Somewhat related to the electrical circuits example, there might be something similar in software engineering, with levels being something like (depending on the programming paradigm):
Yes definitely. I’ve omitted examples from software and math because there’s no “fuzziness” to it; that kind of abstraction is already better-understood than the more probabilistically-flavored use-cases I’m aiming for. But the theory should still apply to those cases, as the limiting case where probabilities are 0 or 1, so they’re useful as a sanity check.
I do want to note that probabilities 0 and 1 only correspond to no fuzziness if we assume a finite set. If we don’t assume a finite set, then it’s easy to cook up examples where probabilities are 0 or 1, but they aren’t equivalent to either nothing or everything, and thus probabilities 0 or 1 can still introduce fuzziness.
Somewhat related to the electrical circuits example, there might be something similar in software engineering, with levels being something like (depending on the programming paradigm):
CPU instructions
byte code or op code or assembly
AST
programming language instructions
statements
functions
modules and classes
patterns and DSLs
processes
applications/products
Yes definitely. I’ve omitted examples from software and math because there’s no “fuzziness” to it; that kind of abstraction is already better-understood than the more probabilistically-flavored use-cases I’m aiming for. But the theory should still apply to those cases, as the limiting case where probabilities are 0 or 1, so they’re useful as a sanity check.
I do want to note that probabilities 0 and 1 only correspond to no fuzziness if we assume a finite set. If we don’t assume a finite set, then it’s easy to cook up examples where probabilities are 0 or 1, but they aren’t equivalent to either nothing or everything, and thus probabilities 0 or 1 can still introduce fuzziness.