347 lines
16 KiB
Markdown
347 lines
16 KiB
Markdown
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---
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title: "Bergamot: Exploring Programming Language Inference Rules"
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date: 2023-12-22T18:16:44-08:00
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draft: true
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tags: ["Project", "Programming Languages"]
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description: "In this post, I show off Bergamot, a tiny logic programming language and an idea for teaching inference rules."
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---
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{{< katex_component_js >}}
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{{< bergamot_js_css >}}
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### Inference Rules and the Study of Programming Languages
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In this post, I will talk about _inference rules_, particularly in the field
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of programming language theory. The first question to get out of the way is
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"what on earth is an inference rule?". The answer is simple: an inference rule
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is just a way of writing "if ... then ...". When writing an inference rule,
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we write the "if" stuff above a line, and the "then" stuff below the line. Really,
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that's all there is to it. I'll steal an example from another one of my posts on the blog -- here's an inference rule:
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{{< latex >}}
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\frac
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{\text{I'm allergic to cats} \quad \text{My friend has a cat}}
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{\text{I will not visit my friend very much}}
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{{</ latex >}}
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We can read this as "__if__ I'm allergic to cats, and my friend has a cat, __then__
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I will not visit my friend very much".
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In the field of programming languages, _inference rules_ are everywhere.
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Practically any paper I read has a table that looks something like this:
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{{< figure src="rules.png" caption="Inference rules from [Logarithm and program testing](https://dl.acm.org/doi/abs/10.1145/3498726) by Kuen-Bang Hou (Favonia) and Zhuyang Wang" class="fullwide" >}}
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And I, for one, love it! They're a precise and concise way to describe static
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and dynamic behavior of programs. I might've written this elsewhere on the blog,
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but whenever I read a paper, my eyes search for the rules first and foremost.
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But to those just starting their PL journey, inference rules can be quite cryptic
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-- I know they were to me! The first level of difficulty are the symbols: we have
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lots of Greek (\\(\\Gamma\\) and \\(\\Delta\\) for environments, \\(\\tau\\) and perhaps \\(\\sigma\\)
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for types), and the occasional mathematical symbol (the "entails" symbol \\(\\vdash\\) is the most
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common, but for operational semantics we can have \\(\\leadsto\\) and \\(\\Downarrow\\)).
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If you don't know what they mean, or if you're still getting used to them, symbols
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in judgements are difficult enough to parse.
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The second level of difficulty is making sense of the individual rules:
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individually, they tend to not be too bad, but for some languages, even making
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sense of one rule can be challenging. The following rule from the Calculus of
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Inductive Constructions is a doozy, for instance.
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{{< figure src="CIC.png" caption="The `match` inference rule from [Introduction to the Calculus of Inductive Constructions](https://inria.hal.science/hal-01094195/document) by Christine Paulin-Mohring" class="fullwide" >}}
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Just look at the metavariables! We have \\(\\textit{pars}\\), \\(t_1\\) through \\(t_p\\),
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\\(x_1\\) through \\(x_n\\), plain \\(x\\), and at least two other sets of variables. Not
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only this, but the rule requires at least some familiarity with [GADTs](https://en.wikipedia.org/wiki/Generalized_algebraic_data_type) to understand
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completely.
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The third level is making sense of how the rules work, _together_. In my
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programming languages class in college, a familiar question was:
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> the [Hindley-Milner type system](https://en.wikipedia.org/wiki/Hindley%E2%80%93Milner_type_system)
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> supports let-polymorphism only. What is it about the rules that implies let-polymorphism,
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> and not any other kind of polymorphism?
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If you don't know the answer, or the question doesn't make sense do you, don't
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worry about it -- suffice to say that whole systems of inference rules exhibit
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certain behaviors, and it takes familiarity with several rules to spot these
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behaviors.
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### Seeing What Works and What Doesn't
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Maybe I'm just a tinker-y sort of person, but for me, teaching inference rules
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just by showing them is not really enough. For instance, let me show you two
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ways of writing the following (informal) rule:
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> When adding two expressions, if both expressions are strings, then thse result
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> of adding them is also a string.
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There's a right way to write this inference rule, and there is a wrong way.
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Let me show you both, and try to explain the two. First, here's the wrong way:
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{{< latex >}}
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\cfrac
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{x : \text{string} \in \Gamma \quad y : \text{string} \in \Gamma}
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{\Gamma \vdash x + y : \text{string}}
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{{< /latex >}}
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This says that the type of adding two _variables_ of type `string` is still `string`.
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Here, \\(\\Gamma\\) is a _context_, which keeps track of which variable has what
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type. Writing \\(x : \\text{string} \\in \\Gamma\\) is the same as saying
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"we know the variable `x` has type `string`. The whole rule reads,
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> If the variables `x` and `y` both have type `string`,
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> then the result of adding these two variables, `x+y`, also has type `string`.
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The trouble with this rule is that it only works when adding two variables.
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But `x+x` is not itself a variable, so the rule wouldn't work for an expression
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like `(x+x)+(y+y)`. The proper way of writing the rule is, then, something like
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this:
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{{< latex >}}
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\cfrac
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{\Gamma \vdash e_1 : \text{string} \quad \Gamma \vdash e_2 : \text{string}}
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{\Gamma \vdash e_1 + e_2 : \text{string}}
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{{< /latex >}}
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This rule says:
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> If the two subexpressions `e1` and `e2` both have type `string`,
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> then the result of adding these two subexpressions, `e1+e2`, also has type `string`.
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Much better! We can apply this rule recursively: to get the type of `(x+x)+(y+y)`,
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we consider `(x+x)` and `(y+y)` as two subexpressions, and go on to compute
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their types first. We can then break `(x+x)` into two subexpressions (`x` and `x`),
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and determine their type separately. Supposing that the variables `x` and `y`
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indeed have the type `string`, this tells us that `(x+x)` and `(y+y)` are both
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string, and therefore that the whole of `(x+x)+(y+y)` is a string.
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What I'd really like to do is type the program in question and have the
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computer figure out whether my rules accept or reject this program.
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With my new rules, perhaps I'd get something like this:
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{{< figure src="goodrule.png" caption="Verifying the `(x+x)+(y+y)` expression using the good rule" class="fullwide" >}}
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On the other hand, since this expression doesn't work with my old rules, maybe
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i wouldn't get a valid type at all:
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{{< figure src="badrule.png" caption="Verifying (unsuccessfully) the `(x+x)+(y+y)` expression using the old rule" class="fullwide" >}}
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More generally, I want to be able to write down some inference rules, and apply
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them to some programs. This way, I can see what works and what doesn't, and when
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it works, which rules were used for what purposes. I also want to be able to
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try tweaking, removing, or adding inference rules, to see what breaks.
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This brings me to the project that I'm trying to show off in this post:
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Bergamot!
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### Introducing Bergamot
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A certain class of programming languages lends itself particularly well to
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writing inference rules and applying them to programs: logic programming.
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The most famous example of a logic programming language is [Prolog](https://www.swi-prolog.org/).
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In logic programming languages like Prolog, we can write rules describing when
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certain statements should hold. The simplest rule I could write is a fact. Perhaps
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I'd like to say that the number 42 is a "good" number:
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```Prolog
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good(42).
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```
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Perhaps I'd then like to say that adding two good numbers together creates
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another good number.
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```Prolog
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good(N) :- good(A), good(B), N is A+B.
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```
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The above can be read as:
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> the number `N` is good if the numbers `A` and `B` are good, and `N` is the sum of `A` and `B`.
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I can then ask Prolog to give me some good numbers:
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```Prolog
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?- good(X)
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```
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Prompting Prolog a few times, I get:
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```
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X = 42
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X = 84
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X = 126
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X = 168
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```
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It's not a huge leap from this to programming language type rules. Perhaps instead
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of something being "good", we can say that it has type `string`. Of course, adding
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two strings together, as we've established, creates another string. In Prolog:
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```Prolog
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/* A string literal like "hello" has type string */
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type(_, strlit(_), string).
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/* Adding two string expressions has type string */
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type(Env, plus(X, Y), string) :- type(Env, X, string), type(Env, Y, string).
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```
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That's almost identical to our inference rules above, except that it's written
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using code instead of mathematical notation! If we could just take these
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Prolog rules and display them as inference rules, we'd be able to "have our cake"
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(draw pretty inference rules like in the papers) and "eat it too" (run our rules
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on the computer against various programs).
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This is where it gets a teensy bit hairy. It's not that easy to embed a Prolog
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engine into the browser; alternatives that I've surveyed are either poorly documented,
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hard to extend, or both. Furthermore, for studying _what each rule was used for_,
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it's nice to be able to see a _proof tree_: a tree made up from the rules that
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we used to arrive at a particular answer. Prolog engines are excellent at
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applying rules and finding answers, but they don't usually provide a way
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to get all the rules that were used, making it harder to get proof trees.
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Thus, [Bergamot](https://dev.danilafe.com/Everything-I-Know-About-Types/bergamot-elm)
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is a new, tiny programming language that I threw together in a couple of days.
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It comes as JavaScript-based widget, and can be embedded into web pages like
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this one to provide an interactive way to write and explore proof trees. Here's
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a screenshot of what all of that looks like:
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{{< figure src="bergamot.png" caption="A screenshot of a Bergamot widget with some type rules" class="fullwide" >}}
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The components of Bergamot are:
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* The programming languages, as stated above. This language is a very simple,
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unification-based logic programming language.
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* A rule rendering system, which takes Prolog-like rules written in Bergamot
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and converts them into pretty LaTeX inference rules.
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* An Elm-based widget that you can embed into your web page, which accepts
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Bergamot rule and an input expression, and applies the rules to produce
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a result (or a whole proof tree!).
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Much like in Prolog, we can write Bergamot rules that describe when certain
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things are true. Unlike Prolog, Bergamot requires each rule to have a name.
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This is common practice in programming languages literature (when we talk
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about rules in papers, we like to be able to refer to them by name). Below
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are some sample Bergamot rules, corresponding to the first few inference rules
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in the above screenshot.
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```
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TNumber @ type(?Gamma, intlit(?n), number) <-;
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TString @ type(?Gamma, strlit(?s), string) <-;
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TVar @ type(?Gamma, var(?x), ?tau) <- inenv(?x, ?tau, ?Gamma);
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TPlusI @ type(?Gamma, plus(?e_1, ?e_2), number) <-
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type(?Gamma, ?e_1, number), type(?Gamma, ?e_2, number);
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TPlusS @ type(?Gamma, plus(?e_1, ?e_2), string) <-
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type(?Gamma, ?e_1, string), type(?Gamma, ?e_2, string);
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```
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Unlike Prolog, where "variables" are anything that starts with a capital letter,
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in Bergamot, variables are things that start with the special `?` symbol. Also,
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Prolog's `:-` has been replaced with an arrow symbol `<-`, for reverse implication.
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These are both purely syntactic differences.
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#### Demo
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If you want to play around with it, here's an embedded Bergamot widget with
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{{< sidenote "right" "wrong-rule-note" "some rules pre-programmed in." >}}
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Actually, one of the rules is incorrect to my knowledge. Can you spot it?
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Hint: is <code>\x : number. \x: string. x+1</code> well-typed? What does
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Bergamot report? Can you see why?
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{{< /sidenote >}}
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It has two modes:
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1. __Language Term__: accepts a rather simple programming language
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to typecheck. Try `1+1`, `fst((1,2))`, or maybe `(\x : number. x) 42`.
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2. __Query__: it accepts Bergamot expressions to query, similarly to Prolog; try
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`type(empty, ?e, tpair(number, string))` to search for expressions that have
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the type "a pair of a number and a string".
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{{< bergamot_widget id="widget-one" query="" prompt="PromptConverter @ prompt(type(empty, ?term, ?t)) <- input(?term);" >}}
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section "" {
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TNumber @ type(?Gamma, intlit(?n), number) <- int(?n);
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TString @ type(?Gamma, strlit(?s), string) <- str(?s);
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TVar @ type(?Gamma, var(?x), ?tau) <- inenv(?x, ?tau, ?Gamma);
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TPlusI @ type(?Gamma, plus(?e_1, ?e_2), number) <-
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type(?Gamma, ?e_1, number), type(?Gamma, ?e_2, number);
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TPlusS @ type(?Gamma, plus(?e_1, ?e_2), string) <-
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type(?Gamma, ?e_1, string), type(?Gamma, ?e_2, string);
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}
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section "" {
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TPair @ type(?Gamma, pair(?e_1, ?e_2), tpair(?tau_1, ?tau_2)) <-
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type(?Gamma, ?e_1, ?tau_1), type(?Gamma, ?e_2, ?tau_2);
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TFst @ type(?Gamma, fst(?e), ?tau_1) <-
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type(?Gamma, ?e, tpair(?tau_1, ?tau_2));
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TSnd @ type(?Gamma, snd(?e), ?tau_2) <-
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type(?Gamma, ?e, tpair(?tau_1, ?tau_2));
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}
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section "" {
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TAbs @ type(?Gamma, abs(?x, ?tau_1, ?e), tarr(?tau_1, ?tau_2)) <-
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type(extend(?Gamma, ?x, ?tau_1), ?e, ?tau_2);
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TApp @ type(?Gamma, app(?e_1, ?e_2), ?tau_2) <-
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type(?Gamma, ?e_1, tarr(?tau_1, ?tau_2)), type(?Gamma, ?e_2, ?tau_1);
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}
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section "" {
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GammaTake @ inenv(?x, ?tau_1, extend(?Gamma, ?x, ?tau_1)) <-;
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GammaSkip @ inenv(?x, ?tau_1, extend(?Gamma, ?y, ?tau_2)) <- inenv(?x, ?tau_1, ?Gamma);
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}
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{{< /bergamot_widget >}}
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#### Rendering Bergamot with Bergamot
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There's something to be said about the conversion between Bergamot's rules,
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encoded as plain text, and pretty LaTeX-based inference rules that the users
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see. Crucially, __we don't want to hardcode how any particular Bergamot
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expression is rendered__. For one, this is a losing battle: we can't possibly
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keep up with all the notation that people use in PL literature, and even if
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we focused ourselves on only "beginner" notation, there wouldn't be one way to do it!
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Different PL papers and texts use slightly different variations of notation.
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For instance, I render my pairs as \\((a, b)\\), but the very first screenshot
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in this post demonstrates a PL paper that writes pairs as \\(\\langle a, b \\rangle\\).
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Neither way (as far as I know!) is right or wrong. But if we hardcode one,
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we lose the ability to draw the other.
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More broadly, one aspect about writing PL rules is that _we control the notation_.
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We are free to define shorthands, symbols, and anything else that would make
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reading our rules easier for others. As an example, a paper from POPL22 about
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programming language semantics with garbage collection used a literal trash
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symbol in their rules:
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{{< figure src="trashrule.png" caption="A rule that uses a trashcan icon as notation, from [A separation logic for heap space under garbage collection](https://dl.acm.org/doi/10.1145/3498672) by Jean-Marie Madiot and François Pottier" >}}
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Thus, what I want to do is __encourage the (responsible) introduction of new notation__.
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This can only be done if Bergamot itself supports custom notation.
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When thinking about how I'd like to implement this custom notation, I was imagining
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some sort of templated rule engine, that would define how each term in a Bergamot
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program can be converted to its LaTeX variant. But then I realized: Bergamot
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is already a rule engine! Instead of inventing yet another language or format
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for defining LaTeX pretty printing, I could just use Bergamot. This turned
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out to work quite nicely -- the "Presentation Rules" tab in the demo above
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should open a text editor with Bergamot rules that handle the conversion
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of Bergamot notation into LaTex. Here are some example rules:
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```
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LatexPlus @ latex(plus(?e_1, ?e_2), ?l) <- latex(?e_1, ?l_1), latex(?e_2, ?l_2), join([?l_1, " + ", ?l_2], ?l);
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LatexPair @ latex(pair(?e_1, ?e_2), ?l) <- latex(?e_1, ?l_1), latex(?e_2, ?l_2), join(["(", ?l_1, ", ", ?l_2, ")"], ?l);
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```
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If we change the `LatexPair` to the following, we can make all pairs render
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using angle brackets:
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```
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LatexPair @ latex(pair(?e_1, ?e_2), ?l) <- latex(?e_1, ?l_1), latex(?e_2, ?l_2), join(["\\langle", ?l_1, ", ", ?l_2, "\\rangle"], ?l);
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```
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{{< figure src="rangle.png" caption="The LaTeX output when angle brackets are used in the rule instead of parentheses." >}}
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You can write rules about arbitrary Bergamot terms for rendering; thus, you can
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invent completely new notation for absolutely anything.
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### Next Steps
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I hope to use Bergamot to write a series of articles about type systems. By
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providing an interactive widget, I hope to make it possible for users to do
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exercises: writing variations of inference rules, or even tweaking the notation,
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and checking them against sets of programs to make sure that they work. Of course,
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I also that Bergamot can be used to explore _why_ an existing set of inference
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rules (such as Hindley-Milner) works. Stay tuned for those!
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