Writing an LLVM Pass¶

Introduction — What is a pass?
Quick Start — Writing hello world
Pass classes and requirements
Pass Statistics
- What PassManager does
  - The releaseMemory method
Registering dynamically loaded passes

Introduction — What is a pass?¶

The LLVM Pass Framework is an important part of the LLVM system, because LLVM passes are where most of the interesting parts of the compiler exist. Passes perform the transformations and optimizations that make up the compiler, they build the analysis results that are used by these transformations, and they are, above all, a structuring technique for compiler code.

All LLVM passes are subclasses of the Pass class, which implement functionality by overriding virtual methods inherited from Pass. Depending on how your pass works, you should inherit from the ModulePass , CallGraphSCCPass, FunctionPass , or LoopPass, or RegionPass, or BasicBlockPass classes, which gives the system more information about what your pass does, and how it can be combined with other passes. One of the main features of the LLVM Pass Framework is that it schedules passes to run in an efficient way based on the constraints that your pass meets (which are indicated by which class they derive from).

We start by showing you how to construct a pass, everything from setting up the code, to compiling, loading, and executing it. After the basics are down, more advanced features are discussed.

Quick Start — Writing hello world ¶

Here we describe how to write the “hello world” of passes. The “Hello” pass is designed to simply print out the name of non-external functions that exist in the program being compiled. It does not modify the program at all, it just inspects it. The source code and files for this pass are available in the LLVM source tree in the lib/Transforms/Hello directory.

Setting up the build environment ¶

First, configure and build LLVM. Next, you need to create a new directory somewhere in the LLVM source base. For this example, we’ll assume that you made lib/Transforms/Hello. Finally, you must set up a build script that will compile the source code for the new pass. To do this, copy the following into CMakeLists.txt:

add_llvm_library( LLVMHello MODULE
  Hello.cpp

  PLUGIN_TOOL
  opt
  )

and the following line into lib/Transforms/CMakeLists.txt:

add_subdirectory(Hello)

(Note that there is already a directory named Hello with a sample “Hello” pass; you may play with it – in which case you don’t need to modify any CMakeLists.txt files – or, if you want to create everything from scratch, use another name.)

This build script specifies that Hello.cpp file in the current directory is to be compiled and linked into a shared object $(LEVEL)/lib/LLVMHello.so that can be dynamically loaded by the opt tool via its -load option. If your operating system uses a suffix other than .so (such as Windows or macOS), the appropriate extension will be used.

Now that we have the build scripts set up, we just need to write the code for the pass itself.

Basic code required ¶

Now that we have a way to compile our new pass, we just have to write it. Start out with:

#include "llvm/Pass.h"
#include "llvm/IR/Function.h"
#include "llvm/Support/raw_ostream.h"

Which are needed because we are writing a Pass, we are operating on Functions, and we will be doing some printing.

Next we have:

using namespace llvm;

… which is required because the functions from the include files live in the llvm namespace.

Next we have:

namespace {

… which starts out an anonymous namespace. Anonymous namespaces are to C++ what the “static” keyword is to C (at global scope). It makes the things declared inside of the anonymous namespace visible only to the current file. If you’re not familiar with them, consult a decent C++ book for more information.

Next, we declare our pass itself:

struct Hello : public FunctionPass {

This declares a “Hello” class that is a subclass of FunctionPass. The different builtin pass subclasses are described in detail later, but for now, know that FunctionPass operates on a function at a time.

static char ID;
Hello() : FunctionPass(ID) {}

This declares pass identifier used by LLVM to identify pass. This allows LLVM to avoid using expensive C++ runtime information.

  bool runOnFunction(Function &F) override {
    errs() << "Hello: ";
    errs().write_escaped(F.getName()) << '\n';
    return false;
  }
}; // end of struct Hello
}  // end of anonymous namespace

We declare a runOnFunction method, which overrides an abstract virtual method inherited from FunctionPass. This is where we are supposed to do our thing, so we just print out our message with the name of each function.

char Hello::ID = 0;

We initialize pass ID here. LLVM uses ID’s address to identify a pass, so initialization value is not important.

static RegisterPass<Hello> X("hello", "Hello World Pass",
                             false /* Only looks at CFG */,
                             false /* Analysis Pass */);

Lastly, we register our class Hello, giving it a command line argument “hello”, and a name “Hello World Pass”. The last two arguments describe its behavior: if a pass walks CFG without modifying it then the third argument is set to true; if a pass is an analysis pass, for example dominator tree pass, then true is supplied as the fourth argument.

If we want to register the pass as a step of an existing pipeline, some extension points are provided, e.g. PassManagerBuilder::EP_EarlyAsPossible to apply our pass before any optimization, or PassManagerBuilder::EP_FullLinkTimeOptimizationLast to apply it after Link Time Optimizations.

static llvm::RegisterStandardPasses Y(
    llvm::PassManagerBuilder::EP_EarlyAsPossible,
    [](const llvm::PassManagerBuilder &Builder,
       llvm::legacy::PassManagerBase &PM) { PM.add(new Hello()); });

As a whole, the .cpp file looks like:

#include "llvm/Pass.h"
#include "llvm/IR/Function.h"
#include "llvm/Support/raw_ostream.h"

#include "llvm/IR/LegacyPassManager.h"
#include "llvm/Transforms/IPO/PassManagerBuilder.h"

using namespace llvm;

namespace {
struct Hello : public FunctionPass {
  static char ID;
  Hello() : FunctionPass(ID) {}

  bool runOnFunction(Function &F) override {
    errs() << "Hello: ";
    errs().write_escaped(F.getName()) << '\n';
    return false;
  }
}; // end of struct Hello
}  // end of anonymous namespace

char Hello::ID = 0;
static RegisterPass<Hello> X("hello", "Hello World Pass",
                             false /* Only looks at CFG */,
                             false /* Analysis Pass */);

static RegisterStandardPasses Y(
    PassManagerBuilder::EP_EarlyAsPossible,
    [](const PassManagerBuilder &Builder,
       legacy::PassManagerBase &PM) { PM.add(new Hello()); });

Now that it’s all together, compile the file with a simple “gmake” command from the top level of your build directory and you should get a new file “lib/LLVMHello.so”. Note that everything in this file is contained in an anonymous namespace — this reflects the fact that passes are self contained units that do not need external interfaces (although they can have them) to be useful.

Running a pass with `opt`¶

Now that you have a brand new shiny shared object file, we can use the opt command to run an LLVM program through your pass. Because you registered your pass with RegisterPass, you will be able to use the opt tool to access it, once loaded.

To test it, follow the example at the end of the Getting Started with the LLVM System to compile “Hello World” to LLVM. We can now run the bitcode file (hello.bc) for the program through our transformation like this (or course, any bitcode file will work):

$ opt -load lib/LLVMHello.so -hello < hello.bc > /dev/null
Hello: __main
Hello: puts
Hello: main

The -load option specifies that opt should load your pass as a shared object, which makes “-hello” a valid command line argument (which is one reason you need to register your pass). Because the Hello pass does not modify the program in any interesting way, we just throw away the result of opt (sending it to /dev/null).

To see what happened to the other string you registered, try running opt with the -help option:

$ opt -load lib/LLVMHello.so -help
OVERVIEW: llvm .bc -> .bc modular optimizer and analysis printer

USAGE: opt [subcommand] [options] <input bitcode file>

OPTIONS:
  Optimizations available:
...
    -guard-widening           - Widen guards
    -gvn                      - Global Value Numbering
    -gvn-hoist                - Early GVN Hoisting of Expressions
    -hello                    - Hello World Pass
    -indvars                  - Induction Variable Simplification
    -inferattrs               - Infer set function attributes
...

The pass name gets added as the information string for your pass, giving some documentation to users of opt. Now that you have a working pass, you would go ahead and make it do the cool transformations you want. Once you get it all working and tested, it may become useful to find out how fast your pass is. The PassManager provides a nice command line option (-time-passes) that allows you to get information about the execution time of your pass along with the other passes you queue up. For example:

$ opt -load lib/LLVMHello.so -hello -time-passes < hello.bc > /dev/null
Hello: __main
Hello: puts
Hello: main
===-------------------------------------------------------------------------===
                      ... Pass execution timing report ...
===-------------------------------------------------------------------------===
  Total Execution Time: 0.0007 seconds (0.0005 wall clock)

   ---User Time---   --User+System--   ---Wall Time---  --- Name ---
   0.0004 ( 55.3%)   0.0004 ( 55.3%)   0.0004 ( 75.7%)  Bitcode Writer
   0.0003 ( 44.7%)   0.0003 ( 44.7%)   0.0001 ( 13.6%)  Hello World Pass
   0.0000 (  0.0%)   0.0000 (  0.0%)   0.0001 ( 10.7%)  Module Verifier
   0.0007 (100.0%)   0.0007 (100.0%)   0.0005 (100.0%)  Total

As you can see, our implementation above is pretty fast. The additional passes listed are automatically inserted by the opt tool to verify that the LLVM emitted by your pass is still valid and well formed LLVM, which hasn’t been broken somehow.

Now that you have seen the basics of the mechanics behind passes, we can talk about some more details of how they work and how to use them.

Pass classes and requirements ¶

One of the first things that you should do when designing a new pass is to decide what class you should subclass for your pass. The Hello World example uses the FunctionPass class for its implementation, but we did not discuss why or when this should occur. Here we talk about the classes available, from the most general to the most specific.

When choosing a superclass for your Pass, you should choose the most specific class possible, while still being able to meet the requirements listed. This gives the LLVM Pass Infrastructure information necessary to optimize how passes are run, so that the resultant compiler isn’t unnecessarily slow.

The `ImmutablePass` class ¶

The most plain and boring type of pass is the “ImmutablePass” class. This pass type is used for passes that do not have to be run, do not change state, and never need to be updated. This is not a normal type of transformation or analysis, but can provide information about the current compiler configuration.

Although this pass class is very infrequently used, it is important for providing information about the current target machine being compiled for, and other static information that can affect the various transformations.

ImmutablePasses never invalidate other transformations, are never invalidated, and are never “run”.

The `ModulePass` class ¶

The ModulePass class is the most general of all superclasses that you can use. Deriving from ModulePass indicates that your pass uses the entire program as a unit, referring to function bodies in no predictable order, or adding and removing functions. Because nothing is known about the behavior of ModulePass subclasses, no optimization can be done for their execution.

A module pass can use function level passes (e.g. dominators) using the getAnalysis interface getAnalysis<DominatorTree>(llvm::Function *) to provide the function to retrieve analysis result for, if the function pass does not require any module or immutable passes. Note that this can only be done for functions for which the analysis ran, e.g. in the case of dominators you should only ask for the DominatorTree for function definitions, not declarations.

To write a correct ModulePass subclass, derive from ModulePass and overload the runOnModule method with the following signature:

The `runOnModule` method ¶

virtual bool runOnModule(Module &M) = 0;

The runOnModule method performs the interesting work of the pass. It should return true if the module was modified by the transformation and false otherwise.

The `CallGraphSCCPass` class ¶

The CallGraphSCCPass is used by passes that need to traverse the program bottom-up on the call graph (callees before callers). Deriving from CallGraphSCCPass provides some mechanics for building and traversing the CallGraph, but also allows the system to optimize execution of CallGraphSCCPasses. If your pass meets the requirements outlined below, and doesn’t meet the requirements of a FunctionPass or BasicBlockPass, you should derive from CallGraphSCCPass.

TODO: explain briefly what SCC, Tarjan’s algo, and B-U mean.

To be explicit, CallGraphSCCPass subclasses are:

… not allowed to inspect or modify any Functions other than those in the current SCC and the direct callers and direct callees of the SCC.
… required to preserve the current CallGraph object, updating it to reflect any changes made to the program.
… not allowed to add or remove SCC’s from the current Module, though they may change the contents of an SCC.
… allowed to add or remove global variables from the current Module.
… allowed to maintain state across invocations of runOnSCC (including global data).

Implementing a CallGraphSCCPass is slightly tricky in some cases because it has to handle SCCs with more than one node in it. All of the virtual methods described below should return true if they modified the program, or false if they didn’t.

The `doInitialization(CallGraph &)` method ¶

virtual bool doInitialization(CallGraph &CG);

The doInitialization method is allowed to do most of the things that CallGraphSCCPasses are not allowed to do. They can add and remove functions, get pointers to functions, etc. The doInitialization method is designed to do simple initialization type of stuff that does not depend on the SCCs being processed. The doInitialization method call is not scheduled to overlap with any other pass executions (thus it should be very fast).

The `runOnSCC` method ¶

virtual bool runOnSCC(CallGraphSCC &SCC) = 0;

The runOnSCC method performs the interesting work of the pass, and should return true if the module was modified by the transformation, false otherwise.

The `doFinalization(CallGraph &)` method ¶

virtual bool doFinalization(CallGraph &CG);

The doFinalization method is an infrequently used method that is called when the pass framework has finished calling runOnSCC for every SCC in the program being compiled.

The `FunctionPass` class ¶

In contrast to ModulePass subclasses, FunctionPass subclasses do have a predictable, local behavior that can be expected by the system. All FunctionPass execute on each function in the program independent of all of the other functions in the program. FunctionPasses do not require that they are executed in a particular order, and FunctionPasses do not modify external functions.

To be explicit, FunctionPass subclasses are not allowed to:

Inspect or modify a Function other than the one currently being processed.
Add or remove Functions from the current Module.
Add or remove global variables from the current Module.
Maintain state across invocations of runOnFunction (including global data).

Implementing a FunctionPass is usually straightforward (See the Hello World pass for example). FunctionPasses may overload three virtual methods to do their work. All of these methods should return true if they modified the program, or false if they didn’t.

The `doInitialization(Module &)` method ¶

virtual bool doInitialization(Module &M);

The doInitialization method is allowed to do most of the things that FunctionPasses are not allowed to do. They can add and remove functions, get pointers to functions, etc. The doInitialization method is designed to do simple initialization type of stuff that does not depend on the functions being processed. The doInitialization method call is not scheduled to overlap with any other pass executions (thus it should be very fast).

A good example of how this method should be used is the LowerAllocations pass. This pass converts malloc and free instructions into platform dependent malloc() and free() function calls. It uses the doInitialization method to get a reference to the malloc and free functions that it needs, adding prototypes to the module if necessary.

The `runOnFunction` method ¶

virtual bool runOnFunction(Function &F) = 0;

The runOnFunction method must be implemented by your subclass to do the transformation or analysis work of your pass. As usual, a true value should be returned if the function is modified.

The `doFinalization(Module &)` method ¶

virtual bool doFinalization(Module &M);

The doFinalization method is an infrequently used method that is called when the pass framework has finished calling runOnFunction for every function in the program being compiled.

The `LoopPass` class ¶

All LoopPass execute on each loop in the function independent of all of the other loops in the function. LoopPass processes loops in loop nest order such that outer most loop is processed last.

LoopPass subclasses are allowed to update loop nest using LPPassManager interface. Implementing a loop pass is usually straightforward. LoopPasses may overload three virtual methods to do their work. All these methods should return true if they modified the program, or false if they didn’t.

A LoopPass subclass which is intended to run as part of the main loop pass pipeline needs to preserve all of the same function analyses that the other loop passes in its pipeline require. To make that easier, a getLoopAnalysisUsage function is provided by LoopUtils.h. It can be called within the subclass’s getAnalysisUsage override to get consistent and correct behavior. Analogously, INITIALIZE_PASS_DEPENDENCY(LoopPass) will initialize this set of function analyses.

The `doInitialization(Loop *, LPPassManager &)` method ¶

virtual bool doInitialization(Loop *, LPPassManager &LPM);

The doInitialization method is designed to do simple initialization type of stuff that does not depend on the functions being processed. The doInitialization method call is not scheduled to overlap with any other pass executions (thus it should be very fast). LPPassManager interface should be used to access Function or Module level analysis information.

The `runOnLoop` method ¶

virtual bool runOnLoop(Loop *, LPPassManager &LPM) = 0;

The runOnLoop method must be implemented by your subclass to do the transformation or analysis work of your pass. As usual, a true value should be returned if the function is modified. LPPassManager interface should be used to update loop nest.

The `doFinalization()` method ¶

virtual bool doFinalization();

The doFinalization method is an infrequently used method that is called when the pass framework has finished calling runOnLoop for every loop in the program being compiled.

The `RegionPass` class ¶

RegionPass is similar to LoopPass, but executes on each single entry single exit region in the function. RegionPass processes regions in nested order such that the outer most region is processed last.

RegionPass subclasses are allowed to update the region tree by using the RGPassManager interface. You may overload three virtual methods of RegionPass to implement your own region pass. All these methods should return true if they modified the program, or false if they did not.

The `doInitialization(Region *, RGPassManager &)` method ¶

virtual bool doInitialization(Region *, RGPassManager &RGM);

The doInitialization method is designed to do simple initialization type of stuff that does not depend on the functions being processed. The doInitialization method call is not scheduled to overlap with any other pass executions (thus it should be very fast). RPPassManager interface should be used to access Function or Module level analysis information.

The `runOnRegion` method ¶

virtual bool runOnRegion(Region *, RGPassManager &RGM) = 0;

The runOnRegion method must be implemented by your subclass to do the transformation or analysis work of your pass. As usual, a true value should be returned if the region is modified. RGPassManager interface should be used to update region tree.

The `doFinalization()` method ¶

virtual bool doFinalization();

The doFinalization method is an infrequently used method that is called when the pass framework has finished calling runOnRegion for every region in the program being compiled.

The `BasicBlockPass` class ¶

BasicBlockPasses are just like FunctionPass’s , except that they must limit their scope of inspection and modification to a single basic block at a time. As such, they are not allowed to do any of the following:

Modify or inspect any basic blocks outside of the current one.
Maintain state across invocations of runOnBasicBlock.
Modify the control flow graph (by altering terminator instructions)
Any of the things forbidden for FunctionPasses.

BasicBlockPasses are useful for traditional local and “peephole” optimizations. They may override the same doInitialization(Module &) and doFinalization(Module &) methods that FunctionPass’s have, but also have the following virtual methods that may also be implemented:

The `doInitialization(Function &)` method ¶

virtual bool doInitialization(Function &F);

The doInitialization method is allowed to do most of the things that BasicBlockPasses are not allowed to do, but that FunctionPasses can. The doInitialization method is designed to do simple initialization that does not depend on the BasicBlocks being processed. The doInitialization method call is not scheduled to overlap with any other pass executions (thus it should be very fast).

The `runOnBasicBlock` method ¶

virtual bool runOnBasicBlock(BasicBlock &BB) = 0;

Override this function to do the work of the BasicBlockPass. This function is not allowed to inspect or modify basic blocks other than the parameter, and are not allowed to modify the CFG. A true value must be returned if the basic block is modified.

The `doFinalization(Function &)` method ¶

virtual bool doFinalization(Function &F);

The doFinalization method is an infrequently used method that is called when the pass framework has finished calling runOnBasicBlock for every BasicBlock in the program being compiled. This can be used to perform per-function finalization.

The `MachineFunctionPass` class ¶

A MachineFunctionPass is a part of the LLVM code generator that executes on the machine-dependent representation of each LLVM function in the program.

Code generator passes are registered and initialized specially by TargetMachine::addPassesToEmitFile and similar routines, so they cannot generally be run from the opt or bugpoint commands.

A MachineFunctionPass is also a FunctionPass, so all the restrictions that apply to a FunctionPass also apply to it. MachineFunctionPasses also have additional restrictions. In particular, MachineFunctionPasses are not allowed to do any of the following:

Modify or create any LLVM IR Instructions, BasicBlocks, Arguments, Functions, GlobalVariables, GlobalAliases, or Modules.
Modify a MachineFunction other than the one currently being processed.
Maintain state across invocations of runOnMachineFunction (including global data).

The `runOnMachineFunction(MachineFunction &MF)` method ¶

virtual bool runOnMachineFunction(MachineFunction &MF) = 0;

runOnMachineFunction can be considered the main entry point of a MachineFunctionPass; that is, you should override this method to do the work of your MachineFunctionPass.

The runOnMachineFunction method is called on every MachineFunction in a Module, so that the MachineFunctionPass may perform optimizations on the machine-dependent representation of the function. If you want to get at the LLVM Function for the MachineFunction you’re working on, use MachineFunction’s getFunction() accessor method — but remember, you may not modify the LLVM Function or its contents from a MachineFunctionPass.

Pass registration ¶

In the Hello World example pass we illustrated how pass registration works, and discussed some of the reasons that it is used and what it does. Here we discuss how and why passes are registered.

As we saw above, passes are registered with the RegisterPass template. The template parameter is the name of the pass that is to be used on the command line to specify that the pass should be added to a program (for example, with opt or bugpoint). The first argument is the name of the pass, which is to be used for the -help output of programs, as well as for debug output generated by the –debug-pass option.

If you want your pass to be easily dumpable, you should implement the virtual print method:

The `print` method ¶

virtual void print(llvm::raw_ostream &O, const Module *M) const;

The print method must be implemented by “analyses” in order to print a human readable version of the analysis results. This is useful for debugging an analysis itself, as well as for other people to figure out how an analysis works. Use the opt -analyze argument to invoke this method.

The llvm::raw_ostream parameter specifies the stream to write the results on, and the Module parameter gives a pointer to the top level module of the program that has been analyzed. Note however that this pointer may be NULL in certain circumstances (such as calling the Pass::dump() from a debugger), so it should only be used to enhance debug output, it should not be depended on.

Specifying interactions between passes ¶

One of the main responsibilities of the PassManager is to make sure that passes interact with each other correctly. Because PassManager tries to optimize the execution of passes it must know how the passes interact with each other and what dependencies exist between the various passes. To track this, each pass can declare the set of passes that are required to be executed before the current pass, and the passes which are invalidated by the current pass.

Typically this functionality is used to require that analysis results are computed before your pass is run. Running arbitrary transformation passes can invalidate the computed analysis results, which is what the invalidation set specifies. If a pass does not implement the getAnalysisUsage method, it defaults to not having any prerequisite passes, and invalidating all other passes.

The `getAnalysisUsage` method ¶

virtual void getAnalysisUsage(AnalysisUsage &Info) const;

By implementing the getAnalysisUsage method, the required and invalidated sets may be specified for your transformation. The implementation should fill in the AnalysisUsage object with information about which passes are required and not invalidated. To do this, a pass may call any of the following methods on the AnalysisUsage object:

The `AnalysisUsage::addRequired<>` and `AnalysisUsage::addRequiredTransitive<>` methods ¶

If your pass requires a previous pass to be executed (an analysis for example), it can use one of these methods to arrange for it to be run before your pass. LLVM has many different types of analyses and passes that can be required, spanning the range from DominatorSet to BreakCriticalEdges. Requiring BreakCriticalEdges, for example, guarantees that there will be no critical edges in the CFG when your pass has been run.

Some analyses chain to other analyses to do their job. For example, an AliasAnalysis <AliasAnalysis> implementation is required to chain to other alias analysis passes. In cases where analyses chain, the addRequiredTransitive method should be used instead of the addRequired method. This informs the PassManager that the transitively required pass should be alive as long as the requiring pass is.

The `AnalysisUsage::addPreserved<>` method ¶

One of the jobs of the PassManager is to optimize how and when analyses are run. In particular, it attempts to avoid recomputing data unless it needs to. For this reason, passes are allowed to declare that they preserve (i.e., they don’t invalidate) an existing analysis if it’s available. For example, a simple constant folding pass would not modify the CFG, so it can’t possibly affect the results of dominator analysis. By default, all passes are assumed to invalidate all others.

The AnalysisUsage class provides several methods which are useful in certain circumstances that are related to addPreserved. In particular, the setPreservesAll method can be called to indicate that the pass does not modify the LLVM program at all (which is true for analyses), and the setPreservesCFG method can be used by transformations that change instructions in the program but do not modify the CFG or terminator instructions (note that this property is implicitly set for BasicBlockPasses).

addPreserved is particularly useful for transformations like BreakCriticalEdges. This pass knows how to update a small set of loop and dominator related analyses if they exist, so it can preserve them, despite the fact that it hacks on the CFG.

Example implementations of `getAnalysisUsage`¶

// This example modifies the program, but does not modify the CFG
void LICM::getAnalysisUsage(AnalysisUsage &AU) const {
  AU.setPreservesCFG();
  AU.addRequired<LoopInfoWrapperPass>();
}

The `getAnalysis<>` and `getAnalysisIfAvailable<>` methods ¶

The Pass::getAnalysis<> method is automatically inherited by your class, providing you with access to the passes that you declared that you required with the getAnalysisUsage method. It takes a single template argument that specifies which pass class you want, and returns a reference to that pass. For example:

bool LICM::runOnFunction(Function &F) {
  LoopInfo &LI = getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
  //...
}

This method call returns a reference to the pass desired. You may get a runtime assertion failure if you attempt to get an analysis that you did not declare as required in your getAnalysisUsage implementation. This method can be called by your run* method implementation, or by any other local method invoked by your run* method.

A module level pass can use function level analysis info using this interface. For example:

bool ModuleLevelPass::runOnModule(Module &M) {
  //...
  DominatorTree &DT = getAnalysis<DominatorTree>(Func);
  //...
}

In above example, runOnFunction for DominatorTree is called by pass manager before returning a reference to the desired pass.

If your pass is capable of updating analyses if they exist (e.g., BreakCriticalEdges, as described above), you can use the getAnalysisIfAvailable method, which returns a pointer to the analysis if it is active. For example:

if (DominatorSet *DS = getAnalysisIfAvailable<DominatorSet>()) {
  // A DominatorSet is active.  This code will update it.
}

Implementing Analysis Groups ¶

Now that we understand the basics of how passes are defined, how they are used, and how they are required from other passes, it’s time to get a little bit fancier. All of the pass relationships that we have seen so far are very simple: one pass depends on one other specific pass to be run before it can run. For many applications, this is great, for others, more flexibility is required.

In particular, some analyses are defined such that there is a single simple interface to the analysis results, but multiple ways of calculating them. Consider alias analysis for example. The most trivial alias analysis returns “may alias” for any alias query. The most sophisticated analysis a flow-sensitive, context-sensitive interprocedural analysis that can take a significant amount of time to execute (and obviously, there is a lot of room between these two extremes for other implementations). To cleanly support situations like this, the LLVM Pass Infrastructure supp