Lecture 5: Binary Operations and Sequential Form
Today we will extend the compiler to support binary arithmetic operations and not just increment and decrement. This is somewhat more difficult since
1 Growing the language: adding infix operators
Again, we follow our standard recipe:
Its impact on the concrete syntax of the language
Examples using the new enhancements, so we build intuition of them
Its impact on the abstract syntax and semantics of the language
Any new or changed transformations needed to process the new forms
Executable tests to confirm the enhancement works as intended
1.1 The new concrete syntax
‹expr› ... ‹expr› + ‹expr› ‹expr›  ‹expr› ‹expr› * ‹expr› ( ‹expr› )
1.2 Examples and semantics
These new expression forms should be familiar from standard arithmetic notation.
Note that while operator precedence will determine the tree structure
the expression is parsed into; it will not affect the evaluation
order. For this language, we will decide that the order of evaluation
should be leftmostinnermost: that is, in the expression (2  3)
+ 4 * 5
, the evaluation order should step through
(2  3) + 4 * 5
==> 1 + (4 * 5)
==> 1 + 20
==> 19
rather than the possible alternative of doing the multiplication first (a more literal reading of PEMDAS taught to American children).
1.3 Enhancing the abstract syntax
enum Prim2 {
Add,
Sub,
Mul,
}
enum Exp<Ann> {
...
Prim2(Prim2, Box<Exp<Ann>>, Box<Exp<Ann>>, Ann),
}
We simply add a new constructor describing our primitive binary operations, and an enumeration of what those operations might be. The parser will do the hard work of figuring out the correct tree structure for unparenthesized expressions like "1  2 + x * y".
1.4 Enhancing the transformations: Normalization
Exercise
What goes wrong with our current naive transformations? How can we fix them?
Let’s try manually “compiling” some simple binaryoperator expressions to assembly:
Original expression 
 Compiled assembly 












Do Now!
Convince yourself that using a letbound variable in place of any of these constants will work just as well.
So far, our compiler has only ever had to deal with a single active expression
at a time: it moves the result into RAX
, increments or decrements it, and
then potentially moves it somewhere onto the stack, for retrieval and later
use. But with our new compound expression forms, that won’t suffice: the
execution of (2  3) + (4 * 5)
above clearly must stash the result of
(2  3)
somewhere, to make room in RAX
for the subsequent
multiplication. We might try to use another register (RBX
, maybe?), but
clearly this approach won’t scale up, since there are only a handful of
registers available. What to do?
1.4.1 Immediate expressions
Do Now!
Why did the first few expressions compile successfully?
Notice that for the first few expressions, all the arguments to the operators were immediately ready:
They required no further computation to be ready.
They were either constants, or variables that could be read off the stack.
Perhaps we can salvage the final program by transforming it somehow, such that all its operations are on immediate values, too.
Do Now!
Try to do this: Find a program that computes the same answer, in the same order of operations, but where every operator is applied only to immediate values.
Note that conceptually, our last program is equivalent to the following:
let first = 2  3 in
let second = 4 * 5 in
first + second
This program has decomposed the compound addition expression into the sum of two letbound variables, each of which is a single operation on immediate values. We can easily compile each individual operation, and we already know how to save results to the stack and restore them for later use, which means we can compile this transformed program to assembly successfully.
Come to think of it, compiling operations when they are applied to
immediate values is so easy, wouldn’t it be nice if we did the same
thing for unary primitives and if? Then the compilation case for those
constructs would only involve the actual operation, rather than the
extra part about running a subexpression and putting its value in
rax
. Then the only expression form that would deal with
sequentially executing two expressions would be the let
form. This has the added benefit in that if we were to every change
how we run two programs sequentially, then we would only have to
change the let
case.
1.5 Testing
Do Now!
Once you’ve completed the section below, run the given source programs through our compiler pipeline. It should give us exactly the handwritten assembly we intend. If not, debug the compiler until it does.
2 Sequential Form
Our goal is to transform our program such that every operator is
applied only to immediate values (constants/variables), and every
expression (besides let
) does exactly one thing with no other
internal computation necessary. We will call such a form
Sequential Form1This is the name I have chosen to use in
this class. The most common name for this intermediate representation
is monadic normal form. There are many names for quite similar
intermediate representations: SSA (staticsingle assignment) is the
most common, used in the LLVM framework. Additionally, there are CPS
(continuationpassing style) and ANF (Anormal form). See
here
for more on the comparison between this form and SSA.
There are at least two ways to implement this. Firstly, we could write
a function sequentialize(&Exp) > Exp
that puts our expressions
into a sequential form. This type makes sense because the sequential
expressions form a subset of all expressions. However, this type
signature is imprecise in that the output doesn’t reflect the
fact that the output is sequential. This means when we write the next
function compile_to_instrs(&Exp) > Vec<Instr>
we will still
have to cover all expressions in our code, likely by using
panic!
when the input is not sequential. Instead we can
eliminate this mismatch by developing a new type SeqExp
that
allows for expressing only those programs in sequential form. We also
need to make a type ImmExp
for describing the subset of
immediate expressions.
enum ImmExp {
Num(i64),
Var(String),
}
enum SeqExp<Ann> {
Imm(ImmExp, Ann),
Prim1(Prim1, ImmExp, Ann),
Prim2(Prim2, ImmExp, ImmExp, Ann),
Let { var: String,
bound_exp: Box<SeqExp<Ann>>,
body: Box<SeqExp<Ann>>,
ann: Ann
},
If { cond: ImmExp,
thn: Box<SeqExp<Ann>>,
els: Box<SeqExp<Ann>>,
ann: Ann
},
}
Do Now!
Why did we choose to make
cond
an immediate, but notthn
andels
? Why?
So Prim1
, Prim2
require that their arguments are
immediates, while in the Let
form we require only that the two
subexpressions are in sequential form themselves. For the If
case the branches are allowed to be arbitrary sequential expressions,
since we don’t want to evaluate them unless they are selected by the
condition. The condition, on the other hand, is an immediate since it
will always be evaluated.
While we already knew how to compile Prim1
and If
with
full subexpressions, requiring the subexpressions to be immediates
simplifies the codegeneration pass since all "sequencing" code goes
into the Let
case. Now when we add more constructs to the
language, we can relegate all sequencing code to the Let
case
and not reimplement it for the new constructs.
Also note that while Exp
allowed for multiple bindings, here we
allow for only one binding at a time. This also simplifies the code
generation since we only have to handle one let at a time, and once we
have taken care of scopechecking, they should have equivalent
semantics.
2.1 Sequentializing our Programs
Exercise
Try to systematically define a conversion function
sequentialize(&Exp<u32>) > SeqExp<()>
such that the resulting expression has the same semantics.
Exercise
Why should the type of the function be
(&Exp<u32>) > SeqExp<()>
? In particular, why do we discard the input tags?
The central idea is that to convert some expression e1 + e2
(or
any other operator), we add new letbindings for every
subexpression. So e1 + e2
becomes let x1 = se1 in let x2 =
se2 in x1 + x2
where se1
is the result of putting e1
into
sequential form, and similarly for se2
. The trickiest part of
implementing this is making sure that the variable names we use
x1, x2
are different from all the names used by the source code,
as well as different from other variables we generate. To make sure
they are different from each other, we can use the unique tag we have
annotated on the term in a previous pass. To ensure they are different
from names from the source code, we can give them names that are not
valid syntactically. For instance, our parser only accepts variable
names that start with an ASCII alphabetic character, so if we start
our generated variable names with a nonalphabetic character we won’t
clash with source variable names.
fn sequentialize(e: &Exp<u32>) > SeqExp<()> {
match e {
...
Exp::Prim2(op, e1, e2, tag) => {
let s_e1 = sequentialize(e1);
let s_e2 = sequentialize(e2);
let name1 = format!("#prim2_1_{}", tag);
let name2 = format!("#prim2_2_{}", tag);
SeqExp::Let {
var: name1.clone(), bound_exp: Box::new(s_e1), ann: (),
body:
Box::new(SeqExp::Let {
var: name2.clone(), bound_exp: Box::new(s_e2), ann: (),
body: Box::new(SeqExp::Prim2(*op, ImmExp::Var(name1), ImmExp::Var(name2), ())),
})
}
},
...
}
}
Note that we discard the tags and replace them with empty annotations
()
in the output program. This makes sense because a
Prim2
gets translated to multiple expression forms (2
Let
and a Prim2
) so we cannot simply preserve the tag
without violating our invariant that all subexpressions have a unique
tag.
The other cases are similar, with the Let
case handling the
mismatch between binding sequences in Exp
and the
"oneatatime" Let
in SeqExp
. The main thing to be
careful of is to not get too greedy in sequentializing. When we
sequentialize an If
if e1: e2 else: e3
We should make sure to simply sequentialize the branches and lift the condition
let x1 = se1 in if x1: se2 else: se3
rather than lifting all of them
let x1 = se1 in
let x2 = se2 in
let x3 = se3 in
if x1: x2 else: x3
Which would always run both branches.
2.2 Improving the translation
This sequentialization pass is somewhat sloppy: it will generate many unnecessary temporary variables.
Do Now!
Find a simple expression that need not generate any extra variables, but for which
sequentialize
generates at least one unneeded variable.
For instance x + y
is already in sequential form, but this
translation will still add new bindings let #prim2_1_0 = x in let
#prim2_2_0 = y in #prim2_1_0 + #prim2_2_0
. There are at least two
ways to remedy this:
We could make the sequentialization code more complex by checking for this special case and not generating extra variables unless necessary
We could keep the sequentialization code the same and rely on later optimizations to eliminate these extra bindings.
We will discuss the relevant optimizations later in the semester. For now it is optional whether you want to make your sequentialization code eliminate these unnecessary bindings. If you do, I encourage you to find an elegant solution that uses a helper function rather than manually inspecting the subexpressions to check if they are immediates in each case.
2.3 An alternate approach: Just use the stack!
One could make the argument that converting to ANF is a complicated waste of
effort. We could simply walk the tree of EPrim2
expressions, evaluate
their left arguments and push them onto the stack —
On the face of it, it is indeed simpler. But as we’ll see later, this will
cause some additional headaches, because it entails that our stack frames are
of dynamic size, growing and shrinking depending on the complexity of the
expression being evaluated. This isn’t inherently a bad thing —
Additionally, though it isn’t apparent so far, having code in sequential form actually enables some subsequent compiler passes, like optimizations, that would be incredibly difficult to pull off otherwise. The advantages of keeping the compilerphases less tightly coupled, along with the later benefits of having code in a normalized form, tend to make Sequential form the winning engineering tradeoff.
Now, we can finally look at our current compiler pipeline:
fn compile(e: Exp<Span>) > String
/* make sure all names are in scope, and then */
let tagged = tag_exp(&e);
let se = sequentialize(&tagged);
let tagged_se = tag_seq_exp(&se);
let compiled = compile_to_instrs(tagged_se);
/* ... surround compiled with prelude as needed ... */
Quite a lot of changes, just for adding arithmetic and conditionals!
1This is the name I have chosen to use in this class. The most common name for this intermediate representation is monadic normal form. There are many names for quite similar intermediate representations: SSA (staticsingle assignment) is the most common, used in the LLVM framework. Additionally, there are CPS (continuationpassing style) and ANF (Anormal form). See here for more on the comparison between this form and SSA