C. Alexander in _Notes on the Synthesis of Form_, rather explicitly puts forth the essential architectural problem in a semiformal form - a constraint satisfact

C. Alexander in _Notes on the Synthesis of Form_, rather explicitly puts forth the essential architectural problem in a semiformal form - a constraint satisfaction problem. The closest application of CSP-like problems in places close to statistics-land is in neural networks, where Rumelhart published in multiple places that the objective of neural networks, including the backprop net that he reinvented, was soft CSP. So actually, there is probably a path towards formal equivalence. Of course, there's a disgustingly large amount of work done on the analogies between CSP and Ising model at criticality, because you only need to look at the damned things (compare to Hopfield model). The other path is to look at R. Sole's work on munging for power law-ish things in software. So physical methods for software are actually quite old hat (from the 90's). It's just that it's all really fucking hard condensed matter stuff. This is quite close to Huberman's work at PARC about networks and stuff, which led to the different Adamic and Huberman munging for power laws in networks and Internet things.