I think the reverse direction is more important: taking a massive complex problem/codebase and decomposing it to short pseudocode. Then you could edit the pseudocode and compile it back into the system.
That's the way software engineers working on large projects work anyway: you first gather context on the state of the system and read it at a level you can understand. Then you propose a change on the simplified representation, and then holistically update the machine-runnable format ("implementation").
I'd be interested in tools that formalize/automate this process more.
I'm working on a bidirectional version of this! The big challenge is keeping the various versions of the thing in sync through edits.
Clever! :)
Difficult! :(
I don't think it's particularly difficult, or clever. You can prompt your way into this with frontier models, especially if your codebase is designed for it from the ground up (architecture well factored, documented, tested, harnessable, so that it even has a pseudocode representation in the first place).
The biggest issue is you end up leaning heavily on the quality of the model. Lower fidelity models tend to make a mess and add tech debt that you must frequently repay with intentional cleanup passes from a higher quality model, or else the rate of useful progress will fall off a cliff. At least that's my experience.