Is it impossible to know if two functions are equivalent? For example, a compiler writer wants to determine if two functions that the developer has written perform the same operation, what methods can he use to figure that one out? Or can what can we do to find out that two TMs are identical? Is there a way to normalize the machines?
Edit: If the general case is undecidable, how much information do you need to have before you can correctly say that two functions are equivalent?
Therefore, the equivalence problem is undecidable. Note that this means that in general, you can't tell whether an original program P and an optimized version P' produced by an optimizing compiler compute the same thing.
For a correct proof, need a convincing argument that the TM always eventually accepts or rejects any input. How can you prove a language is undecidable? To prove a language is undecidable, need to show there is no Turing Machine that can decide the language. This is hard: requires reasoning about all possible TMs.
An undecidable problem is one that should give a "yes" or "no" answer, but yet no algorithm exists that can answer correctly on all inputs.
This is an undecidable problem because we cannot have an algorithm which will tell us whether a given program will halt or not in a generalized way i.e by having specific program/algorithm.In general we can't always know that's why we can't have a general algorithm.
Given an arbitrary function, f, we define a function f' which returns 1 on input n if f halts on input n. Now, for some number x we define a function g which, on input n, returns 1 if n = x, and otherwise calls f'(n).
If functional equivalence were decidable, then deciding whether g is identical to f' decides whether f halts on input x. That would solve the Halting problem. Related to this discussion is Rice's theorem.
Conclusion: functional equivalence is undecidable.
There is some discussion going on below about the validity of this proof. So let me elaborate on what the proof does, and give some example code in Python.
The proof creates a function f' which on input n starts to compute f(n). When this computation finishes, f' returns 1. Thus, f'(n) = 1 iff f halts on input n, and f' doesn't halt on n iff f doesn't. Python:
def create_f_prime(f): def f_prime(n): f(n) return 1 return f_prime
Then we create a function g which takes n as input, and compares it to some value x. If n = x, then g(n) = g(x) = 1, else g(n) = f'(n). Python:
def create_g(f_prime, x): def g(n): return 1 if n == x else f_prime(n) return g
Now the trick is, that for all n != x we have that g(n) = f'(n). Furthermore, we know that g(x) = 1. So, if g = f', then f'(x) = 1 and hence f(x) halts. Likewise, if g != f' then necessarily f'(x) != 1, which means that f(x) does not halt. So, deciding whether g = f' is equivalent to deciding whether f halts on input x. Using a slightly different notation for the above two functions, we can summarise all this as follows:
def halts(f, x): def f_prime(n): f(n); return 1 def g(n): return 1 if n == x else f_prime(n) return equiv(f_prime, g) # If only equiv would actually exist...
I'll also toss in an illustration of the proof in Haskell (GHC performs some loop detection, and I'm not really sure whether the use of seq
is fool proof in this case, but anyway):
-- Tells whether two functions f and g are equivalent. equiv :: (Integer -> Integer) -> (Integer -> Integer) -> Bool equiv f g = undefined -- If only this could be implemented :) -- Tells whether f halts on input x halts :: (Integer -> Integer) -> Integer -> Bool halts f x = equiv f' g where f' n = f n `seq` 1 g n = if n == x then 1 else f' n
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