H. SteinlechnerG. HaaserS. Maierhofer ,  R. Tobler (2019)

Attribute Grammars for Incremental Scene Graph Rendering

communication medium

GRAPP 2019


Scene graphs, as found in many visualization systems are a well-established concept for modeling virtual scenes in computer graphics. State-of-the-art approaches typically issue appropriate draw commands while traversing the graph. Equipped with a functional programming mindset we take a different approach and utilize attribute grammars as a central concept for modeling the problem domain declaratively. Instead of issuing draw commands imperatively, we synthesize first class objects describing appropriate draw commands. In order to make this approach practical in the face of dynamic changes to the scene graph, we utilize incremental evaluation, and thereby avoid repeated evaluation of unchanged parts. Our application prototypically demonstrates how complex systems benefit from domain-specific languages, declarative problem solving and the implications thereof. Besides from being concise and expressive, our solution demonstrates a real-world use case of self-adjusting computation which elegantly extends scene graphs with well-defined reactive semantics and efficient, incremental execution.

research topic


Scenegraph, Attribute Grammar, Rendering Engine, Domain-Specific-Languages, Incremental Evaluation