## Wednesday, May 16

So... yesterday, I was dwelling in depth on types that "cannot be implemented".

Except, that's not a completely fair statement -- you can implement a finite part of an infinite type.  Some operations might fail, but maybe you do not need those operations.

There are several approaches here:

You can fall into an infinite loop when you encounter these situations.

You can introduce runtime checks -- runtime errors.  These are no more logically valid than an infinite loop, but have practical advantages.

You can limit yourself to a formally defined finite subset.  This can be satisfying, mathematically, but there will be operations which behave differently in this finite system than they would behave if they were members of the infinite system.

This all matters because traditionally numbers are infinite -- if I pick a number, you can add one to it.

So the above three approaches look like this:

1. Sometimes when you add two positive numbers, the system just hangs.

2. Sometimes when you add two positive numbers, you get some kind of error.

3. Sometimes when you add two positive numbers, the result is less than the peano sum of those two numbers.

Which of these is "best" can vary, depending on your own purpose and ideals -- on your own concept of "best".

* * * * *

Note also that the above options are valid in both "statically typed languages" and "dynamically typed languages".  So what is the difference between these two?

The distinction between these two kinds of languages has to do with how they treat syntax, and with how people think about problems.

The syntactic distinction is that statically typed languages place an emphasis on "user defined syntax" where when users define "types" (when they describe how they will represent data) , they are also introducing new syntax that is valid for dealing with that data.

In a dynamically typed language, the user defined syntax issue still exists in some vestigial form (undefined names might be syntactically invalid), but greater emphasis is placed on performing checks when the program runs.

Wait, what?

Let's try again... in a "statically typed language" we break up evaluation of a program into multiple stages.  The last stage is the familiar "run the program" stage.  An earlier stage is typically a "compilation" stage (or often a sequence of compilation stages).  Runtime errors in the earlier stages are the static type checks.

Nowadays, with relatively cheap computing, compared to the days when people came up with terms like "compiler", this can get blurry.  You can have multiple execution stages (compilation and running) happen nearly instantaneously.  You can have editing environments (emacs, and other IDEs) that perform some execution for you.

And, you can use a "proof assistant" in the early stages of execution.

And, do not get me wrong, proof assistant's can be fabulously helpful.

But they can never be a substitute for understanding what you are talking about.

* * * * *

So... let's consider one setting where people work on understanding what they are talking about: the classroom.

The classroom is not a perfect learning situation.  Just as it's easy to be glib in the context of computer programming, it's easy to be glib in the classroom.  And, the professor can be glib sometimes.  Hopefully not, but no one is perfect.

All professors are going to have limits on what they understand.  And, how they deal with that issue is a reflection on their quality as a professor.

One *good* practice on the part of a professor, is to refer the student to some appropriate resource when the student is venturing into territory where the professor is not prepared to present the information right then.  "You might want to read ____."

But this is a declaration, also, that the professor is not prepared to talk about that subject.  Maybe the issue is lack of time.  Maybe it's a lack of study.  Maybe the professor is rusty on the subject.

... anyways, referring someone to a book in place of explaining one's point does not mean that the referrer has an adequate understanding of the subject.

* * * *

(Adendum: too small for a new post, but added after the above text)

Anyways... in some ways the kind of concept I have been labeling as a "Glib Type" is related to an "Abstract Class".  The difference, though, is that implementations of an Abstract Class are full members of the abstract class.

With a glib type, you are going to have problem cases.  For the peano numbers, for example, there is going to be a number which does not have a successor.  (And, if you build out operations like addition, multiplication, and exponentiation, it's going to be easy to achieve problem cases, because those operations involve generating long sequences of successors.)

## Tuesday, May 15

### Glib Types

I am currently mildly upset because of how a task is being treated at rosettacode.org.

For people not familiar with the site, rosettacode was developed on the idea of "let's take a look at implementing the same task in various programming languages".  This has a necessary corollary, which was that the task is not allowed to forbid programming languages.

A recent task though, labeled "Proof" has gathered a collection of people that seem bound and determined to circumvent this concept.

The task starts out innocently enough -- it asks that a type be defined representing natural numbers, and that a derivative type be defined which represents the even subset of those natural numbers, and then that we prove that when we add two even numbers we get an even number.  Or its original form was something like that.  Since this is a fairly trivial problem, I submitted a fairly trivial proof which illustrated some of the same points which were illustrated by the other implementations.

And then, after a long time, someone objected to my proof.  And this resulted in a long discussion, where we danced around the real issues.  Eventually, the task was changed, explicitly requiring a type based on the peano axioms and asking that associativity be proved.

So here's a problem:  the peano axioms require an infinity of distinct values.  And, computers can only represent a finite number of distinct values.  And, they explicitly required that we implement this as a concrete type.  And, finiteness means that there will be some value which the computer can implement where the next larger value cannot be represented.

So I added to the task a statement that the existence of this limit was expected.

And my change was almost immediately reverted, without comment.

So I reverted that reversion and asked that the change be justified.

And it was reverted, again, without justification.  And, it's not like anyone feels that computers or computer implementations being finite is in any way controversial.

Instead, the person doing this seems to be confused about the distinction between "a symbol which represents infinity" and "a concrete type which must represent an infinite set of distinct values".  But that's just a guess, since the behavior was not justified.

So... I have decided that I am not going to deal with the site until this unjustified behavior ceases.

Still, it's an interesting problem.  So I am going to post my work here, where I do not have to worry about people reverting my changes.

I plan on doing this in a few stages:  First, a casual discussion of the peano axioms, and a proof about the associativity of addition where addition is built on these axioms.  Then I want to go back and think about re-implementing the proofs in an automated fashion, touching on some of the issues that this raises.

* * * * *

First, are the constraints which our peano axioms need to fit, for this task:

1. Define a countably infinite set of natural numbers {0, 1, 2, 3, ...}.
2. Define an addition on that numbers.
3. Define a countably infinite set of even natural numbers {0, 2, 4, 6, ...} within the previously defined set of natural numbers.
4. Prove that the addition of any two even numbers is even.
5. Prove that the addition is always associative.

(The peano axioms could also be built starting from the number 1 -- this changes some details in the proofs.)

So here's a set of peano axioms that would work here, borrowed from the current instance at the math wiki:

1. There exists a number zero (0).
2. For each $n \in \mathbb{N}$, there exists a natural number that is the successor of n, denoted by n'.
3. Zero is not the successor of any natural number. (For each $n \in \mathbb{N}$$n' \ne 0$)
4. For all natural numbers $n,m \in \mathbb{N}$if n' = m', then n = m.
5. Given any predicate P on the natural numbers, if P(0) is true and P(k) implies P(k') for any $k \in \mathbb{N}$, then P(n)is true for all $n \in \mathbb{N}$. (This is also known as the principle of mathematical induction.)

Note that there's a slight difference here -- the math wiki defines natural numbers as not including 0 where the rosettacode task defines natural numbers as including 0.  So, for the purpose of the rosettacode task we define natural numbers as the set which includes the math wiki natural numbers and 0.

So... proof.

First off, this set of axioms is a classic mathematical problem.  I think most mathematicians get exposed to it sooner or later.  So showing that a system is equivalent to the peano axioms is enough to show that there is an operation like addition which is associative.  And, multiplication is associative.  And... mathematics is generally built on a concept rather like puns, where a set of principles developed for one line of thought can be applied to another line of thought if the underlying axioms can be shown to apply.

But there are limits to mathematical puns.  For example, octonions contain the set of natural numbers but in the general case multiplication of octonions is not associative.  Multiplication involving only octonions which are natural numbers is still associative, but this kind of issue means we need to proceed with caution.

So, back to the peano axioms -- how can we prove that addition is associative if all we have is the peano axioms?

First, we are going to have to define addition.  Here's one implementation, using J (and originally I had used the name 'successor' where I am using the name 'next' but that resulted in some "line too long" problems, so I changed it):

zero=: 0

next=:3 :0
1 + y
)

equal=: -:

predecessor=:3 :0
zero predecessor y
:
if. y equal  next x do.
x
else.
(next x) predecessor y
end.
)

:
if. zero equal x do.
y
else.
end.
)

Example use:

predecessor   next  next  next zero
2
(next  next  next zero) addition (next  next  next   next  zero)
7

This is a rather tedious approach -- this implementation of addition is going to be extremely slow -- but note also that we can replace the initial three definitions with something entirely different and addition will still work.

For example:

zero=: ''

next=: , ? bind 9

equal=: 1:@,. :: 0:

predecessor   next  next  next zero
2 1
(next  next  next zero) addition (next  next  next  next  zero)
2 4 3 2 7 3 3

Here, we are constructing sequences of arbitrary digits and our "peano numbers" are the lengths of these sequences.  Equality is thus an equality of length rather than a literal equality.  (This is generally the case with numbers and equality -- if we are counting sheep we do not mean that the sheep are identical, instead we mean that we do not care about the differences between the things we are counting, except that they somehow represent distinct individuals.)

So... proof... how do we prove that addition is associative?  In other words, if A, B and C are valid peano numbers, how do we prove that these two sentences are peano equal?

First, we can consider the case where A is zero.  If A is zero, then these are equal:

B addition C                           NB. definition of parenthesis

Similarly, if A is zero, then these are equal:

B addition C                            NB. definition of parenthesis

For our next step, we rely on the last clause of the peano axioms.  We start by saying that A is a value where our two sentences are equal (A addition (B addition C) and (A addition B) addition C).  If this allows us to prove that they are also equal when we replace A by  next A then our proof is complete.

So we start this stage with they hypothesis that these are equal:

So:

These are all equal so the first statement in this chain must be equal to the last statement in this chain.

The transition between these two steps needs induction:

Here's a quick exposition of that induction:

If (A addition B) is zero then it breaks down like this:

0 addition (next  C)  NB. by definition
(next C)  NB. if part of addition

And, because (A addition B) is zero, we can replace C by (A addition B) addition C and it means the same thing, which leaves us with:

If we then assume that we have a case where (A addition B) addition (next C) equals (next ((A addition B)  addition C)) we just need to show that it also holds for the  next of (A addition B):

by our induction, we get:

Easy, right?

Though some people might prefer I deal with the parenthesis differently, or that I replace phrases with named values.  That's a quibble, though, and you can do that kind of manipulation for yourself if you are interested in it.

One note here is that this is a rather tedious sequence of manipulations.  But that's not the most important point.

I think the most important point here is the rule of induction.  When we can find a case which is equivalent to the inductive rule in the peano axioms, we have found a case which we can characterize by counting.  In other words: we can manipulate numbers to deal with those kinds of problems.

Many people I think take the wrong lesson here -- instead of seeing how useful numbers can be, they instead focus on the concept of recursion.  But in most practical cases, numbers are good enough.  So why make life complicated and tedious?  (There are cases -- like ackerman's function -- where you need something more, but I do not think anyone has ever found a practical use for ackerman's function.)

Anyways, from a practical programmer's point of view: numbers are handy things.  (And sequences of numbers are handy things -- but that's getting too far afield for this discussion.)

So... how do we convert this proof to a mechanical proof about types?

First, we need a definition for "type" in J.  A type is the set of results which can be yielded by a parenthesized J expression.

We also need a way of expressing the above definitions (especially the definition of addition) in a fashion that lets us distinguish the if part and the else part in a mechanical fashion.  It may also be convenient to represent a part of an addition.  In other words, instead of 1 + 2, we might want to express this in parts like (1 + ]) 2

And, we need a way of tying these things together.

So... back to J... here's some thoughts on how I might construct a type checked program in J:

First, typing itself:  If I can make the complete type declaration a part of the name of the implementation of a routine then I can limit access to the routine by type in the same way that I limit access by name.

We also need a mechanical way of expressing things like (A (equal (predecessor (next A)))).  I do not need a fully general implementation of these kinds of mechanisms -- I only need enough for this task.  (Or, I would not if people would stop changing the task.)

Also, how do we distinguish between different peano systems?

One issue, here, is that for us to be satisfied by a proof, we need to understand it.  That's pretty much the point of a proof -- that we are comfortable with our understanding at each step of the way.

And a related issue is that the theories which we can derive from a set of axioms are always going to be restatements of those axioms.  If there's something new being introduced, it's going to be a new axiom.  An axiom is something that we assume to be true, and the point of all this theory and proof stuff is to minimize our set of axioms -- of assumptions.

And, the way proofs work is: we are introducing a new sequence of things which we might treat as axioms -- constructive statements -- but but which we can later ignore.  We see that they are equal to axioms we already have accepted as true.

But that's not really a good description for how computer programs run.  Computer programs are a mechanical set of logical processes -- very like a proof -- but instead of understanding their steps, the execution of a program happens outside of our minds.   Thus, programs which deal with proofs are typically called "proof assistants".   They can perform proof-like steps but it's still up to us to determine the relevance of these steps.

So... we can express the peano proof in a mechanical fashion.  But whether that is convincing to the reader is going to depend on the reader and in their understanding of the underlying system.

A related issue is that we can trust the system "too much".  The issue I began with here -- the issue having to do with treatment of infinity -- I think illustrates that hazard rather nicely.

But back to representing this problem in J...

Personally, I do not find mechanical manipulations to be a very adequate proof.  So I would not be writing an implementation that satisfies myself.  Instead, I suppose I would start by emulating an implementation in some other language.  Let's take the Agda implementation, for example:

module Arith where

-- 1. Natural numbers.
--
--   ℕ-formation:     ℕ is set.
--
--   ℕ-introduction:  o ∈ ℕ,
--                    a ∈ ℕ | (1 + a) ∈ ℕ.
--
data ℕ : Set where
o : ℕ
1+ : ℕ → ℕ

--
--   via ℕ-elimination.
--
infixl 6 _+_
_+_ : ℕ → ℕ → ℕ
o + n = n
1+ m + n = 1+ (m + n)

-- 3. Even natural numbers.
--
data 2×ℕ : ℕ → Set where
o : 2×ℕ o
2+ : {n : ℕ} → 2×ℕ n → 2×ℕ (1+ (1+ n))

-- 4. Sum of any two even numbers is even.
--
--   This function takes any two even numbers and returns their sum as an even number,
--   this is a type, i.e. logical proposition, algorithm itself is a proof by unification
--   which builds a required term of a given (inhabited) type, and the typechecker
--   performs that proof (so that this is compile-time verification).
--
even+even≡even : {m n : ℕ} → 2×ℕ m → 2×ℕ n → 2×ℕ (m + n)
even+even≡even o n = n
even+even≡even (2+ m) n = 2+ (even+even≡even m n)

-- The identity type for natural numbers.
--
infix 4 _≡_
data _≡_ (n : ℕ) : ℕ → Set where
refl : n ≡ n

cong : {m n : ℕ} → m ≡ n → 1+ m ≡ 1+ n
cong refl = refl

-- 5.1. Direct proof of the associativity of addition.
--
+-associative : (m n p : ℕ) → (m + n) + p ≡ m + (n + p)
+-associative o _ _ = refl
+-associative (1+ m) n p = cong (+-associative m n p)

-- Proof _of_ mathematical induction on the natural numbers.
--
--   P 0, ∀ x. P x → P (1 + x) | ∀ x. P x.
--
ind : (P : ℕ → Set) → P o → (∀ n → P n → P (1+ n)) → ∀ n → P n
ind _ P₀ _ o = P₀
ind P P₀ next (1+ n) = next n (ind P P₀ next n)

-- 5.2. Associativity of addition by induction.
--
+-associative′ : (m n p : ℕ) → (m + n) + p ≡ m + (n + p)
+-associative′ m n p = ind P P₀ is m
where
P : ℕ → Set
P i = i + n + p ≡ i + (n + p)
P₀ : P o
P₀ = refl
is : ∀ i → P i → P (1+ i)
is i Pi = cong Pi


Here's the web site for Agda: http://wiki.portal.chalmers.se/agda/pmwiki.php

So... reading through this... o is similar to my zero and 1+ is similar to my  next .  Except

1.   Agda begins by declaring their "type".
2.   It's not clear to me if this Agda code has any concrete implementation for the type, nor whether it's intended to be able to have any concrete implementation.   We can have different sets which are isomorphic to the natural numbers...

Also, this comment bothers me:

"Proof _of_ mathematical induction on the natural numbers"

This was originally an axiom -- something that we take as a given, not something that we should be proving.  So either that comment is wrong or the code is doing something different from what I think that I would want to do.

Also... if I understand how Agda works (and I might not), it looks to me as if the treatment of associativity is implemented as a constraint on the original definition.  In other words, it looks to me as if it's saying that the earlier definition contains an associative subset, which is something slightly different from saying that the peano axioms guarantee associativity.

But, wait, what about the mathematical "for all" statements in that induction section?  Don't those show that the guarantees in part 5 must be valid for all natural numbers?  ..... unfortunately, that is the problem.  By asserting validity for an infinite series, we are asserting that a finite implementation will eventually fail.

Anyways, it *should* be possible to discuss these kinds of issues rationally, using the english language.  And I am upset that I cannot achieve any basic discussion on the subject of "what does it mean to implement a type in a computer program"?

My sense is that there are multiple concepts of type here -- that an Agda type is not anything like a J type.  (A J type being the set of values which can result from an expression, an Agda type may never correspond to any results?)  If so, this kind of description should be a crucial part of the Rosetta code task.

If it's really the case that the finite character of computer systems has no relevance to the definition of type being used here, this means that the type is not limited to the things which can result from the computer program.  Instead, it's a purely symbolic thing -- a glib type -- a type which does not have examples, which cannot be implemented.

That's... disappointing.