Source code is a 1-dimensional array. For 1-dimensional arrays WFC is just a Markov chain. 2 and higher dimensional arrays are much more interesting because they have cycles, and there is no canonical way to generalize Markov chains to higher dimensions.

This will be abstract, but you seem to know your abstract algebra -- is it possible to do this kind of thing with graphs? It should be, right? And we all know code can be constructed with graphs, so… voila, you can generate code, no?

What do you mean by "code can be constructed with graphs"?

I suppose the GP refers to compilers/interpreters parsing source code into abstract syntax trees (ASTs).

Or maybe to things like PureData, Unreal Engine blueprints, etc

Just to make sure I understand, if I were to use 1D WFC with 1xN tiles, would it be the same as an (N-1)th order Markov chain? Or would it be a 1st-order Markov chain with (N-1) simultaneous outputs?

If you use overlapping model (there are 2 models in the repo) with 1xN patterns, it would be a the same as (N-1)th order Markov chain.

Can you explain the difference between the overlapping and non-overlapping models?

In overlapping models we store probabilities for NxN blocks of colors/tiles. In non-overlapping models we store probabilities for individual colors/tiles.

What about code in a bitmap-based language like Piet?

https://en.wikipedia.org/wiki/Esoteric_programming_language#...

On that tangent, it could be useful for fuzzing inputs to image analysis algorithms.