#Turing’s halting problem – as a poem

In 1936 Alan Turing proved that the halting problem is undecidable over Turing Machines. What does this mean to you? Basically it’s not possible to determine in advance if any computer program will actually stop and not run for ever. Now I’ve not express that very eloquently, so I’ll hand over to Professor Geoffrey Pullum who’s written a rather elegant poem about the halting problem.


SCOOPING THE LOOP SNOOPER


by Geoffrey K Pullum


A proof that the Halting Problem is undecidable

No general procedure for bug checks succeeds.
Now, I won’t just assert that, I’ll show where it leads: 
I will prove that although you might work till you drop, 
you cannot tell if computation will stop.

For imagine we have a procedure called P 
that for specified input permits you to see
whether specified source code, with all of its faults,
defines a routine that eventually halts.

You feed in your program, with suitable data, 
and P gets to work, and a little while later 
(in finite compute time) correctly infers
whether infinite looping behavior occurs.

If there will be no looping, then P prints out ‘Good.’
That means work on this input will halt, as it should.
But if it detects an unstoppable loop,
then P reports ‘Bad!’ — which means you’re in the soup.

Well, the truth is that P cannot possibly be, 
because if you wrote it and gave it to me, 
I could use it to set up a logical bind 
that would shatter your reason and scramble your mind.

Here’s the trick that I’ll use — and it’s simple to do. 
I’ll define a procedure, which I will call Q,
that will use P’s predictions of halting success 
to stir up a terrible logical mess.

For a specified program, say A, one supplies,
the first step of this program called Q I devise
is to find out from P what’s the right thing to say
of the looping behavior of A run on A.

If P’s answer is ‘Bad!’, Q will suddenly stop. 
But otherwise, Q will go back to the top, 
and start off again, looping endlessly back, 
till the universe dies and turns frozen and black.

And this program called Q wouldn’t stay on the shelf; 
I would ask it to forecast its run on itself.
When it reads its own source code, just what will it do? 
What’s the looping behavior of Q run on Q?

If P warns of infinite loops, Q will quit; 
yet P is supposed to speak truly of it! 
And if Q’s going to quit, then P should say ‘Good.’
Which makes Q start to loop! (P denied that it would.)

No matter how P might perform, Q will scoop it: 
Q uses P’s output to make P look stupid.
Whatever P says, it cannot predict Q: 
P is right when it’s wrong, and is false when it’s true!

I’ve created a paradox, neat as can be —
and simply by using your putative P. 
When you posited P you stepped into a snare; 
Your assumption has led you right into my lair.

So where can this argument possibly go? 
I don’t have to tell you; I’m sure you must know. 
A reductio: There cannot possibly be 
a procedure that acts like the mythical P.

You can never find general mechanical means
for predicting the acts of computing machines; 
it’s something that cannot be done. So we users 
must find our own bugs. Our computers are losers!




from The Universal Machine http://universal-machine.blogspot.com/2012/03/turings-halting-problem-as-poem.html

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About driwatson
I'm a New Zealand author, computer scientist and blogger specialising in Artificial Intelligence. I also have an interest in the history of computing and have just written a popular science book called "The Universal Machine - from the dawn of computing to digital consciousness."

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