If executed well, Delaunay-based tetrahedral dithering can outperform the N-convex method and produce results that rival Knoll’s algorithm. The devil is in the detail however, as actually implementing a robust Delaunay triangulator is a non-trivial task, especially where numerical stability is concerned. The additional memory overhead required by the triangulation structure may also be a concern.
Say you want to upgrade your ORM dependency. You start doing so, but you quickly realize that there are some breaking changes. So you need to change some function calls across the codebase. To make it easier, you decide to refactor and extract them somewhere, so you only have one place to change. But to do so, you need to adapt each call first…
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