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\title{\Huge
cfa-cc Developer's Reference
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\author{\LARGE
Fangren Yu
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\date{
\today
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\section{Overview}

cfa-cc is the reference compiler for the \CFA programming language, which is a non-
object-oriented extension to C.
\CFA attempts to introduce productive modern programming language features to C
while maintaining as much backward-compatibility as possible, so that most existing C
programs can seamlessly work with \CFA.

Since the \CFA project was dated back to the early 2000s, and only restarted in the past
few years, there is a significant amount of legacy code in the current compiler codebase,
with little proper documentation available. This becomes a difficulty while developing new
features based on the previous implementations, and especially while diagnosing
problems.

Currently, the \CFA team is also facing another problem: bad compiler performance. For
the development of a new programming language, writing a standard library is an
important part. The incompetence of the compiler causes building the library files to take
tens of minutes, making iterative development and testing almost impossible. There is
ongoing effort to rewrite the core data structure of the compiler to overcome the
performance issue, but many bugs may appear during the work, and lack of documentation
makes debugging extremely difficult.

This developer's reference will be continuously improved and eventually cover the
compiler codebase. For now, the focus is mainly on the parts being rewritten, and also the
performance bottleneck, namely the resolution algorithm. It is aimed to provide new
developers to the project enough guidance and clarify the purposes and behavior of certain
functions which are not mentioned in the previous \CFA research papers.


\section{Compiler Framework}

\subsection{AST Representation}

Source code input is first transformed into abstract syntax tree (AST) representation by the
parser before analyzed by the compiler.

There are 4 major categories of AST nodes used by the compiler, along with some derived
structures.

\subsubsection{Declaration nodes}

A declaration node represents either of:
\begin{itemize}
\item
Type declaration: struct, union, typedef or type parameter (see Appendix A.3)
\item
Variable declaration
\item
Function declaration
\end{itemize}
Declarations are introduced by standard C declarations, with the usual scoping rules.
In addition, declarations can also be introduced by the forall clause (which is the origin
of \CFA's name):
\begin{cfa}
forall (<$\emph{TypeParameterList}$> | <$\emph{AssertionList}$>)
        $\emph{declaration}$
\end{cfa}
Type parameters in \CFA are similar to \CC template type parameters. The \CFA
declaration
\begin{cfa}
forall (dtype T) ...
\end{cfa}
behaves similarly as the \CC template declaration
\begin{C++}
template <typename T> ...
\end{C++}

Assertions are a distinctive feature of \CFA: contrary to the \CC template where
arbitrary functions and operators can be used in a template definition, in a \CFA
parametric function, operations on parameterized types must be declared in assertions.

Consider the following \CC template:
\begin{C++}
template <typename T> int foo(T t) {
        return bar(t) + baz(t);
}
\end{C++}
Unless bar and baz are also parametric functions taking any argument type, they must be
declared in the assertions, or otherwise the code will not compile:
\begin{cfa}
forall (dtype T | { int bar(T); int baz(t); }) int foo (T t) {
        return bar(t) + baz(t);
}
\end{cfa}
Assertions are written using the usual function declaration syntax. The scope of type
parameters and assertions is the following declaration.

\subsubsection{Type nodes}

A type node represents the type of an object or expression.
Named types reference the corresponding type declarations. The type of a function is its
function pointer type (same as standard C).
With the addition of type parameters, named types may contain a list of parameter values
(actual parameter types).

\subsubsection{Statement nodes}

Statement nodes represent the statements in the program, including basic expression
statements, control flows and blocks.
Local declarations (within a block statement) are represented as declaration statements.

\subsubsection{Expression nodes}

Some expressions are represented differently in the compiler before and after resolution
stage:
\begin{itemize}
\item
Name expressions: NameExpr pre-resolution, VariableExpr post-resolution
\item
Member expressions: UntypedMemberExpr pre-resolution, MemberExpr post-resolution
\item
Function call expressions (including overloadable operators): UntypedExpr pre-resolution, ApplicationExpr post-resolution
\end{itemize}
The pre-resolution representations contain only the symbols. Post-resolution results link
them to the actual variable and function declarations.


\subsection{Compilation Passes}

Compilation steps are implemented as passes, which follows a general structural recursion
pattern on the syntax tree.

The basic work flow of compilation passes follows preorder and postorder traversal on
tree data structure, implemented with visitor pattern, and can be loosely described with
the following pseudocode:
\begin{C++}
Pass::visit (node_t node) {
        previsit(node);
        if (visit_children)
                for each child of node:
                        child.accept(this);
        postvisit(node);
}
\end{C++}
Operations in previsit() happen in preorder (top to bottom) and operations in
postvisit() happen in postorder (bottom to top). The precise order of recursive
operations on child nodes can be found in @Common/PassVisitor.impl.h@ (old) and
@AST/Pass.impl.hpp@ (new).
Implementations of compilation passes need to follow certain conventions:
\begin{itemize}
\item
Passes \textbf{should not} directly override the visit method (Non-virtual Interface
principle); if a pass desires different recursion behavior, it should set
@visit_children@ to false and perform recursive calls manually within previsit or
postvisit procedures. To enable this option, inherit from @WithShortCircuiting@ mixin.
\item
previsit may mutate the node but \textbf{must not} change the node type or return null.
\item
postvisit may mutate the node, reconstruct it to a different node type, or delete it by
returning null.
\item
If the previsit or postvisit method is not defined for a node type, the step is skipped.
If the return type is declared as void, the original node is returned by default. These
behaviors are controlled by template specialization rules; see
@Common/PassVisitor.proto.h@ (old) and @AST/Pass.proto.hpp@ (new) for details.
\end{itemize}
Other useful mixin classes for compilation passes include:
\begin{itemize}
\item
WithGuards allows saving values of variables and restore automatically upon exiting
the current node.
\item
WithVisitorRef creates a wrapped entity of current pass (the actual argument
passed to recursive calls internally) for explicit recursion, usually used together
with WithShortCircuiting.
\item
WithSymbolTable gives a managed symbol table with built-in scoping rule handling
(\eg on entering and exiting a block statement)
\end{itemize}
\NOTE: If a pass extends the functionality of another existing pass, due to \CC overloading
resolution rules, it \textbf{must} explicitly introduce the inherited previsit and postvisit procedures
to its own scope, or otherwise they will not be picked up by template resolution:
\begin{C++}
class Pass2: public Pass1 {
        using Pass1::previsit;
        using Pass1::postvisit;
        // new procedures
}
\end{C++}


\subsection{Data Structure Change WIP (new-ast)}

It has been observed that excessive copying of syntax tree structures accounts for a
majority of computation cost and significantly slows down the compiler. In the previous
implementation of the syntax tree, every internal node has a unique parent; therefore all
copies are required to duplicate everything down to the bottom. A new, experimental
re-implementation of the syntax tree (source under directory AST/ hereby referred to as
``new-ast'') attempts to overcome this issue with a functional approach that allows sharing
of common sub-structures and only makes copies when necessary.

The core of new-ast is a customized implementation of smart pointers, similar to
@std::shared_ptr@ and @std::weak_ptr@ in \CC standard library. Reference counting is
used to detect sharing and allows optimization. For a purely functional (a.k.a. immutable)
data structure, all mutations are modelled by shallow copies along the path of mutation.
With reference counting optimization, unique nodes are allowed to be mutated in place.
This however, may potentially introduce some complications and bugs; a few issues are
discussed near the end of this section.

\subsubsection{Source: AST/Node.hpp}

class @ast::Node@ is the base class of all new-ast node classes, which implements
reference counting mechanism. Two different counters are recorded: ``strong'' reference
count for number of nodes semantically owning it; ``weak'' reference count for number of
nodes holding a mere reference and only need to observe changes.
class @ast::ptr_base@ is the smart pointer implementation and also takes care of
resource management.

Direct access through the smart pointer is read-only. A mutable access should be obtained
by calling shallowCopy or mutate as below.

Currently, the weak pointers are only used to reference declaration nodes from a named
type, or a variable expression. Since declaration nodes are intended to denote unique
entities in the program, weak pointers always point to unique (unshared) nodes. This may
change in the future, and weak references to shared nodes may introduce some problems;
see mutate function below.

All node classes should always use smart pointers in the structure and should not use raw
pointers.

\begin{C++}
void ast::Node::increment(ref_type ref)
\end{C++}
Increments this node's strong or weak reference count.
\begin{C++}
void ast::Node::decrement(ref_type ref, bool do_delete = true)
\end{C++}
Decrements this node's strong or weak reference count. If strong reference count reaches
zero, the node is deleted by default.
\NOTE: Setting @do_delete@ to false may result in a detached node. Subsequent code should
manually delete the node or assign it to a strong pointer to prevent memory leak.
Reference counting functions are internally called by @ast::ptr_base@.
\begin{C++}
template<typename node_t>
node_t * shallowCopy(const node_t * node)
\end{C++}
Returns a mutable, shallow copy of node: all child pointers are pointing to the same child
nodes.
\begin{C++}
template<typename node_t>
node_t * mutate(const node_t * node)
\end{C++}
If node is unique (strong reference count is 1), returns a mutable pointer to the same node.
Otherwise, returns shallowCopy(node).
It is an error to mutate a shared node that is weak-referenced. Currently this does not
happen. The problem may appear once weak pointers to shared nodes (\eg expression
nodes) are used; special care will be needed.

\NOTE: This naive uniqueness check may not be sufficient in some cases. A discussion of the
issue is presented at the end of this section.
\begin{C++}
template<typename node_t, typename parent_t, typename field_t, typename assn_t>
const node_t * mutate_field(const node_t * node, field_t parent_t::*field, assn_t && val)
\end{C++}
\begin{C++}
template<typename node_t, typename parent_t, typename coll_t, typename ind_t,
                typename field_t>
const node_t * mutate_field_index(const node_t * node, coll_t parent_t::* field, ind_t i,
                field_t && val)
\end{C++}
Helpers for mutating a field on a node using pointer to member (creates shallow copy
when necessary).

\subsubsection{Issue: Undetected sharing}

The @mutate@ behavior described above has a problem: deeper shared nodes may be
mistakenly considered as unique. \VRef[Figure]{f:DeepNodeSharing} shows how the problem could arise:
\begin{figure}
\centering
\input{DeepNodeSharing}
\caption{Deep sharing of nodes}
\label{f:DeepNodeSharing}
\end{figure}
Suppose that we are working on the tree rooted at P1, which
is logically the chain P1-A-B and P2 is irrelevant, and then
mutate(B) is called. The algorithm considers B as unique since
it is only directly owned by A. However, the other tree P2-A-B
indirectly shares the node B and is therefore wrongly mutated.

To partly address this problem, if the mutation is called higher up the tree, a chain
mutation helper can be used:

\subsubsection{Source: AST/Chain.hpp}

\begin{C++}
template<typename node_t, Node::ref_type ref_t>
auto chain_mutate(ptr_base<node_t, ref_t> & base)
\end{C++}
This function returns a chain mutator handle which takes pointer-to-member to go down
the tree while creating shallow copies as necessary; see @struct _chain_mutator@ in the
source code for details.

For example, in the above diagram, if mutation of B is wanted while at P1, the call using
@chain_mutate@ looks like the following:
\begin{C++}
chain_mutate(P1.a)(&A.b) = new_value_of_b;
\end{C++}
Note that if some node in chain mutate is shared (therefore shallow copied), it implies that
every node further down will also be copied, thus correctly executing the functional
mutation algorithm. This example code creates copies of both A and B and performs
mutation on the new nodes, so that the other tree P2-A-B is untouched.
However, if a pass traverses down to node B and performs mutation, for example, in
@postvisit(B)@, information on sharing higher up is lost. Since the new-ast structure is only in
experimental use with the resolver algorithm, which mostly rebuilds the tree bottom-up,
this issue does not actually happen. It should be addressed in the future when other
compilation passes are migrated to new-ast and many of them contain procedural
mutations, where it might cause accidental mutations to other logically independent trees
(\eg common sub-expression) and become a bug.


\vspace*{20pt} % FIX ME, spacing problem with this heading ???
\section{Compiler Algorithm Documentation}

This documentation currently covers most of the resolver, data structures used in variable
and expression resolution, and a few directly related passes. Later passes involving code
generation is not included yet; documentation for those will be done afterwards.

\subsection{Symbol Table}

\NOTE: For historical reasons, the symbol table data structure was called ``indexer'' in the
old implementation. Hereby we will be using the name SymbolTable everywhere.
The symbol table stores a mapping from names to declarations and implements a similar
name space separation rule, and the same scoping rules in standard C.\footnote{ISO/IEC 9899:1999, Sections 6.2.1 and 6.2.3} The difference in
name space rule is that typedef aliases are no longer considered ordinary identifiers.
In addition to C tag types (struct, union, enum), \CFA introduces another tag type, trait,
which is a named collection of assertions.

\subsubsection{Source: AST/SymbolTable.hpp}

\subsubsection{Source: SymTab/Indexer.h}

\begin{C++}
SymbolTable::addId(const DeclWithType * decl)
\end{C++}
Since \CFA allows overloading of variables and functions, ordinary identifier names need
to be mangled. The mangling scheme is closely based on the Itanium \CC ABI,\footnote{\url{https://itanium-cxx-abi.github.io/cxx-abi/abi.html}, Section 5.1} while
making adaptations to \CFA specific features, mainly assertions and overloaded variables
by type. Naming conflicts are handled by mangled names; lookup by name returns a list of
declarations with the same literal identifier name.

\begin{C++}
SymbolTable::addStruct(const StructDecl * decl)
SymbolTable::addUnion(const UnionDecl * decl)
SymbolTable::addEnum(const EnumDecl * decl)
SymbolTable::addTrait(const TraitDecl * decl)
\end{C++}
Adds a tag type declaration to the symbol table.
\begin{C++}
SymbolTable::addType(const NamedTypeDecl * decl)
\end{C++}
Adds a typedef alias to the symbol table.

\textbf{C Incompatibility Note}: Since Cforall allows using struct, union and enum type names
without the keywords, typedef names and tag type names cannot be disambiguated by
syntax rules. Currently the compiler puts them together and disallows collision. The
following program is valid C but not valid Cforall:
\begin{C++}
struct A {};
typedef int A;
// gcc: ok, cfa: Cannot redefine typedef A
\end{C++}
In actual practices however, such usage is extremely rare, and typedef struct A A; is
not considered an error, but silently discarded. Therefore, we expect this change to have
minimal impact on existing C programs.
Meanwhile, the following program is allowed in Cforall:
\begin{C++}
typedef int A;
void A();
// gcc: A redeclared as different kind of symbol, cfa: ok
\end{C++}

\subsection{Type Environment and Unification}

The core of parametric type resolution algorithm.
Type Environment organizes type parameters in \textbf{equivalent classes} and maps them to
actual types. Unification is the algorithm that takes two (possibly parametric) types and
parameter mappings and attempts to produce a common type by matching the type
environments.

The unification algorithm is recursive in nature and runs in two different modes internally:
\begin{itemize}
\item
\textbf{Exact} unification mode requires equivalent parameters to match perfectly;
\item
\textbf{Inexact} unification mode allows equivalent parameters to be converted to a
common type.
\end{itemize}
For a pair of matching parameters (actually, their equivalent classes), if either side is open
(not bound to a concrete type yet), they are simply combined.

Within inexact mode, types are allowed to differ on their cv-qualifiers; additionally, if a
type never appear either in parameter list or as the base type of a pointer, it may also be
widened (i.e. safely converted). As Cforall currently does not implement subclassing similar
to object-oriented languages, widening conversions are on primitive types only, for
example the conversion from int to long.

The need for two unification modes come from the fact that parametric types are
considered compatible only if all parameters are exactly the same (not just compatible).
Pointer types also behaves similarly; in fact, they may be viewed as a primitive kind of
parametric types. @int*@ and @long*@ are different types, just like @vector(int)@ and
@vector(long)@ are, for the parametric type @vector(T)@.

The resolver should use the following ``@public@'' functions:\footnote{
Actual code also tracks assertions on type parameters; those extra arguments are omitted here for
conciseness.}


\subsubsection{Source: ResolvExpr/Unify.cc}

\begin{C++}
bool unify(const Type *type1, const Type *type2, TypeEnvironment &env,
OpenVarSet &openVars, const SymbolTable &symtab, Type *&commonType)
\end{C++}
Attempts to unify @type1@ and @type2@ with current type environment.

If operation succeeds, @env@ is modified by combining the equivalence classes of matching
parameters in @type1@ and @type2@, and their common type is written to commonType.

If operation fails, returns false.
\begin{C++}
bool typesCompatible(const Type * type1, const Type * type2, const
SymbolTable &symtab, const TypeEnvironment &env)
bool typesCompatibleIgnoreQualifiers(const Type * type1, const Type *
type2, const SymbolTable &symtab, const TypeEnvironment &env)
\end{C++}

Determines if type1 and type2 can possibly be the same type. The second version ignores
the outermost cv-qualifiers if present.\footnote{
In const \lstinline@int * const@, only the second \lstinline@const@ is ignored.}

The call has no side effect.

\NOTE: No attempts are made to widen the types (exact unification is used), although the
function names may suggest otherwise. E.g. @typesCompatible(int, long)@ returns false.


\subsection{Expression Resolution}

The design of the current version of expression resolver is outlined in the Ph.D. Thesis from
Aaron Moss~\cite{Moss19}.

A summary of the resolver algorithm for each expression type is presented below.

All overloadable operators are modelled as function calls. For a function call,
interpretations of the function and arguments are found recursively. Then the following
steps produce a filtered list of valid interpretations:
\begin{enumerate}
\item
From all possible combinations of interpretations of the function and arguments,
those where argument types may be converted to function parameter types are
considered valid.
\item
Valid interpretations with the minimum sum of argument costs are kept.
\item
Argument costs are then discarded; the actual cost for the function call expression is
the sum of conversion costs from the argument types to parameter types.
\item
For each return type, the interpretations with satisfiable assertions are then sorted
by actual cost computed in step 3. If for a given type, the minimum cost
interpretations are not unique, it is said that for that return type the interpretation
is ambiguous. If the minimum cost interpretation is unique but contains an
ambiguous argument, it is also considered ambiguous.
\end{enumerate}
Therefore, for each return type, the resolver produces either of:
\begin{itemize}
\item
No alternatives
\item
A single valid alternative
\item
An ambiguous alternative
\end{itemize}
Note that an ambiguous alternative may be discarded at the parent expressions because a
different return type matches better for the parent expressions.

The non-overloadable expressions in Cforall are: cast expressions, address-of (unary @&@)
expressions, short-circuiting logical expressions (@&&@, @||@) and ternary conditional
expression (@?:@).

For a cast expression, the convertible argument types are kept. Then the result is selected
by lowest argument cost, and further by lowest conversion cost to target type. If the lowest
cost is still not unique, or an ambiguous argument interpretation is selected, the cast
expression is ambiguous. In an expression statement, the top level expression is implicitly
cast to void.

For an address-of expression, only lvalue results are kept and the minimum cost is selected.

For logical expressions @&&@ and @||@, arguments are implicitly cast to bool, and follow the rule
of cast expression as above.

For the ternary conditional expression, the condition is implicitly cast to bool, and the
branch expressions must have compatible types. Each pair of compatible branch
expression types produce a possible interpretation, and the cost is defined as the sum of
expression costs plus the sum of conversion costs to the common type.

TODO: Write a specification for expression costs.


\subsection{Assertion Satisfaction}

The resolver tries to satisfy assertions on expressions only when it is needed: either while
selecting from multiple alternatives of a same result type for a function call (step 4 of
resolving function calls), or upon reaching the top level of an expression statement.

Unsatisfiable alternatives are discarded. Satisfiable alternatives receive \textbf{implicit
parameters}: in Cforall, parametric functions are designed such that they can be compiled
separately, as opposed to \CC templates which are only compiled at instantiation. Given a
parametric function definition:
\begin{C++}
forall (otype T | {void foo(T);})
void bar (T t) { foo(t); }
\end{C++}
The function bar does not know which @foo@ to call when compiled without knowing the call
site, so it requests a function pointer to be passed as an extra argument. At the call site,
implicit parameters are automatically inserted by the compiler.

\textbf{TODO}: Explain how recursive assertion satisfaction and polymorphic recursion work.


\section{Tests}

\subsection{Test Suites}

Automatic test suites are located under the @tests/@ directory. A test case consists of an
input CFA source file (name ending with @.cfa@), and an expected output file located
in @.expect/@ directory relative to the source file, with the same file name ending with @.txt@.
So a test named @tuple/tupleCast@ has the following files, for example:
\begin{C++}
tests/
..     tuple/
......     .expect/
..........       tupleCast.txt
......     tupleCast.cfa
\end{C++}
If compilation fails, the error output is compared to the expect file. If compilation succeeds,
the built program is run and its output compared to the expect file.
To run the tests, execute the test script @test.py@ under the @tests/@ directory, with a list of
test names to be run, or @--all@ to run all tests. The test script reports test cases
fail/success, compilation time and program run time.


\subsection{Performance Reports}

To turn on performance reports, pass @-S@ flag to the compiler.

3 kinds of performance reports are available:
\begin{enumerate}
\item
Time, reports time spent in each compilation step
\item
Heap, reports number of dynamic memory allocations, total bytes allocated, and
maximum heap memory usage
\item
Counters, for certain predefined statistics; counters can be registered anywhere in
the compiler as a static object, and the interface can be found at
@Common/Stats/Counter.h@.
\end{enumerate}
It is suggested to run performance tests with optimized build (@g++@ flag @-O3@)


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