Want to clarify a bit, though, as I didn't say that principal components analysis was a good analogy. I rather said coding should accomplish the opposite, that is spreading to information into the functions, dividing it equally among them.
However stated, the analogy goes wrong because with principal components we talk about orthogonal vectors in space, while with programming we have hierarchial functions. These create a subspace of each own, and you just can not do a PCA on different subspaces. Is that what you more or less ment, tilly?
/me notes with a smile in his face how everyone approaches PCA from its own angle...., Masem from the chemical spectra point of view, tilly from a encoding point of view while I think more in pattern deviation scemes.