I suspect that we could bring this measure into the modern world with a little help from either DFS or ai.
Something like abstractions traversed during interpretation, lines of abstraction v.s. functional implementation, or logic statement dispersion.
It was hard to pin down what was abstraction vs. implementation, but it's much easier now.
The thing is, AI has no idea when an abstraction is good or not.
The reductio ad absurdum here is that, if abstraction can just be assumed to be bad for quality and maintainability, then perhaps we should go back to hand writing machine code for non-microcoded sequential execution CPU architectures. Conversely, if that idea sounds as preposterous to you as it does to me, then you’re stuck conceding that at least some abstractions are mostly good. So then, before you can automate deciding which ones should and should not count against a code quality metric that’s computed automatically, you need to find an operational definition that can be applied deterministically.