implemented in NMF Expressions. NMF Expressions operates on lambda expressions, supported by many .NET languages such as C# and VB.NET in their regular syntax. Lambda expressions are based on the Turingcomplete lambda-calculus. Thus, all model analyses can be specified in this format. To realize the incrementalization, the abstract syntax tree is converted into a dynamic dependency graph on a high abstraction level. Changes of the model under analysis are then propagated through the dependency graph, ultimately updating the analysis result.

The high abstraction level in the dynamic dependency graph is achieved by a manual incrementalization of analysis operators yielding valid results as a consequence of the underlying formalization as a categorial functor. NMF Expressions includes a library of such manually incrementalized operators, including most of the Standard Query Operators (SQO). As a consequence, developers can specify query analyses conveniently through the query syntax offered e.g. by C# and VB.NET, although also implementations for other forms of analysis exist such as for example connectivity analysis.