I had the idea for this language after reading into some of the offerings currently available in the world of Formal Methods: things like Z, TLA+, and somewhat more obscurely, the language developed in A Practical Theory of Programming. I had and have an interest in formal methods though my interest, like that of many, is unconsummated, as I haven’t become anything close to expert in any of them and haven’t had the opportunity to use them in a professional setting.

The desire to put together something of my own came after reading
*aPToP*. Hehner’s rationale for formal methods is, paraphrased, is:
programming would be better if program specifications had two closely
related qualities that they currently lack:

- Unambiguous in meaning
- Provably correct

To that end he puts together a language of program behavior which is as unambiguous in its meaning as mathematics with a set of axiomatic equalities that allow the programmer to express a precise and complete specification of behavior and then refine it, axiomatically, to arrive at a provably correct implementation.

I’ll leave the reader to decide for themselves whether Hehner’s offering
is practicable, but I found myself inspired. I lack the brainpower to
write a formal method that, along the lines of Z and TLA+, allows us
to express program behavior according to some axiomatic theory. So this
is not an attempt to replace or even mimic those systems. However, the
notion of a more mathematical and therefore *less ambiguous* notation
for program behavior is appealing. The observation that English words
like *should*, *all*, *none of* and so forth can contain a multiplicity
of overlapping meanings is well-taken.

What would be especially nice is if we had a notation that was more
mathematical but also easily written by hand, and intuitive to the
programmer, so we could use it as a lingua franca for whiteboarding,
ideation in notebooks, and the like. There’s a possibility for something
with a much lower barrier to entry (for this admittedly more modest goal)
than something like Z. Part of what makes this possible is that we can
jettison a formal *semantics* entirely. Because this is a specification
language, and because it is not going to result in a provably correct
program, it doesn’t need to *mean* anything. At the end of the day the
only semantics will be in the mind of the human reader. So we can try
to provide them with a language that they can use to be as descriptive
as is necessary, but only for their own purposes.

Of course, any language with an undefined semantics will not be *actually*
unambiguous in any objective way. But we might be able to at least avoid
certain classes of less obvious ambiguity.

In other words, it might be nice if we had a system that enforced
certain constraints about exhaustiveness and form while still allowing
the author to be as lazy and hand-wavy as they want if they decide it’s
not important to be more specific. There might be a value in forcing
ambiguity into sentences like ‘There is a function *F* (and I won’t
say anything else about it)’ rather than ‘When the program is finished,
all mailboxes should be empty’.

To that end the last (and only) feature of Pantagruel is that it can be
parsed by a computer program with a well-defined semantics of *binding*
and it can enforce certain constraints on binding. That is, it can
force the user to leave no symbol undefined, even if the definitions
entered are nonsensical or wrong. The hypothesis of Pantagruel is that
there is a cognitive benefit to requiring this kind of exhaustiveness,
even if there are no constraints placed on what is said.

Here’s a trivial but complete Pantagruel program.

```
fib |x : Nat| :: Nat
; A specification for the fibonacci function.
fib x <- fib x - 1 + fib x - 2
fib 1 <- 1
fib 2 <- 1
```

pretty printed, that’s:

fib : |x:ℕ| ∷ ℕ

A specification for the fibonacci function.

fib x ← fib x − 1 + fib x − 2 fib 1 ← 1

fib 2 ← 1

Line 1: A function declaration, introducing the `fib`

function, which
takes some `x`

in the domain of the natural numbers and returns some
natural number. Line 2: A comment describing the program.

Line 3: `fib x`

, that is, `fib`

of any `x`

, is *refined* by `fib`

of
`x - 1`

plus `fib`

of `x - 2`

.

Lines 4,5:

`fib`

of 1 is 1 and `fib`

of 2 is 1.
There are a few components to this, none of which should be particularly
novel: line 1 introduces a function and describes the arguments it takes,
giving each one a name in the process, in terms of their domains. It
also describes the codomain of the function.[^1] Line 2 is an English
comment. Any text between a `;`

and a newline is a comment; there are no
block comments, but multiple lines starting with `;`

will be treated as a
single paragraph. Lines 3-5 offer *refinements* for `fib`

; that is, some
*stronger* restatement of a function call `fib x`

. In this trivial case,
the three statements together completely describe the fibonacci function;
in a more complex example, there may be multiple levels of refinement
as an idea is fleshed out, which might end up in stubs or lacunae rather
than executable code. For instance, we might assert that `f x <- g x 1`

and later provide a sketch of the behavior of `g`

- for instance, saying
that it accepts two integers and returns one - without actually saying
what it *does*. A final thing that we can do being that this is not an
executable computer program is order the patterns in lines 3-5 according
to how we might think of them, with the general case first, rather than
how they would need to be in an ML-style pattern match, whence this is
obviously stolen, where the base case always needs to go first.

[^1]: Pantagruel uses the words “domain” and “codomain” as oppose to
“type” because the natural numbers (here defined as the integers greater
than 0) are not a type; they’re a set. In Pantagruel the expression ```
x :
X
```

says that `x`

is *in the domain* `X`

, but X can be a set of specific
values, a generic data type, or anything in between.

It’s not clear, aside from “me”. My hypothesis is that this will be interesting and maybe even useful to anybody who a) has an interest in formal methods or formal reasoning but b) is not working on projects of sufficient seriousness, or is not sufficiently clever and mathematically literate, to be using proper formal methods. It seems to me that it will be useful to have a well-defined language for communicating algorithms to oneself and others, and that if we can exploit its definition to subject it to automatic analysis and impose certain lightweight constraints, all the better.

To that end, the language itself needs lots of battle testing; lots
of thinking or whiteboarding done in it, to see what is still awkward
to express, what constructs are unnecessary or redundant. At the same
time I will continue to work on `pantagruel`

the computer program, to
build something that is capable of providing some amount of value given
a Pantagruel text file.

If available in Hex, the package can
be installed by adding `pantagruel`

to your list of dependencies in
`mix.exs`

:

def

deps

do

[

{

:pantagruel

,

"~> 0.1.0"

}

]

end

Documentation can be generated with ExDoc and published on HexDocs. Once published, the docs can be found at https://hexdocs.pm/pantagruel.