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fmt | ||
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README.md |
Here's how the compiler is laid out.
Parsing
The main goal of parsing is to take a plain old String (such as the contents a .roc source file read from the filesystem) and translate that String into an Expr
value.
Expr
is an enum
defined in the expr
module. An Expr
represents a Roc expression.
For example, parsing would translate this string...
"1 + 2"
...into this Expr
value:
BinOp(Int(1), Plus, Int(2))
Technically it would be
Box::new(Int(1))
andBox::new(Int(2))
, but that's beside the point for now.
This Expr
representation of the expression is useful for things like:
- Checking that all variables are declared before they're used
- Type checking
- Running Roc code in Interpreted Mode (that is, without having to compile it to Rust first - useful for development, since it's a faster feedback loop, but there's a runtime performance penalty compared to doing a full compile to Rust).
As of this writing, the compiler doesn't do any of those things yet. They'll be added later!
Since the parser is only concerned with translating String values into Expr values, it will happily translate syntactically valid strings into expressions that won't work at runtime.
For example, parsing will translate this string:
not "foo", "bar"
...into this Expr
:
CallByName("not", vec!["foo", "bar"])
Now we may know that not
takes a Bool
and returns another Bool
, but the parser doesn't know that.
The parser only knows how to translate a String
into an Expr
; it's the job of other parts of the compiler to figure out if Expr
values have problems like type mismatches and non-exhaustive patterns.
That said, the parser can still run into syntax errors. This won't parse:
if then 5 then else then
This is gibberish to the parser, so it will produce an error rather than an Expr
.
Roc's parser is implemented using the marwes/combine
crate.
Evaluating
One of the useful things we can do with an Expr
is to evaluate it.
The process of evaluation is basically to transform an Expr
into the simplest Expr
we can that's still equivalent to the original.
For example, let's say we had this code:
"1 + 2 - 3"
The parser will translate this into the following Expr
:
BinOp(
Int(1),
Plus,
BinOp(Int(2), Minus, Int(3))
)
The eval
function will take this Expr
and translate it into this much simpler Expr
:
Int(6)
At this point it's become so simple that we can display it to the end user as the number 6
. So running parse
and then eval
on the original Roc string of 1 + 8 - 3
will result in displaying 6
as the final output.
The
expr
module includes animpl fmt::Display for Expr
that takes care of translatingInt(6)
into6
,Char('x')
as'x'
, and so on.
eval
accomplishes this by doing a match
on an Expr
and resolving every operation it encounters. For example, when it first sees this:
BinOp(
Int(1),
Plus,
BinOp(Int(8), Minus, Int(3))
)
The first thing it does is to call eval
on the right Expr
values on either side of the Plus
. That results in:
- Calling
eval
onInt(1)
, which returnsInt(1)
since it can't be reduced any further. - Calling
eval
onBinOp(Int(8), Minus, Int(3))
, which in fact can be reduced further.
Since the second call to eval
will match on another BinOp
, it's once again going to recursively call eval
on both of its Expr
values. Since those are both Int
values, though, their eval
calls will return them right away without doing anything else.
Now that it's evaluated the expressions on either side of the Minus
, eval
will look at the particular operator being applied to those expressions (in this case, a minus operator) and check to see if the expressions it was given work with that operation.
Remember, this
Expr
value potentially came directly from the parser.eval
can't be sure any type checking has been done on it!
If eval
detects a non-numeric Expr
value (that is, the Expr
is not Int
or Frac
) on either side of the Minus
, then it will immediately give an error and halt the evaluation. This sort of runtime type error is common to dynamic languages, and you can think of eval
as being a dynamic evaluation of Roc code that hasn't necessarily been type-checked.
Assuming there's no type problem, eval
can go ahead and run the Rust code of 8 - 3
and store the result in an Int
expr.
That concludes our original recursive call to eval
, after which point we'll be evaluating this expression:
BinOp(
Int(1),
Plus,
Int(5)
)
This will work the same way as Minus
did, and will reduce down to Int(6)
.
Optimization philosophy
Focus on optimizations which are only safe in the absence of side effects, and leave the rest to LLVM.
This focus may lead to some optimizations becoming transitively in scope. For example, some deforestation examples in the MSR paper benefit from multiple rounds of interleaved deforestation, beta-reduction, and inlining. To get those benefits, we'd have to do some inlining and beta-reduction that we could otherwise leave to LLVM's inlining and constant propagation/folding.
Even if we're doing those things, it may still make sense to have LLVM do a pass for them as well, since early LLVM optimization passes may unlock later opportunities for inlining and constant propagation/folding.
Inlining
If a function is called exactly once (it's a helper function), presumably we always want to inline those. If a function is "small enough" it's probably worth inlining too.
Fusion
https://www.microsoft.com/en-us/research/wp-content/uploads/2016/07/deforestation-short-cut.pdf
Basic approach:
Do list stuff using build
passing Cons Nil (like a cons list) and then do foldr/build substitution/reduction.
Afterwards, we can do a separate pass to flatten nested Cons structures into properly initialized RRBTs.
This way we get both deforestation and efficient RRBT construction. Should work for the other collection types too.
It looks like we need to do some amount of inlining and beta reductions on the Roc side, rather than leaving all of those to LLVM.
Advanced approach:
Express operations like map and filter in terms of toStream and fromStream, to unlock more deforestation. More info on here: