- Introduction
- General Information
- Important and useful LLVM APIs
- The
isa<>
,cast<>
anddyn_cast<>
templates - Passing strings (the
StringRef
andTwine
classes) - Formatting strings (the
formatv
function) - Error handling
- Programmatic Errors
- Recoverable Errors
- StringError
- Interoperability with std::error_code and ErrorOr
- Returning Errors from error handlers
- Using ExitOnError to simplify tool code
- Using cantFail to simplify safe callsites
- Fallible constructors
- Propagating and consuming errors based on types
- Concatenating Errors with joinErrors
- Building fallible iterators and iterator ranges
- Passing functions and other callable objects
- The
LLVM_DEBUG()
macro and-debug
option - The
Statistic
class &-stats
option - Adding debug counters to aid in debugging your code
- Viewing graphs while debugging code
- The
- Picking the Right Data Structure for a Task
- Debugging
- Helpful Hints for Common Operations
- Basic Inspection and Traversal Routines
- Iterating over the
BasicBlock
in aFunction
- Iterating over the
Instruction
in aBasicBlock
- Iterating over the
Instruction
in aFunction
- Turning an iterator into a class pointer (and vice-versa)
- Finding call sites: a slightly more complex example
- Treating calls and invokes the same way
- Iterating over def-use & use-def chains
- Iterating over predecessors & successors of blocks
- Iterating over the
- Making simple changes
- Basic Inspection and Traversal Routines
- Threads and LLVM
- Advanced Topics
- The Core LLVM Class Hierarchy Reference
Warning
This is always a work in progress.
This document is meant to highlight some of the important classes and interfaces available in the LLVM source-base. This manual is not intended to explain what LLVM is, how it works, and what LLVM code looks like. It assumes that you know the basics of LLVM and are interested in writing transformations or otherwise analyzing or manipulating the code.
This document should get you oriented so that you can find your way in the continuously growing source code that makes up the LLVM infrastructure. Note that this manual is not intended to serve as a replacement for reading the source code, so if you think there should be a method in one of these classes to do something, but it's not listed, check the source. Links to the doxygen sources are provided to make this as easy as possible.
The first section of this document describes general information that is useful
to know when working in the LLVM infrastructure, and the second describes the
Core LLVM classes. In the future this manual will be extended with information
describing how to use extension libraries, such as dominator information, CFG
traversal routines, and useful utilities like the InstVisitor
(doxygen) template.
This section contains general information that is useful if you are working in the LLVM source-base, but that isn't specific to any particular API.
LLVM makes heavy use of the C++ Standard Template Library (STL), perhaps much more than you are used to, or have seen before. Because of this, you might want to do a little background reading in the techniques used and capabilities of the library. There are many good pages that discuss the STL, and several books on the subject that you can get, so it will not be discussed in this document.
Here are some useful links:
- cppreference.com - an excellent reference for the STL and other parts of the standard C++ library.
- C++ In a Nutshell - This is an O'Reilly book in the making. It has a decent Standard Library Reference that rivals Dinkumware's, and is unfortunately no longer free since the book has been published.
- C++ Frequently Asked Questions.
- SGI's STL Programmer's Guide - Contains a useful Introduction to the STL.
- Bjarne Stroustrup's C++ Page.
- Bruce Eckel's Thinking in C++, 2nd ed. Volume 2 Revision 4.0 (even better, get the book).
You are also encouraged to take a look at the :doc:`LLVM Coding Standards <CodingStandards>` guide which focuses on how to write maintainable code more than where to put your curly braces.
Here we highlight some LLVM APIs that are generally useful and good to know about when writing transformations.
The LLVM source-base makes extensive use of a custom form of RTTI. These
templates have many similarities to the C++ dynamic_cast<>
operator, but
they don't have some drawbacks (primarily stemming from the fact that
dynamic_cast<>
only works on classes that have a v-table). Because they are
used so often, you must know what they do and how they work. All of these
templates are defined in the llvm/Support/Casting.h
(doxygen) file (note that you very
rarely have to include this file directly).
isa<>
:- The
isa<>
operator works exactly like the Java "instanceof
" operator. It returns true or false depending on whether a reference or pointer points to an instance of the specified class. This can be very useful for constraint checking of various sorts (example below). cast<>
:The
cast<>
operator is a "checked cast" operation. It converts a pointer or reference from a base class to a derived class, causing an assertion failure if it is not really an instance of the right type. This should be used in cases where you have some information that makes you believe that something is of the right type. An example of theisa<>
andcast<>
template is:static bool isLoopInvariant(const Value *V, const Loop *L) { if (isa<Constant>(V) || isa<Argument>(V) || isa<GlobalValue>(V)) return true; // Otherwise, it must be an instruction... return !L->contains(cast<Instruction>(V)->getParent()); }
Note that you should not use an
isa<>
test followed by acast<>
, for that use thedyn_cast<>
operator.dyn_cast<>
:The
dyn_cast<>
operator is a "checking cast" operation. It checks to see if the operand is of the specified type, and if so, returns a pointer to it (this operator does not work with references). If the operand is not of the correct type, a null pointer is returned. Thus, this works very much like thedynamic_cast<>
operator in C++, and should be used in the same circumstances. Typically, thedyn_cast<>
operator is used in anif
statement or some other flow control statement like this:if (auto *AI = dyn_cast<AllocationInst>(Val)) { // ... }
This form of the
if
statement effectively combines together a call toisa<>
and a call tocast<>
into one statement, which is very convenient.Note that the
dyn_cast<>
operator, like C++'sdynamic_cast<>
or Java'sinstanceof
operator, can be abused. In particular, you should not use big chainedif/then/else
blocks to check for lots of different variants of classes. If you find yourself wanting to do this, it is much cleaner and more efficient to use theInstVisitor
class to dispatch over the instruction type directly.cast_or_null<>
:- The
cast_or_null<>
operator works just like thecast<>
operator, except that it allows for a null pointer as an argument (which it then propagates). This can sometimes be useful, allowing you to combine several null checks into one. dyn_cast_or_null<>
:- The
dyn_cast_or_null<>
operator works just like thedyn_cast<>
operator, except that it allows for a null pointer as an argument (which it then propagates). This can sometimes be useful, allowing you to combine several null checks into one.
These five templates can be used with any classes, whether they have a v-table or not. If you want to add support for these templates, see the document :doc:`How to set up LLVM-style RTTI for your class hierarchy <HowToSetUpLLVMStyleRTTI>`
Although LLVM generally does not do much string manipulation, we do have several
important APIs which take strings. Two important examples are the Value class
-- which has names for instructions, functions, etc. -- and the StringMap
class which is used extensively in LLVM and Clang.
These are generic classes, and they need to be able to accept strings which may
have embedded null characters. Therefore, they cannot simply take a const
char *
, and taking a const std::string&
requires clients to perform a heap
allocation which is usually unnecessary. Instead, many LLVM APIs use a
StringRef
or a const Twine&
for passing strings efficiently.
The StringRef
data type represents a reference to a constant string (a
character array and a length) and supports the common operations available on
std::string
, but does not require heap allocation.
It can be implicitly constructed using a C style null-terminated string, an
std::string
, or explicitly with a character pointer and length. For
example, the StringRef
find function is declared as:
iterator find(StringRef Key);
and clients can call it using any one of:
Map.find("foo"); // Lookup "foo"
Map.find(std::string("bar")); // Lookup "bar"
Map.find(StringRef("\0baz", 4)); // Lookup "\0baz"
Similarly, APIs which need to return a string may return a StringRef
instance, which can be used directly or converted to an std::string
using
the str
member function. See llvm/ADT/StringRef.h
(doxygen) for more
information.
You should rarely use the StringRef
class directly, because it contains
pointers to external memory it is not generally safe to store an instance of the
class (unless you know that the external storage will not be freed).
StringRef
is small and pervasive enough in LLVM that it should always be
passed by value.
The Twine
(doxygen)
class is an efficient way for APIs to accept concatenated strings. For example,
a common LLVM paradigm is to name one instruction based on the name of another
instruction with a suffix, for example:
New = CmpInst::Create(..., SO->getName() + ".cmp");
The Twine
class is effectively a lightweight rope which points to
temporary (stack allocated) objects. Twines can be implicitly constructed as
the result of the plus operator applied to strings (i.e., a C strings, an
std::string
, or a StringRef
). The twine delays the actual concatenation
of strings until it is actually required, at which point it can be efficiently
rendered directly into a character array. This avoids unnecessary heap
allocation involved in constructing the temporary results of string
concatenation. See llvm/ADT/Twine.h
(doxygen) and :ref:`here <dss_twine>`
for more information.
As with a StringRef
, Twine
objects point to external memory and should
almost never be stored or mentioned directly. They are intended solely for use
when defining a function which should be able to efficiently accept concatenated
strings.
While LLVM doesn't necessarily do a lot of string manipulation and parsing, it
does do a lot of string formatting. From diagnostic messages, to llvm tool
outputs such as llvm-readobj
to printing verbose disassembly listings and
LLDB runtime logging, the need for string formatting is pervasive.
The formatv
is similar in spirit to printf
, but uses a different syntax
which borrows heavily from Python and C#. Unlike printf
it deduces the type
to be formatted at compile time, so it does not need a format specifier such as
%d
. This reduces the mental overhead of trying to construct portable format
strings, especially for platform-specific types like size_t
or pointer types.
Unlike both printf
and Python, it additionally fails to compile if LLVM does
not know how to format the type. These two properties ensure that the function
is both safer and simpler to use than traditional formatting methods such as
the printf
family of functions.
A call to formatv
involves a single format string consisting of 0 or more
replacement sequences, followed by a variable length list of replacement values.
A replacement sequence is a string of the form {N[[,align]:style]}
.
N
refers to the 0-based index of the argument from the list of replacement
values. Note that this means it is possible to reference the same parameter
multiple times, possibly with different style and/or alignment options, in any order.
align
is an optional string specifying the width of the field to format
the value into, and the alignment of the value within the field. It is specified as
an optional alignment style followed by a positive integral field width. The
alignment style can be one of the characters -
(left align), =
(center align),
or +
(right align). The default is right aligned.
style
is an optional string consisting of a type specific that controls the
formatting of the value. For example, to format a floating point value as a percentage,
you can use the style option P
.
There are two ways to customize the formatting behavior for a type.
- Provide a template specialization of
llvm::format_provider<T>
for your typeT
with the appropriate static format method.
namespace llvm { template<> struct format_provider<MyFooBar> { static void format(const MyFooBar &V, raw_ostream &Stream, StringRef Style) { // Do whatever is necessary to format `V` into `Stream` } }; void foo() { MyFooBar X; std::string S = formatv("{0}", X); } }This is a useful extensibility mechanism for adding support for formatting your own custom types with your own custom Style options. But it does not help when you want to extend the mechanism for formatting a type that the library already knows how to format. For that, we need something else.
- Provide a format adapter inheriting from
llvm::FormatAdapter<T>
.
namespace anything { struct format_int_custom : public llvm::FormatAdapter<int> { explicit format_int_custom(int N) : llvm::FormatAdapter<int>(N) {} void format(llvm::raw_ostream &Stream, StringRef Style) override { // Do whatever is necessary to format ``this->Item`` into ``Stream`` } }; } namespace llvm { void foo() { std::string S = formatv("{0}", anything::format_int_custom(42)); } }If the type is detected to be derived from
FormatAdapter<T>
,formatv
will call theformat
method on the argument passing in the specified style. This allows one to provide custom formatting of any type, including one which already has a builtin format provider.
Below is intended to provide an incomplete set of examples demonstrating
the usage of formatv
. More information can be found by reading the
doxygen documentation or by looking at the unit test suite.
std::string S;
// Simple formatting of basic types and implicit string conversion.
S = formatv("{0} ({1:P})", 7, 0.35); // S == "7 (35.00%)"
// Out-of-order referencing and multi-referencing
outs() << formatv("{0} {2} {1} {0}", 1, "test", 3); // prints "1 3 test 1"
// Left, right, and center alignment
S = formatv("{0,7}", 'a'); // S == " a";
S = formatv("{0,-7}", 'a'); // S == "a ";
S = formatv("{0,=7}", 'a'); // S == " a ";
S = formatv("{0,+7}", 'a'); // S == " a";
// Custom styles
S = formatv("{0:N} - {0:x} - {1:E}", 12345, 123908342); // S == "12,345 - 0x3039 - 1.24E8"
// Adapters
S = formatv("{0}", fmt_align(42, AlignStyle::Center, 7)); // S == " 42 "
S = formatv("{0}", fmt_repeat("hi", 3)); // S == "hihihi"
S = formatv("{0}", fmt_pad("hi", 2, 6)); // S == " hi "
// Ranges
std::vector<int> V = {8, 9, 10};
S = formatv("{0}", make_range(V.begin(), V.end())); // S == "8, 9, 10"
S = formatv("{0:$[+]}", make_range(V.begin(), V.end())); // S == "8+9+10"
S = formatv("{0:$[ + ]@[x]}", make_range(V.begin(), V.end())); // S == "0x8 + 0x9 + 0xA"
Proper error handling helps us identify bugs in our code, and helps end-users understand errors in their tool usage. Errors fall into two broad categories: programmatic and recoverable, with different strategies for handling and reporting.
Programmatic errors are violations of program invariants or API contracts, and represent bugs within the program itself. Our aim is to document invariants, and to abort quickly at the point of failure (providing some basic diagnostic) when invariants are broken at runtime.
The fundamental tools for handling programmatic errors are assertions and the llvm_unreachable function. Assertions are used to express invariant conditions, and should include a message describing the invariant:
assert(isPhysReg(R) && "All virt regs should have been allocated already.");
The llvm_unreachable function can be used to document areas of control flow that should never be entered if the program invariants hold:
enum { Foo, Bar, Baz } X = foo();
switch (X) {
case Foo: /* Handle Foo */; break;
case Bar: /* Handle Bar */; break;
default:
llvm_unreachable("X should be Foo or Bar here");
}
Recoverable errors represent an error in the program's environment, for example a resource failure (a missing file, a dropped network connection, etc.), or malformed input. These errors should be detected and communicated to a level of the program where they can be handled appropriately. Handling the error may be as simple as reporting the issue to the user, or it may involve attempts at recovery.
Note
While it would be ideal to use this error handling scheme throughout
LLVM, there are places where this hasn't been practical to apply. In
situations where you absolutely must emit a non-programmatic error and
the Error
model isn't workable you can call report_fatal_error
,
which will call installed error handlers, print a message, and exit the
program.
Recoverable errors are modeled using LLVM's Error
scheme. This scheme
represents errors using function return values, similar to classic C integer
error codes, or C++'s std::error_code
. However, the Error
class is
actually a lightweight wrapper for user-defined error types, allowing arbitrary
information to be attached to describe the error. This is similar to the way C++
exceptions allow throwing of user-defined types.
Success values are created by calling Error::success()
, E.g.:
Error foo() {
// Do something.
// Return success.
return Error::success();
}
Success values are very cheap to construct and return - they have minimal impact on program performance.
Failure values are constructed using make_error<T>
, where T
is any class
that inherits from the ErrorInfo utility, E.g.:
class BadFileFormat : public ErrorInfo<BadFileFormat> {
public:
static char ID;
std::string Path;
BadFileFormat(StringRef Path) : Path(Path.str()) {}
void log(raw_ostream &OS) const override {
OS << Path << " is malformed";
}
std::error_code convertToErrorCode() const override {
return make_error_code(object_error::parse_failed);
}
};
char BadFileFormat::ID; // This should be declared in the C++ file.
Error printFormattedFile(StringRef Path) {
if (<check for valid format>)
return make_error<BadFileFormat>(Path);
// print file contents.
return Error::success();
}
Error values can be implicitly converted to bool: true for error, false for success, enabling the following idiom:
Error mayFail();
Error foo() {
if (auto Err = mayFail())
return Err;
// Success! We can proceed.
...
For functions that can fail but need to return a value the Expected<T>
utility can be used. Values of this type can be constructed with either a
T
, or an Error
. Expected<T> values are also implicitly convertible to
boolean, but with the opposite convention to Error
: true for success, false
for error. If success, the T
value can be accessed via the dereference
operator. If failure, the Error
value can be extracted using the
takeError()
method. Idiomatic usage looks like:
Expected<FormattedFile> openFormattedFile(StringRef Path) {
// If badly formatted, return an error.
if (auto Err = checkFormat(Path))
return std::move(Err);
// Otherwise return a FormattedFile instance.
return FormattedFile(Path);
}
Error processFormattedFile(StringRef Path) {
// Try to open a formatted file
if (auto FileOrErr = openFormattedFile(Path)) {
// On success, grab a reference to the file and continue.
auto &File = *FileOrErr;
...
} else
// On error, extract the Error value and return it.
return FileOrErr.takeError();
}
If an Expected<T>
value is in success mode then the takeError()
method
will return a success value. Using this fact, the above function can be
rewritten as:
Error processFormattedFile(StringRef Path) {
// Try to open a formatted file
auto FileOrErr = openFormattedFile(Path);
if (auto Err = FileOrErr.takeError())
// On error, extract the Error value and return it.
return Err;
// On success, grab a reference to the file and continue.
auto &File = *FileOrErr;
...
}
This second form is often more readable for functions that involve multiple
Expected<T>
values as it limits the indentation required.
All Error
instances, whether success or failure, must be either checked or
moved from (via std::move
or a return) before they are destructed.
Accidentally discarding an unchecked error will cause a program abort at the
point where the unchecked value's destructor is run, making it easy to identify
and fix violations of this rule.
Success values are considered checked once they have been tested (by invoking the boolean conversion operator):
if (auto Err = mayFail(...))
return Err; // Failure value - move error to caller.
// Safe to continue: Err was checked.
In contrast, the following code will always cause an abort, even if mayFail
returns a success value:
mayFail();
// Program will always abort here, even if mayFail() returns Success, since
// the value is not checked.
Failure values are considered checked once a handler for the error type has been activated:
handleErrors(
processFormattedFile(...),
[](const BadFileFormat &BFF) {
report("Unable to process " + BFF.Path + ": bad format");
},
[](const FileNotFound &FNF) {
report("File not found " + FNF.Path);
});
The handleErrors
function takes an error as its first argument, followed by
a variadic list of "handlers", each of which must be a callable type (a
function, lambda, or class with a call operator) with one argument. The
handleErrors
function will visit each handler in the sequence and check its
argument type against the dynamic type of the error, running the first handler
that matches. This is the same decision process that is used decide which catch
clause to run for a C++ exception.
Since the list of handlers passed to handleErrors
may not cover every error
type that can occur, the handleErrors
function also returns an Error value
that must be checked or propagated. If the error value that is passed to
handleErrors
does not match any of the handlers it will be returned from
handleErrors. Idiomatic use of handleErrors
thus looks like:
if (auto Err =
handleErrors(
processFormattedFile(...),
[](const BadFileFormat &BFF) {
report("Unable to process " + BFF.Path + ": bad format");
},
[](const FileNotFound &FNF) {
report("File not found " + FNF.Path);
}))
return Err;
In cases where you truly know that the handler list is exhaustive the
handleAllErrors
function can be used instead. This is identical to
handleErrors
except that it will terminate the program if an unhandled
error is passed in, and can therefore return void. The handleAllErrors
function should generally be avoided: the introduction of a new error type
elsewhere in the program can easily turn a formerly exhaustive list of errors
into a non-exhaustive list, risking unexpected program termination. Where
possible, use handleErrors and propagate unknown errors up the stack instead.
For tool code, where errors can be handled by printing an error message then exiting with an error code, the :ref:`ExitOnError <err_exitonerr>` utility may be a better choice than handleErrors, as it simplifies control flow when calling fallible functions.
In situations where it is known that a particular call to a fallible function will always succeed (for example, a call to a function that can only fail on a subset of inputs with an input that is known to be safe) the :ref:`cantFail <err_cantfail>` functions can be used to remove the error type, simplifying control flow.
Many kinds of errors have no recovery strategy, the only action that can be
taken is to report them to the user so that the user can attempt to fix the
environment. In this case representing the error as a string makes perfect
sense. LLVM provides the StringError
class for this purpose. It takes two
arguments: A string error message, and an equivalent std::error_code
for
interoperability:
make_error<StringError>("Bad executable",
make_error_code(errc::executable_format_error"));
If you're certain that the error you're building will never need to be converted
to a std::error_code
you can use the inconvertibleErrorCode()
function:
make_error<StringError>("Bad executable", inconvertibleErrorCode());
This should be done only after careful consideration. If any attempt is made to
convert this error to a std::error_code
it will trigger immediate program
termination. Unless you are certain that your errors will not need
interoperability you should look for an existing std::error_code
that you
can convert to, and even (as painful as it is) consider introducing a new one as
a stopgap measure.
Many existing LLVM APIs use std::error_code
and its partner ErrorOr<T>
(which plays the same role as Expected<T>
, but wraps a std::error_code
rather than an Error
). The infectious nature of error types means that an
attempt to change one of these functions to return Error
or Expected<T>
instead often results in an avalanche of changes to callers, callers of callers,
and so on. (The first such attempt, returning an Error
from
MachOObjectFile's constructor, was abandoned after the diff reached 3000 lines,
impacted half a dozen libraries, and was still growing).
To solve this problem, the Error
/std::error_code
interoperability requirement was
introduced. Two pairs of functions allow any Error
value to be converted to a
std::error_code
, any Expected<T>
to be converted to an ErrorOr<T>
, and vice
versa:
std::error_code errorToErrorCode(Error Err);
Error errorCodeToError(std::error_code EC);
template <typename T> ErrorOr<T> expectedToErrorOr(Expected<T> TOrErr);
template <typename T> Expected<T> errorOrToExpected(ErrorOr<T> TOrEC);
Using these APIs it is easy to make surgical patches that update individual
functions from std::error_code
to Error
, and from ErrorOr<T>
to
Expected<T>
.
Error recovery attempts may themselves fail. For that reason, handleErrors
actually recognises three different forms of handler signature:
// Error must be handled, no new errors produced:
void(UserDefinedError &E);
// Error must be handled, new errors can be produced:
Error(UserDefinedError &E);
// Original error can be inspected, then re-wrapped and returned (or a new
// error can be produced):
Error(std::unique_ptr<UserDefinedError> E);
Any error returned from a handler will be returned from the handleErrors
function so that it can be handled itself, or propagated up the stack.
Library code should never call exit
for a recoverable error, however in tool
code (especially command line tools) this can be a reasonable approach. Calling
exit
upon encountering an error dramatically simplifies control flow as the
error no longer needs to be propagated up the stack. This allows code to be
written in straight-line style, as long as each fallible call is wrapped in a
check and call to exit. The ExitOnError
class supports this pattern by
providing call operators that inspect Error
values, stripping the error away
in the success case and logging to stderr
then exiting in the failure case.
To use this class, declare a global ExitOnError
variable in your program:
ExitOnError ExitOnErr;
Calls to fallible functions can then be wrapped with a call to ExitOnErr
,
turning them into non-failing calls:
Error mayFail();
Expected<int> mayFail2();
void foo() {
ExitOnErr(mayFail());
int X = ExitOnErr(mayFail2());
}
On failure, the error's log message will be written to stderr
, optionally
preceded by a string "banner" that can be set by calling the setBanner method. A
mapping can also be supplied from Error
values to exit codes using the
setExitCodeMapper
method:
int main(int argc, char *argv[]) {
ExitOnErr.setBanner(std::string(argv[0]) + " error:");
ExitOnErr.setExitCodeMapper(
[](const Error &Err) {
if (Err.isA<BadFileFormat>())
return 2;
return 1;
});
Use ExitOnError
in your tool code where possible as it can greatly improve
readability.
Some functions may only fail for a subset of their inputs, so calls using known safe inputs can be assumed to succeed.
The cantFail functions encapsulate this by wrapping an assertion that their argument is a success value and, in the case of Expected<T>, unwrapping the T value:
Error onlyFailsForSomeXValues(int X);
Expected<int> onlyFailsForSomeXValues2(int X);
void foo() {
cantFail(onlyFailsForSomeXValues(KnownSafeValue));
int Y = cantFail(onlyFailsForSomeXValues2(KnownSafeValue));
...
}
Like the ExitOnError utility, cantFail simplifies control flow. Their treatment of error cases is very different however: Where ExitOnError is guaranteed to terminate the program on an error input, cantFile simply asserts that the result is success. In debug builds this will result in an assertion failure if an error is encountered. In release builds the behavior of cantFail for failure values is undefined. As such, care must be taken in the use of cantFail: clients must be certain that a cantFail wrapped call really can not fail with the given arguments.
Use of the cantFail functions should be rare in library code, but they are likely to be of more use in tool and unit-test code where inputs and/or mocked-up classes or functions may be known to be safe.
Some classes require resource acquisition or other complex initialization that
can fail during construction. Unfortunately constructors can't return errors,
and having clients test objects after they're constructed to ensure that they're
valid is error prone as it's all too easy to forget the test. To work around
this, use the named constructor idiom and return an Expected<T>
:
class Foo {
public:
static Expected<Foo> Create(Resource R1, Resource R2) {
Error Err;
Foo F(R1, R2, Err);
if (Err)
return std::move(Err);
return std::move(F);
}
private:
Foo(Resource R1, Resource R2, Error &Err) {
ErrorAsOutParameter EAO(&Err);
if (auto Err2 = R1.acquire()) {
Err = std::move(Err2);
return;
}
Err = R2.acquire();
}
};
Here, the named constructor passes an Error
by reference into the actual
constructor, which the constructor can then use to return errors. The
ErrorAsOutParameter
utility sets the Error
value's checked flag on entry
to the constructor so that the error can be assigned to, then resets it on exit
to force the client (the named constructor) to check the error.
By using this idiom, clients attempting to construct a Foo receive either a well-formed Foo or an Error, never an object in an invalid state.
In some contexts, certain types of error are known to be benign. For example,
when walking an archive, some clients may be happy to skip over badly formatted
object files rather than terminating the walk immediately. Skipping badly
formatted objects could be achieved using an elaborate handler method, but the
Error.h header provides two utilities that make this idiom much cleaner: the
type inspection method, isA
, and the consumeError
function:
Error walkArchive(Archive A) {
for (unsigned I = 0; I != A.numMembers(); ++I) {
auto ChildOrErr = A.getMember(I);
if (auto Err = ChildOrErr.takeError()) {
if (Err.isA<BadFileFormat>())
consumeError(std::move(Err))
else
return Err;
}
auto &Child = *ChildOrErr;
// Use Child
...
}
return Error::success();
}
In the archive walking example above BadFileFormat
errors are simply
consumed and ignored. If the client had wanted report these errors after
completing the walk over the archive they could use the joinErrors
utility:
Error walkArchive(Archive A) {
Error DeferredErrs = Error::success();
for (unsigned I = 0; I != A.numMembers(); ++I) {
auto ChildOrErr = A.getMember(I);
if (auto Err = ChildOrErr.takeError())
if (Err.isA<BadFileFormat>())
DeferredErrs = joinErrors(std::move(DeferredErrs), std::move(Err));
else
return Err;
auto &Child = *ChildOrErr;
// Use Child
...
}
return DeferredErrs;
}
The joinErrors
routine builds a special error type called ErrorList
,
which holds a list of user defined errors. The handleErrors
routine
recognizes this type and will attempt to handle each of the contained errors in
order. If all contained errors can be handled, handleErrors
will return
Error::success()
, otherwise handleErrors
will concatenate the remaining
errors and return the resulting ErrorList
.
The archive walking examples above retrieve archive members by index, however
this requires considerable boiler-plate for iteration and error checking. We can
clean this up by using Error
with the "fallible iterator" pattern. The usual
C++ iterator patterns do not allow for failure on increment, but we can
incorporate support for it by having iterators hold an Error reference through
which they can report failure. In this pattern, if an increment operation fails
the failure is recorded via the Error reference and the iterator value is set to
the end of the range in order to terminate the loop. This ensures that the
dereference operation is safe anywhere that an ordinary iterator dereference
would be safe (i.e. when the iterator is not equal to end). Where this pattern
is followed (as in the llvm::object::Archive
class) the result is much
cleaner iteration idiom:
Error Err;
for (auto &Child : Ar->children(Err)) {
// Use Child - we only enter the loop when it's valid
...
}
// Check Err after the loop to ensure it didn't break due to an error.
if (Err)
return Err;
More information on Error and its related utilities can be found in the Error.h header file.
Sometimes you may want a function to be passed a callback object. In order to support lambda expressions and other function objects, you should not use the traditional C approach of taking a function pointer and an opaque cookie:
void takeCallback(bool (*Callback)(Function *, void *), void *Cookie);
Instead, use one of the following approaches:
If you don't mind putting the definition of your function into a header file, make it a function template that is templated on the callable type.
template<typename Callable>
void takeCallback(Callable Callback) {
Callback(1, 2, 3);
}
The function_ref
(doxygen) class
template represents a reference to a callable object, templated over the type
of the callable. This is a good choice for passing a callback to a function,
if you don't need to hold onto the callback after the function returns. In this
way, function_ref
is to std::function
as StringRef
is to
std::string
.
function_ref<Ret(Param1, Param2, ...)>
can be implicitly constructed from
any callable object that can be called with arguments of type Param1
,
Param2
, ..., and returns a value that can be converted to type Ret
.
For example:
void visitBasicBlocks(Function *F, function_ref<bool (BasicBlock*)> Callback) {
for (BasicBlock &BB : *F)
if (Callback(&BB))
return;
}
can be called using:
visitBasicBlocks(F, [&](BasicBlock *BB) {
if (process(BB))
return isEmpty(BB);
return false;
});
Note that a function_ref
object contains pointers to external memory, so it
is not generally safe to store an instance of the class (unless you know that
the external storage will not be freed). If you need this ability, consider
using std::function
. function_ref
is small enough that it should always
be passed by value.
Often when working on your pass you will put a bunch of debugging printouts and other code into your pass. After you get it working, you want to remove it, but you may need it again in the future (to work out new bugs that you run across).
Naturally, because of this, you don't want to delete the debug printouts, but you don't want them to always be noisy. A standard compromise is to comment them out, allowing you to enable them if you need them in the future.
The llvm/Support/Debug.h
(doxygen) file provides a macro named
LLVM_DEBUG()
that is a much nicer solution to this problem. Basically, you can
put arbitrary code into the argument of the LLVM_DEBUG
macro, and it is only
executed if 'opt
' (or any other tool) is run with the '-debug
' command
line argument:
LLVM_DEBUG(dbgs() << "I am here!\n");
Then you can run your pass like this:
$ opt < a.bc > /dev/null -mypass
<no output>
$ opt < a.bc > /dev/null -mypass -debug
I am here!
Using the LLVM_DEBUG()
macro instead of a home-brewed solution allows you to not
have to create "yet another" command line option for the debug output for your
pass. Note that LLVM_DEBUG()
macros are disabled for non-asserts builds, so they
do not cause a performance impact at all (for the same reason, they should also
not contain side-effects!).
One additional nice thing about the LLVM_DEBUG()
macro is that you can enable or
disable it directly in gdb. Just use "set DebugFlag=0
" or "set
DebugFlag=1
" from the gdb if the program is running. If the program hasn't
been started yet, you can always just run it with -debug
.
Sometimes you may find yourself in a situation where enabling -debug
just
turns on too much information (such as when working on the code generator).
If you want to enable debug information with more fine-grained control, you
should define the DEBUG_TYPE
macro and use the -debug-only
option as
follows:
#define DEBUG_TYPE "foo"
LLVM_DEBUG(dbgs() << "'foo' debug type\n");
#undef DEBUG_TYPE
#define DEBUG_TYPE "bar"
LLVM_DEBUG(dbgs() << "'bar' debug type\n");
#undef DEBUG_TYPE
Then you can run your pass like this:
$ opt < a.bc > /dev/null -mypass
<no output>
$ opt < a.bc > /dev/null -mypass -debug
'foo' debug type
'bar' debug type
$ opt < a.bc > /dev/null -mypass -debug-only=foo
'foo' debug type
$ opt < a.bc > /dev/null -mypass -debug-only=bar
'bar' debug type
$ opt < a.bc > /dev/null -mypass -debug-only=foo,bar
'foo' debug type
'bar' debug type
Of course, in practice, you should only set DEBUG_TYPE
at the top of a file,
to specify the debug type for the entire module. Be careful that you only do
this after including Debug.h and not around any #include of headers. Also, you
should use names more meaningful than "foo" and "bar", because there is no
system in place to ensure that names do not conflict. If two different modules
use the same string, they will all be turned on when the name is specified.
This allows, for example, all debug information for instruction scheduling to be
enabled with -debug-only=InstrSched
, even if the source lives in multiple
files. The name must not include a comma (,) as that is used to separate the
arguments of the -debug-only
option.
For performance reasons, -debug-only is not available in optimized build
(--enable-optimized
) of LLVM.
The DEBUG_WITH_TYPE
macro is also available for situations where you would
like to set DEBUG_TYPE
, but only for one specific DEBUG
statement. It
takes an additional first parameter, which is the type to use. For example, the
preceding example could be written as:
DEBUG_WITH_TYPE("foo", dbgs() << "'foo' debug type\n");
DEBUG_WITH_TYPE("bar", dbgs() << "'bar' debug type\n");
The llvm/ADT/Statistic.h
(doxygen) file provides a class
named Statistic
that is used as a unified way to keep track of what the LLVM
compiler is doing and how effective various optimizations are. It is useful to
see what optimizations are contributing to making a particular program run
faster.
Often you may run your pass on some big program, and you're interested to see
how many times it makes a certain transformation. Although you can do this with
hand inspection, or some ad-hoc method, this is a real pain and not very useful
for big programs. Using the Statistic
class makes it very easy to keep
track of this information, and the calculated information is presented in a
uniform manner with the rest of the passes being executed.
There are many examples of Statistic
uses, but the basics of using it are as
follows:
Define your statistic like this:
#define DEBUG_TYPE "mypassname" // This goes before any #includes.
STATISTIC(NumXForms, "The # of times I did stuff");
The STATISTIC
macro defines a static variable, whose name is specified by
the first argument. The pass name is taken from the DEBUG_TYPE
macro, and
the description is taken from the second argument. The variable defined
("NumXForms" in this case) acts like an unsigned integer.
Whenever you make a transformation, bump the counter:
++NumXForms; // I did stuff!
That's all you have to do. To get 'opt
' to print out the statistics
gathered, use the '-stats
' option:
$ opt -stats -mypassname < program.bc > /dev/null
... statistics output ...
Note that in order to use the '-stats
' option, LLVM must be
compiled with assertions enabled.
When running opt
on a C file from the SPEC benchmark suite, it gives a
report that looks like this:
7646 bitcodewriter - Number of normal instructions
725 bitcodewriter - Number of oversized instructions
129996 bitcodewriter - Number of bitcode bytes written
2817 raise - Number of insts DCEd or constprop'd
3213 raise - Number of cast-of-self removed
5046 raise - Number of expression trees converted
75 raise - Number of other getelementptr's formed
138 raise - Number of load/store peepholes
42 deadtypeelim - Number of unused typenames removed from symtab
392 funcresolve - Number of varargs functions resolved
27 globaldce - Number of global variables removed
2 adce - Number of basic blocks removed
134 cee - Number of branches revectored
49 cee - Number of setcc instruction eliminated
532 gcse - Number of loads removed
2919 gcse - Number of instructions removed
86 indvars - Number of canonical indvars added
87 indvars - Number of aux indvars removed
25 instcombine - Number of dead inst eliminate
434 instcombine - Number of insts combined
248 licm - Number of load insts hoisted
1298 licm - Number of insts hoisted to a loop pre-header
3 licm - Number of insts hoisted to multiple loop preds (bad, no loop pre-header)
75 mem2reg - Number of alloca's promoted
1444 cfgsimplify - Number of blocks simplified
Obviously, with so many optimizations, having a unified framework for this stuff is very nice. Making your pass fit well into the framework makes it more maintainable and useful.
Sometimes, when writing new passes, or trying to track down bugs, it is useful to be able to control whether certain things in your pass happen or not. For example, there are times the minimization tooling can only easily give you large testcases. You would like to narrow your bug down to a specific transformation happening or not happening, automatically, using bisection. This is where debug counters help. They provide a framework for making parts of your code only execute a certain number of times.
The llvm/Support/DebugCounter.h
(doxygen) file
provides a class named DebugCounter
that can be used to create
command line counter options that control execution of parts of your code.
Define your DebugCounter like this:
DEBUG_COUNTER(DeleteAnInstruction, "passname-delete-instruction",
"Controls which instructions get delete");
The DEBUG_COUNTER
macro defines a static variable, whose name
is specified by the first argument. The name of the counter
(which is used on the command line) is specified by the second
argument, and the description used in the help is specified by the
third argument.
Whatever code you want that control, use DebugCounter::shouldExecute
to control it.
if (DebugCounter::shouldExecute(DeleteAnInstruction))
I->eraseFromParent();
That's all you have to do. Now, using opt, you can control when this code triggers using
the '--debug-counter
' option. There are two counters provided, skip
and count
.
skip
is the number of times to skip execution of the codepath. count
is the number
of times, once we are done skipping, to execute the codepath.
$ opt --debug-counter=passname-delete-instruction-skip=1,passname-delete-instruction-count=2 -passname
This will skip the above code the first time we hit it, then execute it twice, then skip the rest of the executions.
So if executed on the following code:
%1 = add i32 %a, %b
%2 = add i32 %a, %b
%3 = add i32 %a, %b
%4 = add i32 %a, %b
It would delete number %2
and %3
.
A utility is provided in utils/bisect-skip-count to binary search skip and count arguments. It can be used to automatically minimize the skip and count for a debug-counter variable.
Several of the important data structures in LLVM are graphs: for example CFGs made out of LLVM :ref:`BasicBlocks <BasicBlock>`, CFGs made out of LLVM :ref:`MachineBasicBlocks <MachineBasicBlock>`, and :ref:`Instruction Selection DAGs <SelectionDAG>`. In many cases, while debugging various parts of the compiler, it is nice to instantly visualize these graphs.
LLVM provides several callbacks that are available in a debug build to do
exactly that. If you call the Function::viewCFG()
method, for example, the
current LLVM tool will pop up a window containing the CFG for the function where
each basic block is a node in the graph, and each node contains the instructions
in the block. Similarly, there also exists Function::viewCFGOnly()
(does
not include the instructions), the MachineFunction::viewCFG()
and
MachineFunction::viewCFGOnly()
, and the SelectionDAG::viewGraph()
methods. Within GDB, for example, you can usually use something like call
DAG.viewGraph()
to pop up a window. Alternatively, you can sprinkle calls to
these functions in your code in places you want to debug.
Getting this to work requires a small amount of setup. On Unix systems
with X11, install the graphviz toolkit, and make
sure 'dot' and 'gv' are in your path. If you are running on Mac OS X, download
and install the Mac OS X Graphviz program and add
/Applications/Graphviz.app/Contents/MacOS/
(or wherever you install it) to
your path. The programs need not be present when configuring, building or
running LLVM and can simply be installed when needed during an active debug
session.
SelectionDAG
has been extended to make it easier to locate interesting
nodes in large complex graphs. From gdb, if you call DAG.setGraphColor(node,
"color")
, then the next call DAG.viewGraph()
would highlight the node in
the specified color (choices of colors can be found at colors.) More complex node attributes
can be provided with call DAG.setGraphAttrs(node, "attributes")
(choices can
be found at Graph attributes.)
If you want to restart and clear all the current graph attributes, then you can
call DAG.clearGraphAttrs()
.
Note that graph visualization features are compiled out of Release builds to reduce file size. This means that you need a Debug+Asserts or Release+Asserts build to use these features.
LLVM has a plethora of data structures in the llvm/ADT/
directory, and we
commonly use STL data structures. This section describes the trade-offs you
should consider when you pick one.
The first step is a choose your own adventure: do you want a sequential container, a set-like container, or a map-like container? The most important thing when choosing a container is the algorithmic properties of how you plan to access the container. Based on that, you should use:
- a :ref:`map-like <ds_map>` container if you need efficient look-up of a value based on another value. Map-like containers also support efficient queries for containment (whether a key is in the map). Map-like containers generally do not support efficient reverse mapping (values to keys). If you need that, use two maps. Some map-like containers also support efficient iteration through the keys in sorted order. Map-like containers are the most expensive sort, only use them if you need one of these capabilities.
- a :ref:`set-like <ds_set>` container if you need to put a bunch of stuff into a container that automatically eliminates duplicates. Some set-like containers support efficient iteration through the elements in sorted order. Set-like containers are more expensive than sequential containers.
- a :ref:`sequential <ds_sequential>` container provides the most efficient way to add elements and keeps track of the order they are added to the collection. They permit duplicates and support efficient iteration, but do not support efficient look-up based on a key.
- a :ref:`string <ds_string>` container is a specialized sequential container or reference structure that is used for character or byte arrays.
- a :ref:`bit <ds_bit>` container provides an efficient way to store and perform set operations on sets of numeric id's, while automatically eliminating duplicates. Bit containers require a maximum of 1 bit for each identifier you want to store.
Once the proper category of container is determined, you can fine tune the memory use, constant factors, and cache behaviors of access by intelligently picking a member of the category. Note that constant factors and cache behavior can be a big deal. If you have a vector that usually only contains a few elements (but could contain many), for example, it's much better to use :ref:`SmallVector <dss_smallvector>` than :ref:`vector <dss_vector>`. Doing so avoids (relatively) expensive malloc/free calls, which dwarf the cost of adding the elements to the container.
There are a variety of sequential containers available for you, based on your needs. Pick the first in this section that will do what you want.
The llvm::ArrayRef
class is the preferred class to use in an interface that
accepts a sequential list of elements in memory and just reads from them. By
taking an ArrayRef
, the API can be passed a fixed size array, an
std::vector
, an llvm::SmallVector
and anything else that is contiguous
in memory.
Fixed size arrays are very simple and very fast. They are good if you know exactly how many elements you have, or you have a (low) upper bound on how many you have.
Heap allocated arrays (new[]
+ delete[]
) are also simple. They are good
if the number of elements is variable, if you know how many elements you will
need before the array is allocated, and if the array is usually large (if not,
consider a :ref:`SmallVector <dss_smallvector>`). The cost of a heap allocated
array is the cost of the new/delete (aka malloc/free). Also note that if you
are allocating an array of a type with a constructor, the constructor and
destructors will be run for every element in the array (re-sizable vectors only
construct those elements actually used).
TinyPtrVector<Type>
is a highly specialized collection class that is
optimized to avoid allocation in the case when a vector has zero or one
elements. It has two major restrictions: 1) it can only hold values of pointer
type, and 2) it cannot hold a null pointer.
Since this container is highly specialized, it is rarely used.
SmallVector<Type, N>
is a simple class that looks and smells just like
vector<Type>
: it supports efficient iteration, lays out elements in memory
order (so you can do pointer arithmetic between elements), supports efficient
push_back/pop_back operations, supports efficient random access to its elements,
etc.
The main advantage of SmallVector is that it allocates space for some number of elements (N) in the object itself. Because of this, if the SmallVector is dynamically smaller than N, no malloc is performed. This can be a big win in cases where the malloc/free call is far more expensive than the code that fiddles around with the elements.
This is good for vectors that are "usually small" (e.g. the number of predecessors/successors of a block is usually less than 8). On the other hand, this makes the size of the SmallVector itself large, so you don't want to allocate lots of them (doing so will waste a lot of space). As such, SmallVectors are most useful when on the stack.
SmallVector also provides a nice portable and efficient replacement for
alloca
.
SmallVector has grown a few other minor advantages over std::vector, causing
SmallVector<Type, 0>
to be preferred over std::vector<Type>
.
- std::vector is exception-safe, and some implementations have pessimizations that copy elements when SmallVector would move them.
- SmallVector understands
isPodLike<Type>
and uses realloc aggressively. - Many LLVM APIs take a SmallVectorImpl as an out parameter (see the note below).
- SmallVector with N equal to 0 is smaller than std::vector on 64-bit
platforms, since it uses
unsigned
(instead ofvoid*
) for its size and capacity.
Note
Prefer to use SmallVectorImpl<T>
as a parameter type.
In APIs that don't care about the "small size" (most?), prefer to use
the SmallVectorImpl<T>
class, which is basically just the "vector
header" (and methods) without the elements allocated after it. Note that
SmallVector<T, N>
inherits from SmallVectorImpl<T>
so the
conversion is implicit and costs nothing. E.g.
// BAD: Clients cannot pass e.g. SmallVector<Foo, 4>.
hardcodedSmallSize(SmallVector<Foo, 2> &Out);
// GOOD: Clients can pass any SmallVector<Foo, N>.
allowsAnySmallSize(SmallVectorImpl<Foo> &Out);
void someFunc() {
SmallVector<Foo, 8> Vec;
hardcodedSmallSize(Vec); // Error.
allowsAnySmallSize(Vec); // Works.
}
Even though it has "Impl
" in the name, this is so widely used that
it really isn't "private to the implementation" anymore. A name like
SmallVectorHeader
would be more appropriate.
std::vector<T>
is well loved and respected. However, SmallVector<T, 0>
is often a better option due to the advantages listed above. std::vector is
still useful when you need to store more than UINT32_MAX
elements or when
interfacing with code that expects vectors :).
One worthwhile note about std::vector: avoid code like this:
for ( ... ) {
std::vector<foo> V;
// make use of V.
}
Instead, write this as:
std::vector<foo> V;
for ( ... ) {
// make use of V.
V.clear();
}
Doing so will save (at least) one heap allocation and free per iteration of the loop.
std::deque
is, in some senses, a generalized version of std::vector
.
Like std::vector
, it provides constant time random access and other similar
properties, but it also provides efficient access to the front of the list. It
does not guarantee continuity of elements within memory.
In exchange for this extra flexibility, std::deque
has significantly higher
constant factor costs than std::vector
. If possible, use std::vector
or
something cheaper.
std::list
is an extremely inefficient class that is rarely useful. It
performs a heap allocation for every element inserted into it, thus having an
extremely high constant factor, particularly for small data types.
std::list
also only supports bidirectional iteration, not random access
iteration.
In exchange for this high cost, std::list supports efficient access to both ends
of the list (like std::deque
, but unlike std::vector
or
SmallVector
). In addition, the iterator invalidation characteristics of
std::list are stronger than that of a vector class: inserting or removing an
element into the list does not invalidate iterator or pointers to other elements
in the list.
ilist<T>
implements an 'intrusive' doubly-linked list. It is intrusive,
because it requires the element to store and provide access to the prev/next
pointers for the list.
ilist
has the same drawbacks as std::list
, and additionally requires an
ilist_traits
implementation for the element type, but it provides some novel
characteristics. In particular, it can efficiently store polymorphic objects,
the traits class is informed when an element is inserted or removed from the
list, and ilist
s are guaranteed to support a constant-time splice
operation.
These properties are exactly what we want for things like Instruction
s and
basic blocks, which is why these are implemented with ilist
s.
Related classes of interest are explained in the following subsections:
- :ref:`ilist_traits <dss_ilist_traits>`
- :ref:`iplist <dss_iplist>`
- :ref:`llvm/ADT/ilist_node.h <dss_ilist_node>`
- :ref:`Sentinels <dss_ilist_sentinel>`
Useful for storing a vector of values using only a few number of bits for each value. Apart from the standard operations of a vector-like container, it can also perform an 'or' set operation.
For example:
enum State {
None = 0x0,
FirstCondition = 0x1,
SecondCondition = 0x2,
Both = 0x3
};
State get() {
PackedVector<State, 2> Vec1;
Vec1.push_back(FirstCondition);
PackedVector<State, 2> Vec2;
Vec2.push_back(SecondCondition);
Vec1 |= Vec2;
return Vec1[0]; // returns 'Both'.
}
ilist_traits<T>
is ilist<T>
's customization mechanism. iplist<T>
(and consequently ilist<T>
) publicly derive from this traits class.
iplist<T>
is ilist<T>
's base and as such supports a slightly narrower
interface. Notably, inserters from T&
are absent.
ilist_traits<T>
is a public base of this class and can be used for a wide
variety of customizations.
ilist_node<T>
implements the forward and backward links that are expected
by the ilist<T>
(and analogous containers) in the default manner.
ilist_node<T>
s are meant to be embedded in the node type T
, usually
T
publicly derives from ilist_node<T>
.
ilist
s have another specialty that must be considered. To be a good
citizen in the C++ ecosystem, it needs to support the standard container
operations, such as begin
and end
iterators, etc. Also, the
operator--
must work correctly on the end
iterator in the case of
non-empty ilist
s.
The only sensible solution to this problem is to allocate a so-called sentinel
along with the intrusive list, which serves as the end
iterator, providing
the back-link to the last element. However conforming to the C++ convention it
is illegal to operator++
beyond the sentinel and it also must not be
dereferenced.
These constraints allow for some implementation freedom to the ilist
how to
allocate and store the sentinel. The corresponding policy is dictated by
ilist_traits<T>
. By default a T
gets heap-allocated whenever the need
for a sentinel arises.
While the default policy is sufficient in most cases, it may break down when
T
does not provide a default constructor. Also, in the case of many
instances of ilist
s, the memory overhead of the associated sentinels is
wasted. To alleviate the situation with numerous and voluminous
T
-sentinels, sometimes a trick is employed, leading to ghostly sentinels.
Ghostly sentinels are obtained by specially-crafted ilist_traits<T>
which
superpose the sentinel with the ilist
instance in memory. Pointer
arithmetic is used to obtain the sentinel, which is relative to the ilist
's
this
pointer. The ilist
is augmented by an extra pointer, which serves
as the back-link of the sentinel. This is the only field in the ghostly
sentinel which can be legally accessed.
Other STL containers are available, such as std::string
.
There are also various STL adapter classes such as std::queue
,
std::priority_queue
, std::stack
, etc. These provide simplified access
to an underlying container but don't affect the cost of the container itself.
There are a variety of ways to pass around and use strings in C and C++, and LLVM adds a few new options to choose from. Pick the first option on this list that will do what you need, they are ordered according to their relative cost.
Note that it is generally preferred to not pass strings around as const
char*
's. These have a number of problems, including the fact that they
cannot represent embedded nul ("0") characters, and do not have a length
available efficiently. The general replacement for 'const char*
' is
StringRef.
For more information on choosing string containers for APIs, please see :ref:`Passing Strings <string_apis>`.
The StringRef class is a simple value class that contains a pointer to a character and a length, and is quite related to the :ref:`ArrayRef <dss_arrayref>` class (but specialized for arrays of characters). Because StringRef carries a length with it, it safely handles strings with embedded nul characters in it, getting the length does not require a strlen call, and it even has very convenient APIs for slicing and dicing the character range that it represents.
StringRef is ideal for passing simple strings around that are known to be live, either because they are C string literals, std::string, a C array, or a SmallVector. Each of these cases has an efficient implicit conversion to StringRef, which doesn't result in a dynamic strlen being executed.
StringRef has a few major limitations which make more powerful string containers useful:
- You cannot directly convert a StringRef to a 'const char*' because there is no way to add a trailing nul (unlike the .c_str() method on various stronger classes).
- StringRef doesn't own or keep alive the underlying string bytes. As such it can easily lead to dangling pointers, and is not suitable for embedding in datastructures in most cases (instead, use an std::string or something like that).
- For the same reason, StringRef cannot be used as the return value of a method if the method "computes" the result string. Instead, use std::string.
- StringRef's do not allow you to mutate the pointed-to string bytes and it doesn't allow you to insert or remove bytes from the range. For editing operations like this, it interoperates with the :ref:`Twine <dss_twine>` class.
Because of its strengths and limitations, it is very common for a function to take a StringRef and for a method on an object to return a StringRef that points into some string that it owns.
The Twine class is used as an intermediary datatype for APIs that want to take a string that can be constructed inline with a series of concatenations. Twine works by forming recursive instances of the Twine datatype (a simple value object) on the stack as temporary objects, linking them together into a tree which is then linearized when the Twine is consumed. Twine is only safe to use as the argument to a function, and should always be a const reference, e.g.:
void foo(const Twine &T);
...
StringRef X = ...
unsigned i = ...
foo(X + "." + Twine(i));
This example forms a string like "blarg.42" by concatenating the values together, and does not form intermediate strings containing "blarg" or "blarg.".
Because Twine is constructed with temporary objects on the stack, and because these instances are destroyed at the end of the current statement, it is an inherently dangerous API. For example, this simple variant contains undefined behavior and will probably crash:
void foo(const Twine &T);
...
StringRef X = ...
unsigned i = ...
const Twine &Tmp = X + "." + Twine(i);
foo(Tmp);
... because the temporaries are destroyed before the call. That said, Twine's are much more efficient than intermediate std::string temporaries, and they work really well with StringRef. Just be aware of their limitations.
SmallString is a subclass of :ref:`SmallVector <dss_smallvector>` that adds some convenience APIs like += that takes StringRef's. SmallString avoids allocating memory in the case when the preallocated space is enough to hold its data, and it calls back to general heap allocation when required. Since it owns its data, it is very safe to use and supports full mutation of the string.
Like SmallVector's, the big downside to SmallString is their sizeof. While they are optimized for small strings, they themselves are not particularly small. This means that they work great for temporary scratch buffers on the stack, but should not generally be put into the heap: it is very rare to see a SmallString as the member of a frequently-allocated heap data structure or returned by-value.
The standard C++ std::string class is a very general class that (like SmallString) owns its underlying data. sizeof(std::string) is very reasonable so it can be embedded into heap data structures and returned by-value. On the other hand, std::string is highly inefficient for inline editing (e.g. concatenating a bunch of stuff together) and because it is provided by the standard library, its performance characteristics depend a lot of the host standard library (e.g. libc++ and MSVC provide a highly optimized string class, GCC contains a really slow implementation).
The major disadvantage of std::string is that almost every operation that makes them larger can allocate memory, which is slow. As such, it is better to use SmallVector or Twine as a scratch buffer, but then use std::string to persist the result.
Set-like containers are useful when you need to canonicalize multiple values into a single representation. There are several different choices for how to do this, providing various trade-offs.
If you intend to insert a lot of elements, then do a lot of queries, a great approach is to use an std::vector (or other sequential container) with std::sort+std::unique to remove duplicates. This approach works really well if your usage pattern has these two distinct phases (insert then query), and can be coupled with a good choice of :ref:`sequential container <ds_sequential>`.
This combination provides the several nice properties: the result data is
contiguous in memory (good for cache locality), has few allocations, is easy to
address (iterators in the final vector are just indices or pointers), and can be
efficiently queried with a standard binary search (e.g.
std::lower_bound
; if you want the whole range of elements comparing
equal, use std::equal_range
).
If you have a set-like data structure that is usually small and whose elements
are reasonably small, a SmallSet<Type, N>
is a good choice. This set has
space for N elements in place (thus, if the set is dynamically smaller than N,
no malloc traffic is required) and accesses them with a simple linear search.
When the set grows beyond N elements, it allocates a more expensive
representation that guarantees efficient access (for most types, it falls back
to :ref:`std::set <dss_set>`, but for pointers it uses something far better,
:ref:`SmallPtrSet <dss_smallptrset>`.
The magic of this class is that it handles small sets extremely efficiently, but gracefully handles extremely large sets without loss of efficiency.
SmallPtrSet
has all the advantages of SmallSet
(and a SmallSet
of
pointers is transparently implemented with a SmallPtrSet
). If more than N
insertions are performed, a single quadratically probed hash table is allocated
and grows as needed, providing extremely efficient access (constant time
insertion/deleting/queries with low constant factors) and is very stingy with
malloc traffic.
Note that, unlike :ref:`std::set <dss_set>`, the iterators of SmallPtrSet
are invalidated whenever an insertion occurs. Also, the values visited by the
iterators are not visited in sorted order.
StringSet
is a thin wrapper around :ref:`StringMap\<char\> <dss_stringmap>`,
and it allows efficient storage and retrieval of unique strings.
Functionally analogous to SmallSet<StringRef>
, StringSet
also supports
iteration. (The iterator dereferences to a StringMapEntry<char>
, so you
need to call i->getKey()
to access the item of the StringSet.) On the
other hand, StringSet
doesn't support range-insertion and
copy-construction, which :ref:`SmallSet <dss_smallset>` and :ref:`SmallPtrSet
<dss_smallptrset>` do support.
DenseSet is a simple quadratically probed hash table. It excels at supporting small values: it uses a single allocation to hold all of the pairs that are currently inserted in the set. DenseSet is a great way to unique small values that are not simple pointers (use :ref:`SmallPtrSet <dss_smallptrset>` for pointers). Note that DenseSet has the same requirements for the value type that :ref:`DenseMap <dss_densemap>` has.
SparseSet holds a small number of objects identified by unsigned keys of moderate size. It uses a lot of memory, but provides operations that are almost as fast as a vector. Typical keys are physical registers, virtual registers, or numbered basic blocks.
SparseSet is useful for algorithms that need very fast clear/find/insert/erase and fast iteration over small sets. It is not intended for building composite data structures.
SparseMultiSet adds multiset behavior to SparseSet, while retaining SparseSet's desirable attributes. Like SparseSet, it typically uses a lot of memory, but provides operations that are almost as fast as a vector. Typical keys are physical registers, virtual registers, or numbered basic blocks.
SparseMultiSet is useful for algorithms that need very fast clear/find/insert/erase of the entire collection, and iteration over sets of elements sharing a key. It is often a more efficient choice than using composite data structures (e.g. vector-of-vectors, map-of-vectors). It is not intended for building composite data structures.
FoldingSet is an aggregate class that is really good at uniquing expensive-to-create or polymorphic objects. It is a combination of a chained hash table with intrusive links (uniqued objects are required to inherit from FoldingSetNode) that uses :ref:`SmallVector <dss_smallvector>` as part of its ID process.
Consider a case where you want to implement a "getOrCreateFoo" method for a complex object (for example, a node in the code generator). The client has a description of what it wants to generate (it knows the opcode and all the operands), but we don't want to 'new' a node, then try inserting it into a set only to find out it already exists, at which point we would have to delete it and return the node that already exists.
To support this style of client, FoldingSet perform a query with a FoldingSetNodeID (which wraps SmallVector) that can be used to describe the element that we want to query for. The query either returns the element matching the ID or it returns an opaque ID that indicates where insertion should take place. Construction of the ID usually does not require heap traffic.
Because FoldingSet uses intrusive links, it can support polymorphic objects in the set (for example, you can have SDNode instances mixed with LoadSDNodes). Because the elements are individually allocated, pointers to the elements are stable: inserting or removing elements does not invalidate any pointers to other elements.
std::set
is a reasonable all-around set class, which is decent at many
things but great at nothing. std::set allocates memory for each element
inserted (thus it is very malloc intensive) and typically stores three pointers
per element in the set (thus adding a large amount of per-element space
overhead). It offers guaranteed log(n) performance, which is not particularly
fast from a complexity standpoint (particularly if the elements of the set are
expensive to compare, like strings), and has extremely high constant factors for
lookup, insertion and removal.
The advantages of std::set are that its iterators are stable (deleting or inserting an element from the set does not affect iterators or pointers to other elements) and that iteration over the set is guaranteed to be in sorted order. If the elements in the set are large, then the relative overhead of the pointers and malloc traffic is not a big deal, but if the elements of the set are small, std::set is almost never a good choice.
LLVM's SetVector<Type>
is an adapter class that combines your choice of a
set-like container along with a :ref:`Sequential Container <ds_sequential>` The
important property that this provides is efficient insertion with uniquing
(duplicate elements are ignored) with iteration support. It implements this by
inserting elements into both a set-like container and the sequential container,
using the set-like container for uniquing and the sequential container for
iteration.
The difference between SetVector and other sets is that the order of iteration is guaranteed to match the order of insertion into the SetVector. This property is really important for things like sets of pointers. Because pointer values are non-deterministic (e.g. vary across runs of the program on different machines), iterating over the pointers in the set will not be in a well-defined order.
The drawback of SetVector is that it requires twice as much space as a normal set and has the sum of constant factors from the set-like container and the sequential container that it uses. Use it only if you need to iterate over the elements in a deterministic order. SetVector is also expensive to delete elements out of (linear time), unless you use its "pop_back" method, which is faster.
SetVector
is an adapter class that defaults to using std::vector
and a
size 16 SmallSet
for the underlying containers, so it is quite expensive.
However, "llvm/ADT/SetVector.h"
also provides a SmallSetVector
class,
which defaults to using a SmallVector
and SmallSet
of a specified size.
If you use this, and if your sets are dynamically smaller than N
, you will
save a lot of heap traffic.
UniqueVector is similar to :ref:`SetVector <dss_setvector>` but it retains a unique ID for each element inserted into the set. It internally contains a map and a vector, and it assigns a unique ID for each value inserted into the set.
UniqueVector is very expensive: its cost is the sum of the cost of maintaining both the map and vector, it has high complexity, high constant factors, and produces a lot of malloc traffic. It should be avoided.
ImmutableSet is an immutable (functional) set implementation based on an AVL tree. Adding or removing elements is done through a Factory object and results in the creation of a new ImmutableSet object. If an ImmutableSet already exists with the given contents, then the existing one is returned; equality is compared with a FoldingSetNodeID. The time and space complexity of add or remove operations is logarithmic in the size of the original set.
There is no method for returning an element of the set, you can only check for membership.
The STL provides several other options, such as std::multiset and the various "hash_set" like containers (whether from C++ TR1 or from the SGI library). We never use hash_set and unordered_set because they are generally very expensive (each insertion requires a malloc) and very non-portable.
std::multiset is useful if you're not interested in elimination of duplicates, but has all the drawbacks of :ref:`std::set <dss_set>`. A sorted vector (where you don't delete duplicate entries) or some other approach is almost always better.
Map-like containers are useful when you want to associate data to a key. As usual, there are a lot of different ways to do this. :)
If your usage pattern follows a strict insert-then-query approach, you can trivially use the same approach as :ref:`sorted vectors for set-like containers <dss_sortedvectorset>`. The only difference is that your query function (which uses std::lower_bound to get efficient log(n) lookup) should only compare the key, not both the key and value. This yields the same advantages as sorted vectors for sets.
Strings are commonly used as keys in maps, and they are difficult to support efficiently: they are variable length, inefficient to hash and compare when long, expensive to copy, etc. StringMap is a specialized container designed to cope with these issues. It supports mapping an arbitrary range of bytes to an arbitrary other object.
The StringMap implementation uses a quadratically-probed hash table, where the
buckets store a pointer to the heap allocated entries (and some other stuff).
The entries in the map must be heap allocated because the strings are variable
length. The string data (key) and the element object (value) are stored in the
same allocation with the string data immediately after the element object.
This container guarantees the "(char*)(&Value+1)
" points to the key string
for a value.
The StringMap is very fast for several reasons: quadratic probing is very cache efficient for lookups, the hash value of strings in buckets is not recomputed when looking up an element, StringMap rarely has to touch the memory for unrelated objects when looking up a value (even when hash collisions happen), hash table growth does not recompute the hash values for strings already in the table, and each pair in the map is store in a single allocation (the string data is stored in the same allocation as the Value of a pair).
StringMap also provides query methods that take byte ranges, so it only ever copies a string if a value is inserted into the table.
StringMap iteration order, however, is not guaranteed to be deterministic, so any uses which require that should instead use a std::map.
IndexedMap is a specialized container for mapping small dense integers (or values that can be mapped to small dense integers) to some other type. It is internally implemented as a vector with a mapping function that maps the keys to the dense integer range.
This is useful for cases like virtual registers in the LLVM code generator: they have a dense mapping that is offset by a compile-time constant (the first virtual register ID).
DenseMap is a simple quadratically probed hash table. It excels at supporting small keys and values: it uses a single allocation to hold all of the pairs that are currently inserted in the map. DenseMap is a great way to map pointers to pointers, or map other small types to each other.
There are several aspects of DenseMap that you should be aware of, however. The iterators in a DenseMap are invalidated whenever an insertion occurs, unlike map. Also, because DenseMap allocates space for a large number of key/value pairs (it starts with 64 by default), it will waste a lot of space if your keys or values are large. Finally, you must implement a partial specialization of DenseMapInfo for the key that you want, if it isn't already supported. This is required to tell DenseMap about two special marker values (which can never be inserted into the map) that it needs internally.
DenseMap's find_as() method supports lookup operations using an alternate key type. This is useful in cases where the normal key type is expensive to construct, but cheap to compare against. The DenseMapInfo is responsible for defining the appropriate comparison and hashing methods for each alternate key type used.
ValueMap is a wrapper around a :ref:`DenseMap <dss_densemap>` mapping
Value*
s (or subclasses) to another type. When a Value is deleted or
RAUW'ed, ValueMap will update itself so the new version of the key is mapped to
the same value, just as if the key were a WeakVH. You can configure exactly how
this happens, and what else happens on these two events, by passing a Config
parameter to the ValueMap template.
IntervalMap is a compact map for small keys and values. It maps key intervals instead of single keys, and it will automatically coalesce adjacent intervals. When the map only contains a few intervals, they are stored in the map object itself to avoid allocations.
The IntervalMap iterators are quite big, so they should not be passed around as STL iterators. The heavyweight iterators allow a smaller data structure.
std::map has similar characteristics to :ref:`std::set <dss_set>`: it uses a single allocation per pair inserted into the map, it offers log(n) lookup with an extremely large constant factor, imposes a space penalty of 3 pointers per pair in the map, etc.
std::map is most useful when your keys or values are very large, if you need to iterate over the collection in sorted order, or if you need stable iterators into the map (i.e. they don't get invalidated if an insertion or deletion of another element takes place).
MapVector<KeyT,ValueT>
provides a subset of the DenseMap interface. The
main difference is that the iteration order is guaranteed to be the insertion
order, making it an easy (but somewhat expensive) solution for non-deterministic
iteration over maps of pointers.
It is implemented by mapping from key to an index in a vector of key,value
pairs. This provides fast lookup and iteration, but has two main drawbacks:
the key is stored twice and removing elements takes linear time. If it is
necessary to remove elements, it's best to remove them in bulk using
remove_if()
.
IntEqClasses provides a compact representation of equivalence classes of small integers. Initially, each integer in the range 0..n-1 has its own equivalence class. Classes can be joined by passing two class representatives to the join(a, b) method. Two integers are in the same class when findLeader() returns the same representative.
Once all equivalence classes are formed, the map can be compressed so each integer 0..n-1 maps to an equivalence class number in the range 0..m-1, where m is the total number of equivalence classes. The map must be uncompressed before it can be edited again.
ImmutableMap is an immutable (functional) map implementation based on an AVL tree. Adding or removing elements is done through a Factory object and results in the creation of a new ImmutableMap object. If an ImmutableMap already exists with the given key set, then the existing one is returned; equality is compared with a FoldingSetNodeID. The time and space complexity of add or remove operations is logarithmic in the size of the original map.
The STL provides several other options, such as std::multimap and the various "hash_map" like containers (whether from C++ TR1 or from the SGI library). We never use hash_set and unordered_set because they are generally very expensive (each insertion requires a malloc) and very non-portable.
std::multimap is useful if you want to map a key to multiple values, but has all the drawbacks of std::map. A sorted vector or some other approach is almost always better.
Unlike the other containers, there are only two bit storage containers, and choosing when to use each is relatively straightforward.
One additional option is std::vector<bool>
: we discourage its use for two
reasons 1) the implementation in many common compilers (e.g. commonly
available versions of GCC) is extremely inefficient and 2) the C++ standards
committee is likely to deprecate this container and/or change it significantly
somehow. In any case, please don't use it.
The BitVector container provides a dynamic size set of bits for manipulation. It supports individual bit setting/testing, as well as set operations. The set operations take time O(size of bitvector), but operations are performed one word at a time, instead of one bit at a time. This makes the BitVector very fast for set operations compared to other containers. Use the BitVector when you expect the number of set bits to be high (i.e. a dense set).
The SmallBitVector container provides the same interface as BitVector, but it is optimized for the case where only a small number of bits, less than 25 or so, are needed. It also transparently supports larger bit counts, but slightly less efficiently than a plain BitVector, so SmallBitVector should only be used when larger counts are rare.
At this time, SmallBitVector does not support set operations (and, or, xor), and its operator[] does not provide an assignable lvalue.
The SparseBitVector container is much like BitVector, with one major difference: Only the bits that are set, are stored. This makes the SparseBitVector much more space efficient than BitVector when the set is sparse, as well as making set operations O(number of set bits) instead of O(size of universe). The downside to the SparseBitVector is that setting and testing of random bits is O(N), and on large SparseBitVectors, this can be slower than BitVector. In our implementation, setting or testing bits in sorted order (either forwards or reverse) is O(1) worst case. Testing and setting bits within 128 bits (depends on size) of the current bit is also O(1). As a general statement, testing/setting bits in a SparseBitVector is O(distance away from last set bit).
A handful of GDB pretty printers are
provided for some of the core LLVM libraries. To use them, execute the
following (or add it to your ~/.gdbinit
):
source /path/to/llvm/src/utils/gdb-scripts/prettyprinters.py
It also might be handy to enable the print pretty option to avoid data structures being printed as a big block of text.
This section describes how to perform some very simple transformations of LLVM code. This is meant to give examples of common idioms used, showing the practical side of LLVM transformations.
Because this is a "how-to" section, you should also read about the main classes that you will be working with. The :ref:`Core LLVM Class Hierarchy Reference <coreclasses>` contains details and descriptions of the main classes that you should know about.
The LLVM compiler infrastructure have many different data structures that may be
traversed. Following the example of the C++ standard template library, the
techniques used to traverse these various data structures are all basically the
same. For a enumerable sequence of values, the XXXbegin()
function (or
method) returns an iterator to the start of the sequence, the XXXend()
function returns an iterator pointing to one past the last valid element of the
sequence, and there is some XXXiterator
data type that is common between the
two operations.
Because the pattern for iteration is common across many different aspects of the program representation, the standard template library algorithms may be used on them, and it is easier to remember how to iterate. First we show a few common examples of the data structures that need to be traversed. Other data structures are traversed in very similar ways.
It's quite common to have a Function
instance that you'd like to transform
in some way; in particular, you'd like to manipulate its BasicBlock
s. To
facilitate this, you'll need to iterate over all of the BasicBlock
s that
constitute the Function
. The following is an example that prints the name
of a BasicBlock
and the number of Instruction
s it contains:
Function &Func = ...
for (BasicBlock &BB : Func)
// Print out the name of the basic block if it has one, and then the
// number of instructions that it contains
errs() << "Basic block (name=" << BB.getName() << ") has "
<< BB.size() << " instructions.\n";
Just like when dealing with BasicBlock
s in Function
s, it's easy to
iterate over the individual instructions that make up BasicBlock
s. Here's
a code snippet that prints out each instruction in a BasicBlock
:
BasicBlock& BB = ...
for (Instruction &I : BB)
// The next statement works since operator<<(ostream&,...)
// is overloaded for Instruction&
errs() << I << "\n";
However, this isn't really the best way to print out the contents of a
BasicBlock
! Since the ostream operators are overloaded for virtually
anything you'll care about, you could have just invoked the print routine on the
basic block itself: errs() << BB << "\n";
.
If you're finding that you commonly iterate over a Function
's
BasicBlock
s and then that BasicBlock
's Instruction
s,
InstIterator
should be used instead. You'll need to include
llvm/IR/InstIterator.h
(doxygen) and then instantiate
InstIterator
s explicitly in your code. Here's a small example that shows
how to dump all instructions in a function to the standard error stream:
#include "llvm/IR/InstIterator.h"
// F is a pointer to a Function instance
for (inst_iterator I = inst_begin(F), E = inst_end(F); I != E; ++I)
errs() << *I << "\n";
Easy, isn't it? You can also use InstIterator
s to fill a work list with
its initial contents. For example, if you wanted to initialize a work list to
contain all instructions in a Function
F, all you would need to do is
something like:
std::set<Instruction*> worklist;
// or better yet, SmallPtrSet<Instruction*, 64> worklist;
for (inst_iterator I = inst_begin(F), E = inst_end(F); I != E; ++I)
worklist.insert(&*I);
The STL set worklist
would now contain all instructions in the Function
pointed to by F.
Sometimes, it'll be useful to grab a reference (or pointer) to a class instance
when all you've got at hand is an iterator. Well, extracting a reference or a
pointer from an iterator is very straight-forward. Assuming that i
is a
BasicBlock::iterator
and j
is a BasicBlock::const_iterator
:
Instruction& inst = *i; // Grab reference to instruction reference
Instruction* pinst = &*i; // Grab pointer to instruction reference
const Instruction& inst = *j;
However, the iterators you'll be working with in the LLVM framework are special: they will automatically convert to a ptr-to-instance type whenever they need to. Instead of dereferencing the iterator and then taking the address of the result, you can simply assign the iterator to the proper pointer type and you get the dereference and address-of operation as a result of the assignment (behind the scenes, this is a result of overloading casting mechanisms). Thus the second line of the last example,
Instruction *pinst = &*i;
is semantically equivalent to
Instruction *pinst = i;
It's also possible to turn a class pointer into the corresponding iterator, and this is a constant time operation (very efficient). The following code snippet illustrates use of the conversion constructors provided by LLVM iterators. By using these, you can explicitly grab the iterator of something without actually obtaining it via iteration over some structure:
void printNextInstruction(Instruction* inst) {
BasicBlock::iterator it(inst);
++it; // After this line, it refers to the instruction after *inst
if (it != inst->getParent()->end()) errs() << *it << "\n";
}
Unfortunately, these implicit conversions come at a cost; they prevent these
iterators from conforming to standard iterator conventions, and thus from being
usable with standard algorithms and containers. For example, they prevent the
following code, where B
is a BasicBlock
, from compiling:
llvm::SmallVector<llvm::Instruction *, 16>(B->begin(), B->end());
Because of this, these implicit conversions may be removed some day, and
operator*
changed to return a pointer instead of a reference.
Say that you're writing a FunctionPass and would like to count all the locations
in the entire module (that is, across every Function
) where a certain
function (i.e., some Function *
) is already in scope. As you'll learn
later, you may want to use an InstVisitor
to accomplish this in a much more
straight-forward manner, but this example will allow us to explore how you'd do
it if you didn't have InstVisitor
around. In pseudo-code, this is what we
want to do:
initialize callCounter to zero
for each Function f in the Module
for each BasicBlock b in f
for each Instruction i in b
if (i is a CallInst and calls the given function)
increment callCounter
And the actual code is (remember, because we're writing a FunctionPass
, our
FunctionPass
-derived class simply has to override the runOnFunction
method):
Function* targetFunc = ...;
class OurFunctionPass : public FunctionPass {
public:
OurFunctionPass(): callCounter(0) { }
virtual runOnFunction(Function& F) {
for (BasicBlock &B : F) {
for (Instruction &I: B) {
if (auto *CallInst = dyn_cast<CallInst>(&I)) {
// We know we've encountered a call instruction, so we
// need to determine if it's a call to the
// function pointed to by m_func or not.
if (CallInst->getCalledFunction() == targetFunc)
++callCounter;
}
}
}
}
private:
unsigned callCounter;
};
You may have noticed that the previous example was a bit oversimplified in that
it did not deal with call sites generated by 'invoke' instructions. In this,
and in other situations, you may find that you want to treat CallInst
s and
InvokeInst
s the same way, even though their most-specific common base
class is Instruction
, which includes lots of less closely-related things.
For these cases, LLVM provides a handy wrapper class called CallSite
(doxygen) It is
essentially a wrapper around an Instruction
pointer, with some methods that
provide functionality common to CallInst
s and InvokeInst
s.
This class has "value semantics": it should be passed by value, not by reference
and it should not be dynamically allocated or deallocated using operator new
or operator delete
. It is efficiently copyable, assignable and
constructable, with costs equivalents to that of a bare pointer. If you look at
its definition, it has only a single pointer member.
Frequently, we might have an instance of the Value
class (doxygen) and we want to determine
which User
s use the Value
. The list of all User
s of a particular
Value
is called a def-use chain. For example, let's say we have a
Function*
named F
to a particular function foo
. Finding all of the
instructions that use foo
is as simple as iterating over the def-use
chain of F
:
Function *F = ...;
for (User *U : F->users()) {
if (Instruction *Inst = dyn_cast<Instruction>(U)) {
errs() << "F is used in instruction:\n";
errs() << *Inst << "\n";
}
Alternatively, it's common to have an instance of the User
Class (doxygen) and need to know what
Value
s are used by it. The list of all Value
s used by a User
is
known as a use-def chain. Instances of class Instruction
are common
User
s, so we might want to iterate over all of the values that a particular
instruction uses (that is, the operands of the particular Instruction
):
Instruction *pi = ...;
for (Use &U : pi->operands()) {
Value *v = U.get();
// ...
}
Declaring objects as const
is an important tool of enforcing mutation free
algorithms (such as analyses, etc.). For this purpose above iterators come in
constant flavors as Value::const_use_iterator
and
Value::const_op_iterator
. They automatically arise when calling
use/op_begin()
on const Value*
s or const User*
s respectively.
Upon dereferencing, they return const Use*
s. Otherwise the above patterns
remain unchanged.
Iterating over the predecessors and successors of a block is quite easy with the
routines defined in "llvm/IR/CFG.h"
. Just use code like this to
iterate over all predecessors of BB:
#include "llvm/IR/CFG.h"
BasicBlock *BB = ...;
for (BasicBlock *Pred : predecessors(BB)) {
// ...
}
Similarly, to iterate over successors use successors
.
There are some primitive transformation operations present in the LLVM infrastructure that are worth knowing about. When performing transformations, it's fairly common to manipulate the contents of basic blocks. This section describes some of the common methods for doing so and gives example code.
Instantiating Instructions
Creation of Instruction
s is straight-forward: simply call the constructor
for the kind of instruction to instantiate and provide the necessary parameters.
For example, an AllocaInst
only requires a (const-ptr-to) Type
. Thus:
auto *ai = new AllocaInst(Type::Int32Ty);
will create an AllocaInst
instance that represents the allocation of one
integer in the current stack frame, at run time. Each Instruction
subclass
is likely to have varying default parameters which change the semantics of the
instruction, so refer to the doxygen documentation for the subclass of
Instruction that
you're interested in instantiating.
Naming values
It is very useful to name the values of instructions when you're able to, as
this facilitates the debugging of your transformations. If you end up looking
at generated LLVM machine code, you definitely want to have logical names
associated with the results of instructions! By supplying a value for the
Name
(default) parameter of the Instruction
constructor, you associate a
logical name with the result of the instruction's execution at run time. For
example, say that I'm writing a transformation that dynamically allocates space
for an integer on the stack, and that integer is going to be used as some kind
of index by some other code. To accomplish this, I place an AllocaInst
at
the first point in the first BasicBlock
of some Function
, and I'm
intending to use it within the same Function
. I might do:
auto *pa = new AllocaInst(Type::Int32Ty, 0, "indexLoc");
where indexLoc
is now the logical name of the instruction's execution value,
which is a pointer to an integer on the run time stack.
Inserting instructions
There are essentially three ways to insert an Instruction
into an existing
sequence of instructions that form a BasicBlock
:
Insertion into an explicit instruction list
Given a
BasicBlock* pb
, anInstruction* pi
within thatBasicBlock
, and a newly-created instruction we wish to insert before*pi
, we do the following:BasicBlock *pb = ...; Instruction *pi = ...; auto *newInst = new Instruction(...); pb->getInstList().insert(pi, newInst); // Inserts newInst before pi in pb
Appending to the end of a
BasicBlock
is so common that theInstruction
class andInstruction
-derived classes provide constructors which take a pointer to aBasicBlock
to be appended to. For example code that looked like:BasicBlock *pb = ...; auto *newInst = new Instruction(...); pb->getInstList().push_back(newInst); // Appends newInst to pb
becomes:
BasicBlock *pb = ...; auto *newInst = new Instruction(..., pb);
which is much cleaner, especially if you are creating long instruction streams.
Insertion into an implicit instruction list
Instruction
instances that are already inBasicBlock
s are implicitly associated with an existing instruction list: the instruction list of the enclosing basic block. Thus, we could have accomplished the same thing as the above code without being given aBasicBlock
by doing:Instruction *pi = ...; auto *newInst = new Instruction(...); pi->getParent()->getInstList().insert(pi, newInst);
In fact, this sequence of steps occurs so frequently that the
Instruction
class andInstruction
-derived classes provide constructors which take (as a default parameter) a pointer to anInstruction
which the newly-createdInstruction
should precede. That is,Instruction
constructors are capable of inserting the newly-created instance into theBasicBlock
of a provided instruction, immediately before that instruction. Using anInstruction
constructor with ainsertBefore
(default) parameter, the above code becomes:Instruction* pi = ...; auto *newInst = new Instruction(..., pi);
which is much cleaner, especially if you're creating a lot of instructions and adding them to
BasicBlock
s.Insertion using an instance of
IRBuilder
Inserting several
Instruction
s can be quite laborious using the previous methods. TheIRBuilder
is a convenience class that can be used to add several instructions to the end of aBasicBlock
or before a particularInstruction
. It also supports constant folding and renaming named registers (seeIRBuilder
's template arguments).The example below demonstrates a very simple use of the
IRBuilder
where three instructions are inserted before the instructionpi
. The first two instructions are Call instructions and third instruction multiplies the return value of the two calls.Instruction *pi = ...; IRBuilder<> Builder(pi); CallInst* callOne = Builder.CreateCall(...); CallInst* callTwo = Builder.CreateCall(...); Value* result = Builder.CreateMul(callOne, callTwo);
The example below is similar to the above example except that the created
IRBuilder
inserts instructions at the end of theBasicBlock
pb
.BasicBlock *pb = ...; IRBuilder<> Builder(pb); CallInst* callOne = Builder.CreateCall(...); CallInst* callTwo = Builder.CreateCall(...); Value* result = Builder.CreateMul(callOne, callTwo);
See :doc:`tutorial/LangImpl03` for a practical use of the
IRBuilder
.
Deleting an instruction from an existing sequence of instructions that form a
BasicBlock is very straight-forward: just call the instruction's
eraseFromParent()
method. For example:
Instruction *I = .. ;
I->eraseFromParent();
This unlinks the instruction from its containing basic block and deletes it. If
you'd just like to unlink the instruction from its containing basic block but
not delete it, you can use the removeFromParent()
method.
Including "llvm/Transforms/Utils/BasicBlockUtils.h" permits use of two
very useful replace functions: ReplaceInstWithValue
and
ReplaceInstWithInst
.
ReplaceInstWithValue
This function replaces all uses of a given instruction with a value, and then removes the original instruction. The following example illustrates the replacement of the result of a particular
AllocaInst
that allocates memory for a single integer with a null pointer to an integer.AllocaInst* instToReplace = ...; BasicBlock::iterator ii(instToReplace); ReplaceInstWithValue(instToReplace->getParent()->getInstList(), ii, Constant::getNullValue(PointerType::getUnqual(Type::Int32Ty)));
ReplaceInstWithInst
This function replaces a particular instruction with another instruction, inserting the new instruction into the basic block at the location where the old instruction was, and replacing any uses of the old instruction with the new instruction. The following example illustrates the replacement of one
AllocaInst
with another.AllocaInst* instToReplace = ...; BasicBlock::iterator ii(instToReplace); ReplaceInstWithInst(instToReplace->getParent()->getInstList(), ii, new AllocaInst(Type::Int32Ty, 0, "ptrToReplacedInt"));
You can use Value::replaceAllUsesWith
and User::replaceUsesOfWith
to
change more than one use at a time. See the doxygen documentation for the
Value Class and User Class, respectively, for more
information.
Deleting a global variable from a module is just as easy as deleting an Instruction. First, you must have a pointer to the global variable that you wish to delete. You use this pointer to erase it from its parent, the module. For example:
GlobalVariable *GV = .. ;
GV->eraseFromParent();
This section describes the interaction of the LLVM APIs with multithreading, both on the part of client applications, and in the JIT, in the hosted application.
Note that LLVM's support for multithreading is still relatively young. Up through version 2.5, the execution of threaded hosted applications was supported, but not threaded client access to the APIs. While this use case is now supported, clients must adhere to the guidelines specified below to ensure proper operation in multithreaded mode.
Note that, on Unix-like platforms, LLVM requires the presence of GCC's atomic intrinsics in order to support threaded operation. If you need a multhreading-capable LLVM on a platform without a suitably modern system compiler, consider compiling LLVM and LLVM-GCC in single-threaded mode, and using the resultant compiler to build a copy of LLVM with multithreading support.
When you are done using the LLVM APIs, you should call llvm_shutdown()
to
deallocate memory used for internal structures.
ManagedStatic
is a utility class in LLVM used to implement static
initialization of static resources, such as the global type tables. In a
single-threaded environment, it implements a simple lazy initialization scheme.
When LLVM is compiled with support for multi-threading, however, it uses
double-checked locking to implement thread-safe lazy initialization.
LLVMContext
is an opaque class in the LLVM API which clients can use to
operate multiple, isolated instances of LLVM concurrently within the same
address space. For instance, in a hypothetical compile-server, the compilation
of an individual translation unit is conceptually independent from all the
others, and it would be desirable to be able to compile incoming translation
units concurrently on independent server threads. Fortunately, LLVMContext
exists to enable just this kind of scenario!
Conceptually, LLVMContext
provides isolation. Every LLVM entity
(Module
s, Value
s, Type
s, Constant
s, etc.) in LLVM's
in-memory IR belongs to an LLVMContext
. Entities in different contexts
cannot interact with each other: Module
s in different contexts cannot be
linked together, Function
s cannot be added to Module
s in different
contexts, etc. What this means is that is safe to compile on multiple
threads simultaneously, as long as no two threads operate on entities within the
same context.
In practice, very few places in the API require the explicit specification of a
LLVMContext
, other than the Type
creation/lookup APIs. Because every
Type
carries a reference to its owning context, most other entities can
determine what context they belong to by looking at their own Type
. If you
are adding new entities to LLVM IR, please try to maintain this interface
design.
LLVM's "eager" JIT compiler is safe to use in threaded programs. Multiple
threads can call ExecutionEngine::getPointerToFunction()
or
ExecutionEngine::runFunction()
concurrently, and multiple threads can run
code output by the JIT concurrently. The user must still ensure that only one
thread accesses IR in a given LLVMContext
while another thread might be
modifying it. One way to do that is to always hold the JIT lock while accessing
IR outside the JIT (the JIT modifies the IR by adding CallbackVH
s).
Another way is to only call getPointerToFunction()
from the
LLVMContext
's thread.
When the JIT is configured to compile lazily (using
ExecutionEngine::DisableLazyCompilation(false)
), there is currently a race
condition in updating call sites
after a function is lazily-jitted. It's still possible to use the lazy JIT in a
threaded program if you ensure that only one thread at a time can call any
particular lazy stub and that the JIT lock guards any IR access, but we suggest
using only the eager JIT in threaded programs.
This section describes some of the advanced or obscure API's that most clients do not need to be aware of. These API's tend manage the inner workings of the LLVM system, and only need to be accessed in unusual circumstances.
The ValueSymbolTable
(doxygen) class provides
a symbol table that the :ref:`Function <c_Function>` and Module classes use for
naming value definitions. The symbol table can provide a name for any Value.
Note that the SymbolTable
class should not be directly accessed by most
clients. It should only be used when iteration over the symbol table names
themselves are required, which is very special purpose. Note that not all LLVM
Values have names, and those without names (i.e. they have an empty name) do
not exist in the symbol table.
Symbol tables support iteration over the values in the symbol table with
begin/end/iterator
and supports querying to see if a specific name is in the
symbol table (with lookup
). The ValueSymbolTable
class exposes no
public mutator methods, instead, simply call setName
on a value, which will
autoinsert it into the appropriate symbol table.
The User
(doxygen)
class provides a basis for expressing the ownership of User
towards other
Value instances. The
Use
(doxygen) helper
class is employed to do the bookkeeping and to facilitate O(1) addition and
removal.
A subclass of User
can choose between incorporating its Use
objects or
refer to them out-of-line by means of a pointer. A mixed variant (some Use
s inline others hung off) is impractical and breaks the invariant that the
Use
objects belonging to the same User
form a contiguous array.
We have 2 different layouts in the User
(sub)classes:
Layout a)
The
Use
object(s) are inside (resp. at fixed offset) of theUser
object and there are a fixed number of them.Layout b)
The
Use
object(s) are referenced by a pointer to an array from theUser
object and there may be a variable number of them.
As of v2.4 each layout still possesses a direct pointer to the start of the
array of Use
s. Though not mandatory for layout a), we stick to this
redundancy for the sake of simplicity. The User
object also stores the
number of Use
objects it has. (Theoretically this information can also be
calculated given the scheme presented below.)
Special forms of allocation operators (operator new
) enforce the following
memory layouts:
Layout a) is modelled by prepending the
User
object by theUse[]
array....---.---.---.---.-------... | P | P | P | P | User '''---'---'---'---'-------'''
Layout b) is modelled by pointing at the
Use[]
array..-------... | User '-------''' | v .---.---.---.---... | P | P | P | P | '---'---'---'---'''
(In the above figures 'P
' stands for the Use**
that is stored in
each Use
object in the member Use::Prev
)
Since the Use
objects are deprived of the direct (back)pointer to their
User
objects, there must be a fast and exact method to recover it. This is
accomplished by the following scheme:
A bit-encoding in the 2 LSBits (least significant bits) of the Use::Prev
allows to find the start of the User
object:
00
--- binary digit 001
--- binary digit 110
--- stop and calculate (s
)11
--- full stop (S
)
Given a Use*
, all we have to do is to walk till we get a stop and we either
have a User
immediately behind or we have to walk to the next stop picking
up digits and calculating the offset:
.---.---.---.---.---.---.---.---.---.---.---.---.---.---.---.---.----------------
| 1 | s | 1 | 0 | 1 | 0 | s | 1 | 1 | 0 | s | 1 | 1 | s | 1 | S | User (or User*)
'---'---'---'---'---'---'---'---'---'---'---'---'---'---'---'---'----------------
|+15 |+10 |+6 |+3 |+1
| | | | | __>
| | | | __________>
| | | ______________________>
| | ______________________________________>
| __________________________________________________________>
Only the significant number of bits need to be stored between the stops, so that
the worst case is 20 memory accesses when there are 1000 Use
objects
associated with a User
.
The following literate Haskell fragment demonstrates the concept:
> import Test.QuickCheck
>
> digits :: Int -> [Char] -> [Char]
> digits 0 acc = '0' : acc
> digits 1 acc = '1' : acc
> digits n acc = digits (n `div` 2) $ digits (n `mod` 2) acc
>
> dist :: Int -> [Char] -> [Char]
> dist 0 [] = ['S']
> dist 0 acc = acc
> dist 1 acc = let r = dist 0 acc in 's' : digits (length r) r
> dist n acc = dist (n - 1) $ dist 1 acc
>
> takeLast n ss = reverse $ take n $ reverse ss
>
> test = takeLast 40 $ dist 20 []
>
Printing <test> gives: "1s100000s11010s10100s1111s1010s110s11s1S"
The reverse algorithm computes the length of the string just by examining a certain prefix:
> pref :: [Char] -> Int
> pref "S" = 1
> pref ('s':'1':rest) = decode 2 1 rest
> pref (_:rest) = 1 + pref rest
>
> decode walk acc ('0':rest) = decode (walk + 1) (acc * 2) rest
> decode walk acc ('1':rest) = decode (walk + 1) (acc * 2 + 1) rest
> decode walk acc _ = walk + acc
>
Now, as expected, printing <pref test> gives 40
.
We can quickCheck this with following property:
> testcase = dist 2000 []
> testcaseLength = length testcase
>
> identityProp n = n > 0 && n <= testcaseLength ==> length arr == pref arr
> where arr = takeLast n testcase
>
As expected <quickCheck identityProp> gives:
*Main> quickCheck identityProp OK, passed 100 tests.
Let's be a bit more exhaustive:
>
> deepCheck p = check (defaultConfig { configMaxTest = 500 }) p
>
And here is the result of <deepCheck identityProp>:
*Main> deepCheck identityProp OK, passed 500 tests.
To maintain the invariant that the 2 LSBits of each Use**
in Use
never
change after being set up, setters of Use::Prev
must re-tag the new
Use**
on every modification. Accordingly getters must strip the tag bits.
For layout b) instead of the User
we find a pointer (User*
with LSBit
set). Following this pointer brings us to the User
. A portable trick
ensures that the first bytes of User
(if interpreted as a pointer) never has
the LSBit set. (Portability is relying on the fact that all known compilers
place the vptr
in the first word of the instances.)
There are two different design patterns that tend to result in the use of
virtual dispatch for methods in a type hierarchy in C++ programs. The first is
a genuine type hierarchy where different types in the hierarchy model
a specific subset of the functionality and semantics, and these types nest
strictly within each other. Good examples of this can be seen in the Value
or Type
type hierarchies.
A second is the desire to dispatch dynamically across a collection of polymorphic interface implementations. This latter use case can be modeled with virtual dispatch and inheritance by defining an abstract interface base class which all implementations derive from and override. However, this implementation strategy forces an "is-a" relationship to exist that is not actually meaningful. There is often not some nested hierarchy of useful generalizations which code might interact with and move up and down. Instead, there is a singular interface which is dispatched across a range of implementations.
The preferred implementation strategy for the second use case is that of
generic programming (sometimes called "compile-time duck typing" or "static
polymorphism"). For example, a template over some type parameter T
can be
instantiated across any particular implementation that conforms to the
interface or concept. A good example here is the highly generic properties of
any type which models a node in a directed graph. LLVM models these primarily
through templates and generic programming. Such templates include the
LoopInfoBase
and DominatorTreeBase
. When this type of polymorphism
truly needs dynamic dispatch you can generalize it using a technique
called concept-based polymorphism. This pattern emulates the interfaces and
behaviors of templates using a very limited form of virtual dispatch for type
erasure inside its implementation. You can find examples of this technique in
the PassManager.h
system, and there is a more detailed introduction to it
by Sean Parent in several of his talks and papers:
- Inheritance Is The Base Class of Evil - The GoingNative 2013 talk describing this technique, and probably the best place to start.
- Value Semantics and Concepts-based Polymorphism - The C++Now! 2012 talk describing this technique in more detail.
- Sean Parent's Papers and Presentations - A Github project full of links to slides, video, and sometimes code.
When deciding between creating a type hierarchy (with either tagged or virtual dispatch) and using templates or concepts-based polymorphism, consider whether there is some refinement of an abstract base class which is a semantically meaningful type on an interface boundary. If anything more refined than the root abstract interface is meaningless to talk about as a partial extension of the semantic model, then your use case likely fits better with polymorphism and you should avoid using virtual dispatch. However, there may be some exigent circumstances that require one technique or the other to be used.
If you do need to introduce a type hierarchy, we prefer to use explicitly closed type hierarchies with manual tagged dispatch and/or RTTI rather than the open inheritance model and virtual dispatch that is more common in C++ code. This is because LLVM rarely encourages library consumers to extend its core types, and leverages the closed and tag-dispatched nature of its hierarchies to generate significantly more efficient code. We have also found that a large amount of our usage of type hierarchies fits better with tag-based pattern matching rather than dynamic dispatch across a common interface. Within LLVM we have built custom helpers to facilitate this design. See this document's section on :ref:`isa and dyn_cast <isa>` and our :doc:`detailed document <HowToSetUpLLVMStyleRTTI>` which describes how you can implement this pattern for use with the LLVM helpers.
Checks and asserts that alter the LLVM C++ ABI are predicated on the preprocessor symbol LLVM_ENABLE_ABI_BREAKING_CHECKS -- LLVM libraries built with LLVM_ENABLE_ABI_BREAKING_CHECKS are not ABI compatible LLVM libraries built without it defined. By default, turning on assertions also turns on LLVM_ENABLE_ABI_BREAKING_CHECKS so a default +Asserts build is not ABI compatible with a default -Asserts build. Clients that want ABI compatibility between +Asserts and -Asserts builds should use the CMake or autoconf build systems to set LLVM_ENABLE_ABI_BREAKING_CHECKS independently of LLVM_ENABLE_ASSERTIONS.
#include "llvm/IR/Type.h"
header source: Type.h
doxygen info: Type Clases
The Core LLVM classes are the primary means of representing the program being
inspected or transformed. The core LLVM classes are defined in header files in
the include/llvm/IR
directory, and implemented in the lib/IR
directory. It's worth noting that, for historical reasons, this library is
called libLLVMCore.so
, not libLLVMIR.so
as you might expect.
Type
is a superclass of all type classes. Every Value
has a Type
.
Type
cannot be instantiated directly but only through its subclasses.
Certain primitive types (VoidType
, LabelType
, FloatType
and
DoubleType
) have hidden subclasses. They are hidden because they offer no
useful functionality beyond what the Type
class offers except to distinguish
themselves from other subclasses of Type
.
All other types are subclasses of DerivedType
. Types can be named, but this
is not a requirement. There exists exactly one instance of a given shape at any
one time. This allows type equality to be performed with address equality of
the Type Instance. That is, given two Type*
values, the types are identical
if the pointers are identical.
bool isIntegerTy() const
: Returns true for any integer type.bool isFloatingPointTy()
: Return true if this is one of the five floating point types.bool isSized()
: Return true if the type has known size. Things that don't have a size are abstract types, labels and void.
IntegerType
Subclass of DerivedType that represents integer types of any bit width. Any bit width between
IntegerType::MIN_INT_BITS
(1) andIntegerType::MAX_INT_BITS
(~8 million) can be represented.static const IntegerType* get(unsigned NumBits)
: get an integer type of a specific bit width.unsigned getBitWidth() const
: Get the bit width of an integer type.
SequentialType
This is subclassed by ArrayType and VectorType.
const Type * getElementType() const
: Returns the type of each of the elements in the sequential type.uint64_t getNumElements() const
: Returns the number of elements in the sequential type.
ArrayType
- This is a subclass of SequentialType and defines the interface for array types.
PointerType
- Subclass of Type for pointer types.
VectorType
- Subclass of SequentialType for vector types. A vector type is similar to an ArrayType but is distinguished because it is a first class type whereas ArrayType is not. Vector types are used for vector operations and are usually small vectors of an integer or floating point type.
StructType
- Subclass of DerivedTypes for struct types.
FunctionType
Subclass of DerivedTypes for function types.
bool isVarArg() const
: Returns true if it's a vararg function.const Type * getReturnType() const
: Returns the return type of the function.const Type * getParamType (unsigned i)
: Returns the type of the ith parameter.const unsigned getNumParams() const
: Returns the number of formal parameters.
#include "llvm/IR/Module.h"
header source: Module.h
doxygen info: Module Class
The Module
class represents the top level structure present in LLVM
programs. An LLVM module is effectively either a translation unit of the
original program or a combination of several translation units merged by the
linker. The Module
class keeps track of a list of :ref:`Function
<c_Function>`s, a list of GlobalVariables, and a SymbolTable.
Additionally, it contains a few helpful member functions that try to make common
operations easy.
Module::Module(std::string name = "")
Constructing a Module is easy. You can optionally provide a name for it (probably based on the name of the translation unit).
Module::iterator
- Typedef for function list iteratorModule::const_iterator
- Typedef for const_iterator.begin()
,end()
,size()
,empty()
These are forwarding methods that make it easy to access the contents of a
Module
object's :ref:`Function <c_Function>` list.Module::FunctionListType &getFunctionList()
Returns the list of :ref:`Function <c_Function>`s. This is necessary to use when you need to update the list or perform a complex action that doesn't have a forwarding method.
Module::global_iterator
- Typedef for global variable list iteratorModule::const_global_iterator
- Typedef for const_iterator.global_begin()
,global_end()
,global_size()
,global_empty()
These are forwarding methods that make it easy to access the contents of a
Module
object's GlobalVariable list.Module::GlobalListType &getGlobalList()
Returns the list of GlobalVariables. This is necessary to use when you need to update the list or perform a complex action that doesn't have a forwarding method.
SymbolTable *getSymbolTable()
Return a reference to the SymbolTable for this
Module
.
Function *getFunction(StringRef Name) const
Look up the specified function in the
Module
SymbolTable. If it does not exist, returnnull
.Function *getOrInsertFunction(const std::string &Name, const FunctionType *T)
Look up the specified function in the
Module
SymbolTable. If it does not exist, add an external declaration for the function and return it.std::string getTypeName(const Type *Ty)
If there is at least one entry in the SymbolTable for the specified Type, return it. Otherwise return the empty string.
bool addTypeName(const std::string &Name, const Type *Ty)
Insert an entry in the SymbolTable mapping
Name
toTy
. If there is already an entry for this name, true is returned and the SymbolTable is not modified.
#include "llvm/IR/Value.h"
header source: Value.h
doxygen info: Value Class
The Value
class is the most important class in the LLVM Source base. It
represents a typed value that may be used (among other things) as an operand to
an instruction. There are many different types of Value
s, such as
Constants, Arguments. Even Instructions and :ref:`Function
<c_Function>`s are Value
s.
A particular Value
may be used many times in the LLVM representation for a
program. For example, an incoming argument to a function (represented with an
instance of the Argument class) is "used" by every instruction in the function
that references the argument. To keep track of this relationship, the Value
class keeps a list of all of the User
s that is using it (the User class
is a base class for all nodes in the LLVM graph that can refer to Value
s).
This use list is how LLVM represents def-use information in the program, and is
accessible through the use_*
methods, shown below.
Because LLVM is a typed representation, every LLVM Value
is typed, and this
Type is available through the getType()
method. In addition, all LLVM
values can be named. The "name" of the Value
is a symbolic string printed
in the LLVM code:
%foo = add i32 1, 2
The name of this instruction is "foo". NOTE that the name of any value may
be missing (an empty string), so names should ONLY be used for debugging
(making the source code easier to read, debugging printouts), they should not be
used to keep track of values or map between them. For this purpose, use a
std::map
of pointers to the Value
itself instead.
One important aspect of LLVM is that there is no distinction between an SSA variable and the operation that produces it. Because of this, any reference to the value produced by an instruction (or the value available as an incoming argument, for example) is represented as a direct pointer to the instance of the class that represents this value. Although this may take some getting used to, it simplifies the representation and makes it easier to manipulate.
Value::use_iterator
- Typedef for iterator over the use-listValue::const_use_iterator
- Typedef for const_iterator over the use-listunsigned use_size()
- Returns the number of users of the value.bool use_empty()
- Returns true if there are no users.use_iterator use_begin()
- Get an iterator to the start of the use-list.use_iterator use_end()
- Get an iterator to the end of the use-list.User *use_back()
- Returns the last element in the list.These methods are the interface to access the def-use information in LLVM. As with all other iterators in LLVM, the naming conventions follow the conventions defined by the STL.
Type *getType() const
This method returns the Type of the Value.bool hasName() const
std::string getName() const
void setName(const std::string &Name)
This family of methods is used to access and assign a name to a
Value
, be aware of the :ref:`precaution above <nameWarning>`.void replaceAllUsesWith(Value *V)
This method traverses the use list of a
Value
changing all Users of the current value to refer to "V
" instead. For example, if you detect that an instruction always produces a constant value (for example through constant folding), you can replace all uses of the instruction with the constant like this:Inst->replaceAllUsesWith(ConstVal);
#include "llvm/IR/User.h"
header source: User.h
doxygen info: User Class
Superclass: Value
The User
class is the common base class of all LLVM nodes that may refer to
Value
s. It exposes a list of "Operands" that are all of the Value
s
that the User is referring to. The User
class itself is a subclass of
Value
.
The operands of a User
point directly to the LLVM Value
that it refers
to. Because LLVM uses Static Single Assignment (SSA) form, there can only be
one definition referred to, allowing this direct connection. This connection
provides the use-def information in LLVM.
The User
class exposes the operand list in two ways: through an index access
interface and through an iterator based interface.
Value *getOperand(unsigned i)
unsigned getNumOperands()
These two methods expose the operands of the
User
in a convenient form for direct access.User::op_iterator
- Typedef for iterator over the operand listop_iterator op_begin()
- Get an iterator to the start of the operand list.op_iterator op_end()
- Get an iterator to the end of the operand list.Together, these methods make up the iterator based interface to the operands of a
User
.
#include "llvm/IR/Instruction.h"
header source: Instruction.h
doxygen info: Instruction Class
The Instruction
class is the common base class for all LLVM instructions.
It provides only a few methods, but is a very commonly used class. The primary
data tracked by the Instruction
class itself is the opcode (instruction
type) and the parent BasicBlock the Instruction
is embedded into. To
represent a specific type of instruction, one of many subclasses of
Instruction
are used.
Because the Instruction
class subclasses the User class, its operands can
be accessed in the same way as for other User
s (with the
getOperand()
/getNumOperands()
and op_begin()
/op_end()
methods).
An important file for the Instruction
class is the llvm/Instruction.def
file. This file contains some meta-data about the various different types of
instructions in LLVM. It describes the enum values that are used as opcodes
(for example Instruction::Add
and Instruction::ICmp
), as well as the
concrete sub-classes of Instruction
that implement the instruction (for
example BinaryOperator and CmpInst). Unfortunately, the use of macros in this
file confuses doxygen, so these enum values don't show up correctly in the
doxygen output.
BinaryOperator
This subclasses represents all two operand instructions whose operands must be the same type, except for the comparison instructions.
CastInst
This subclass is the parent of the 12 casting instructions. It provides common operations on cast instructions.
CmpInst
This subclass represents the two comparison instructions, ICmpInst (integer opreands), and FCmpInst (floating point operands).
BasicBlock *getParent()
Returns the BasicBlock that this
Instruction
is embedded into.bool mayWriteToMemory()
Returns true if the instruction writes to memory, i.e. it is a
call
,free
,invoke
, orstore
.unsigned getOpcode()
Returns the opcode for the
Instruction
.Instruction *clone() const
Returns another instance of the specified instruction, identical in all ways to the original except that the instruction has no parent (i.e. it's not embedded into a BasicBlock), and it has no name.
Constant represents a base class for different types of constants. It is subclassed by ConstantInt, ConstantArray, etc. for representing the various types of Constants. GlobalValue is also a subclass, which represents the address of a global variable or function.
- ConstantInt : This subclass of Constant represents an integer constant of
any width.
const APInt& getValue() const
: Returns the underlying value of this constant, an APInt value.int64_t getSExtValue() const
: Converts the underlying APInt value to an int64_t via sign extension. If the value (not the bit width) of the APInt is too large to fit in an int64_t, an assertion will result. For this reason, use of this method is discouraged.uint64_t getZExtValue() const
: Converts the underlying APInt value to a uint64_t via zero extension. IF the value (not the bit width) of the APInt is too large to fit in a uint64_t, an assertion will result. For this reason, use of this method is discouraged.static ConstantInt* get(const APInt& Val)
: Returns the ConstantInt object that represents the value provided byVal
. The type is implied as the IntegerType that corresponds to the bit width ofVal
.static ConstantInt* get(const Type *Ty, uint64_t Val)
: Returns the ConstantInt object that represents the value provided byVal
for integer typeTy
.
- ConstantFP : This class represents a floating point constant.
double getValue() const
: Returns the underlying value of this constant.
- ConstantArray : This represents a constant array.
const std::vector<Use> &getValues() const
: Returns a vector of component constants that makeup this array.
- ConstantStruct : This represents a constant struct.
const std::vector<Use> &getValues() const
: Returns a vector of component constants that makeup this array.
- GlobalValue : This represents either a global variable or a function. In either case, the value is a constant fixed address (after linking).
#include "llvm/IR/GlobalValue.h"
header source: GlobalValue.h
doxygen info: GlobalValue Class
Superclasses: Constant, User, Value
Global values ( GlobalVariables or :ref:`Function <c_Function>`s) are the
only LLVM values that are visible in the bodies of all :ref:`Function
<c_Function>`s. Because they are visible at global scope, they are also
subject to linking with other globals defined in different translation units.
To control the linking process, GlobalValue
s know their linkage rules.
Specifically, GlobalValue
s know whether they have internal or external
linkage, as defined by the LinkageTypes
enumeration.
If a GlobalValue
has internal linkage (equivalent to being static
in C),
it is not visible to code outside the current translation unit, and does not
participate in linking. If it has external linkage, it is visible to external
code, and does participate in linking. In addition to linkage information,
GlobalValue
s keep track of which Module they are currently part of.
Because GlobalValue
s are memory objects, they are always referred to by
their address. As such, the Type of a global is always a pointer to its
contents. It is important to remember this when using the GetElementPtrInst
instruction because this pointer must be dereferenced first. For example, if
you have a GlobalVariable
(a subclass of GlobalValue)
that is an array
of 24 ints, type [24 x i32]
, then the GlobalVariable
is a pointer to
that array. Although the address of the first element of this array and the
value of the GlobalVariable
are the same, they have different types. The
GlobalVariable
's type is [24 x i32]
. The first element's type is
i32.
Because of this, accessing a global value requires you to dereference
the pointer with GetElementPtrInst
first, then its elements can be accessed.
This is explained in the LLVM Language Reference Manual.
bool hasInternalLinkage() const
bool hasExternalLinkage() const
void setInternalLinkage(bool HasInternalLinkage)
These methods manipulate the linkage characteristics of the
GlobalValue
.Module *getParent()
This returns the Module that the GlobalValue is currently embedded into.
#include "llvm/IR/Function.h"
header source: Function.h
doxygen info: Function Class
Superclasses: GlobalValue, Constant, User, Value
The Function
class represents a single procedure in LLVM. It is actually
one of the more complex classes in the LLVM hierarchy because it must keep track
of a large amount of data. The Function
class keeps track of a list of
BasicBlocks, a list of formal Arguments, and a SymbolTable.
The list of BasicBlocks is the most commonly used part of Function
objects. The list imposes an implicit ordering of the blocks in the function,
which indicate how the code will be laid out by the backend. Additionally, the
first BasicBlock is the implicit entry node for the Function
. It is not
legal in LLVM to explicitly branch to this initial block. There are no implicit
exit nodes, and in fact there may be multiple exit nodes from a single
Function
. If the BasicBlock list is empty, this indicates that the
Function
is actually a function declaration: the actual body of the function
hasn't been linked in yet.
In addition to a list of BasicBlocks, the Function
class also keeps track
of the list of formal Arguments that the function receives. This container
manages the lifetime of the Argument nodes, just like the BasicBlock list does
for the BasicBlocks.
The SymbolTable is a very rarely used LLVM feature that is only used when you have to look up a value by name. Aside from that, the SymbolTable is used internally to make sure that there are not conflicts between the names of Instructions, BasicBlocks, or Arguments in the function body.
Note that Function
is a GlobalValue and therefore also a Constant. The
value of the function is its address (after linking) which is guaranteed to be
constant.
Function(const FunctionType *Ty, LinkageTypes Linkage, const std::string &N = "", Module* Parent = 0)
Constructor used when you need to create new
Function
s to add the program. The constructor must specify the type of the function to create and what type of linkage the function should have. The FunctionType argument specifies the formal arguments and return value for the function. The same FunctionType value can be used to create multiple functions. TheParent
argument specifies the Module in which the function is defined. If this argument is provided, the function will automatically be inserted into that module's list of functions.bool isDeclaration()
Return whether or not the
Function
has a body defined. If the function is "external", it does not have a body, and thus must be resolved by linking with a function defined in a different translation unit.Function::iterator
- Typedef for basic block list iteratorFunction::const_iterator
- Typedef for const_iterator.begin()
,end()
,size()
,empty()
These are forwarding methods that make it easy to access the contents of a
Function
object's BasicBlock list.Function::BasicBlockListType &getBasicBlockList()
Returns the list of BasicBlocks. This is necessary to use when you need to update the list or perform a complex action that doesn't have a forwarding method.
Function::arg_iterator
- Typedef for the argument list iteratorFunction::const_arg_iterator
- Typedef for const_iterator.arg_begin()
,arg_end()
,arg_size()
,arg_empty()
These are forwarding methods that make it easy to access the contents of a
Function
object's Argument list.Function::ArgumentListType &getArgumentList()
Returns the list of Argument. This is necessary to use when you need to update the list or perform a complex action that doesn't have a forwarding method.
BasicBlock &getEntryBlock()
Returns the entry
BasicBlock
for the function. Because the entry block for the function is always the first block, this returns the first block of theFunction
.Type *getReturnType()
FunctionType *getFunctionType()
This traverses the Type of the
Function
and returns the return type of the function, or the FunctionType of the actual function.SymbolTable *getSymbolTable()
Return a pointer to the SymbolTable for this
Function
.
#include "llvm/IR/GlobalVariable.h"
header source: GlobalVariable.h
doxygen info: GlobalVariable Class
Superclasses: GlobalValue, Constant, User, Value
Global variables are represented with the (surprise surprise) GlobalVariable
class. Like functions, GlobalVariable
s are also subclasses of
GlobalValue, and as such are always referenced by their address (global values
must live in memory, so their "name" refers to their constant address). See
GlobalValue for more on this. Global variables may have an initial value
(which must be a Constant), and if they have an initializer, they may be marked
as "constant" themselves (indicating that their contents never change at
runtime).
GlobalVariable(const Type *Ty, bool isConstant, LinkageTypes &Linkage, Constant *Initializer = 0, const std::string &Name = "", Module* Parent = 0)
Create a new global variable of the specified type. If
isConstant
is true then the global variable will be marked as unchanging for the program. The Linkage parameter specifies the type of linkage (internal, external, weak, linkonce, appending) for the variable. If the linkage is InternalLinkage, WeakAnyLinkage, WeakODRLinkage, LinkOnceAnyLinkage or LinkOnceODRLinkage, then the resultant global variable will have internal linkage. AppendingLinkage concatenates together all instances (in different translation units) of the variable into a single variable but is only applicable to arrays. See the LLVM Language Reference for further details on linkage types. Optionally an initializer, a name, and the module to put the variable into may be specified for the global variable as well.bool isConstant() const
Returns true if this is a global variable that is known not to be modified at runtime.
bool hasInitializer()
Returns true if this
GlobalVariable
has an intializer.Constant *getInitializer()
Returns the initial value for a
GlobalVariable
. It is not legal to call this method if there is no initializer.
#include "llvm/IR/BasicBlock.h"
header source: BasicBlock.h
doxygen info: BasicBlock Class
Superclass: Value
This class represents a single entry single exit section of the code, commonly
known as a basic block by the compiler community. The BasicBlock
class
maintains a list of Instructions, which form the body of the block. Matching
the language definition, the last element of this list of instructions is always
a terminator instruction.
In addition to tracking the list of instructions that make up the block, the
BasicBlock
class also keeps track of the :ref:`Function <c_Function>` that
it is embedded into.
Note that BasicBlock
s themselves are Values, because they are
referenced by instructions like branches and can go in the switch tables.
BasicBlock
s have type label
.
BasicBlock(const std::string &Name = "", Function *Parent = 0)
The
BasicBlock
constructor is used to create new basic blocks for insertion into a function. The constructor optionally takes a name for the new block, and a :ref:`Function <c_Function>` to insert it into. If theParent
parameter is specified, the newBasicBlock
is automatically inserted at the end of the specified :ref:`Function <c_Function>`, if not specified, the BasicBlock must be manually inserted into the :ref:`Function <c_Function>`.BasicBlock::iterator
- Typedef for instruction list iteratorBasicBlock::const_iterator
- Typedef for const_iterator.begin()
,end()
,front()
,back()
,size()
,empty()
STL-style functions for accessing the instruction list.These methods and typedefs are forwarding functions that have the same semantics as the standard library methods of the same names. These methods expose the underlying instruction list of a basic block in a way that is easy to manipulate. To get the full complement of container operations (including operations to update the list), you must use the
getInstList()
method.BasicBlock::InstListType &getInstList()
This method is used to get access to the underlying container that actually holds the Instructions. This method must be used when there isn't a forwarding function in the
BasicBlock
class for the operation that you would like to perform. Because there are no forwarding functions for "updating" operations, you need to use this if you want to update the contents of aBasicBlock
.Function *getParent()
Returns a pointer to :ref:`Function <c_Function>` the block is embedded into, or a null pointer if it is homeless.
Instruction *getTerminator()
Returns a pointer to the terminator instruction that appears at the end of the
BasicBlock
. If there is no terminator instruction, or if the last instruction in the block is not a terminator, then a null pointer is returned.
This subclass of Value defines the interface for incoming formal arguments to a function. A Function maintains a list of its formal arguments. An argument has a pointer to the parent Function.