Writing an LLVM Pass

1. Introduction - What is a pass?
2. Quick Start - Writing hello world
   - Setting up the build environment
   - Basic code required
   - Running a pass with `opt` or `analyze`
3. Pass classes and requirements
   - The `ImmutablePass` class
   - The `ModulePass` class
     - The `runOnModule` method
   - The `CallGraphSCCPass` class
     - The `doInitialization(Module &)` method
     - The `runOnSCC` method
     - The `doFinalization(Module &)` method
   - The `FunctionPass` class
     - The `doInitialization(Module &)` method
     - The `runOnFunction` method
     - The `doFinalization(Module &)` method
   - The `BasicBlockPass` class
     - The `doInitialization(Function &)` method
     - The `runOnBasicBlock` method
     - The `doFinalization(Function &)` method
   - The `MachineFunctionPass` class
     - The `runOnMachineFunction(MachineFunction &)` method
4. Pass Registration
   - The `print` method
5. Specifying interactions between passes
   - The `getAnalysisUsage` method
   - The `AnalysisUsage::addRequired<>` and `AnalysisUsage::addRequiredTransitive<>` methods
   - The `AnalysisUsage::addPreserved<>` method
   - Example implementations of `getAnalysisUsage`
   - The `getAnalysis<>` and `getAnalysisToUpdate<>` methods
6. Implementing Analysis Groups
   - Analysis Group Concepts
   - Using `RegisterAnalysisGroup`
7. Pass Statistics
8. What PassManager does
   - The `releaseMemory` method
9. Using GDB with dynamically loaded passes
   - Setting a breakpoint in your pass
   - Miscellaneous Problems
10. Future extensions planned
    - Multithreaded LLVM
    - `ModulePass`es requiring `FunctionPass`es

Written by Chris Lattner

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 `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, 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`. Next, you must set up a build script (Makefile) that will compile the source code for the new pass. To do this, copy the following into `Makefile`:

    # Makefile for hello pass

    # Path to top level of LLVM heirarchy
    LEVEL = ../../..

    # Name of the library to build
    LIBRARYNAME = hello

    # Build a dynamically loadable shared object
    SHARED_LIBRARY = 1

    # Include the makefile implementation stuff
    include $(LEVEL)/Makefile.common

This makefile specifies that all of the `.cpp` files in the current directory are to be compiled and linked together into a `lib/Debug/libhello.so` shared object that can be dynamically loaded by the `opt` or `analyze` tools. If your operating system uses a suffix other than .so (such as windows or Mac OS/X), 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/Function.h"

Which are needed because we are writing a `Pass`, and we are operating on `Function`'s.

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 only visible 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`'s operate a function at a time.

        virtual bool runOnFunction(Function &F) {
          std::cerr << "Hello: " << F.getName() << "\n";
          return false;
        }
      };  // end of struct Hello

We declare a "`runOnFunction`" method, which overloads 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.

      RegisterOpt<Hello> X("hello", "Hello World Pass");
    }  // end of anonymous namespace

Lastly, we register our class `Hello`, giving it a command line argument "`hello`", and a name "`Hello World Pass`". There are several different ways of registering your pass, depending on what it is to be used for. For "optimizations" we use the `RegisterOpt` template.

As a whole, the `.cpp` file looks like:

    #include "llvm/Pass.h"
    #include "llvm/Function.h"

    using namespace llvm;

    namespace {
      struct Hello : public FunctionPass {
        virtual bool runOnFunction(Function &F) {
          std::cerr << "Hello: " << F.getName() << "\n";
          return false;
        }
      };

      RegisterOpt<Hello> X("hello", "Hello World Pass");
    }

Now that it's all together, compile the file with a simple "`gmake`" command in the local directory and you should get a new "`lib/Debug/libhello.so` file. 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` or `analyze`

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 the `RegisterOpt` template, 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 Guide to compile "Hello World" to LLVM. We can now run the bytecode file (`hello.bc`) for the program through our transformation like this (or course, any bytecode file will work):

    $ opt -load ../../../lib/Debug/libhello.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/Debug/libhello.so --help
    OVERVIEW: llvm .bc -> .bc modular optimizer

    USAGE: opt [options] <input bytecode>

    OPTIONS:
      Optimizations available:
    ...
        -funcresolve    - Resolve Functions
        -gcse           - Global Common Subexpression Elimination
        -globaldce      - Dead Global Elimination
        -hello          - Hello World Pass
        -indvars        - Canonicalize Induction Variables
        -inline         - Function Integration/Inlining
        -instcombine    - Combine redundant instructions
    ...

The pass name get 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/Debug/libhello.so -hello -time-passes < hello.bc > /dev/null
    Hello: __main
    Hello: puts
    Hello: main
    ===============================================================================
                          ... Pass execution timing report ...
    ===============================================================================
      Total Execution Time: 0.02 seconds (0.0479059 wall clock)

       ---User Time---   --System Time--   --User+System--   ---Wall Time---  --- Pass Name ---
       0.0100 (100.0%)   0.0000 (  0.0%)   0.0100 ( 50.0%)   0.0402 ( 84.0%)  Bytecode Writer
       0.0000 (  0.0%)   0.0100 (100.0%)   0.0100 ( 50.0%)   0.0031 (  6.4%)  Dominator Set Construction
       0.0000 (  0.0%)   0.0000 (  0.0%)   0.0000 (  0.0%)   0.0013 (  2.7%)  Module Verifier
       0.0000 (  0.0%)   0.0000 (  0.0%)   0.0000 (  0.0%)   0.0033 (  6.9%)  Hello World Pass
       0.0100 (100.0%)   0.0100 (100.0%)   0.0200 (100.0%)   0.0479 (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 unneccesarily 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.

`ImmutablePass`es 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, refering 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.

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, and should return true if the module was modified by the transformation, 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 CallGraphSCCPass's. 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:

1. ... not allowed to modify any `Function`s that are not in the current SCC.
2. ... allowed to inspect any Function's other than those in the current SCC and the direct callees of the SCC.
3. ... required to preserve the current CallGraph object, updating it to reflect any changes made to the program.
4. ... not allowed to add or remove SCC's from the current Module, though they may change the contents of an SCC.
5. ... allowed to add or remove global variables from the current Module.
6. ... 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(Module &)` method

      virtual bool doInitialization(Module &M);

The `doIninitialize` method is allowed to do most of the things that `CallGraphSCCPass`'s 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(const std::vector<CallGraphNode *> &SCCM) = 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(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 `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. `FunctionPass`'s do not require that they are executed in a particular order, and `FunctionPass`'s do not modify external functions.

To be explicit, `FunctionPass` subclasses are not allowed to:

1. Modify a Function other than the one currently being processed.
2. Add or remove Function's from the current Module.
3. Add or remove global variables from the current Module.
4. Maintain state across invocations of `runOnFunction` (including global data)

Implementing a `FunctionPass` is usually straightforward (See the Hello World pass for example). `FunctionPass`'s 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 `doIninitialize` method is allowed to do most of the things that `FunctionPass`'s 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 `BasicBlockPass` class

`BasicBlockPass`'s 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:

1. Modify or inspect any basic blocks outside of the current one
2. Maintain state across invocations of `runOnBasicBlock`
3. Modify the control flow graph (by altering terminator instructions)
4. Any of the things forbidden for `FunctionPass`es.

`BasicBlockPass`es 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 `doIninitialize` method is allowed to do most of the things that `BasicBlockPass`'s are not allowed to do, but that `FunctionPass`'s 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. A `MachineFunctionPass` is also a `FunctionPass`, so all the restrictions that apply to a `FunctionPass` also apply to it. `MachineFunctionPass`es also have additional restrictions. In particular, `MachineFunctionPass`es are not allowed to do any of the following:

1. Modify any LLVM Instructions, BasicBlocks or Functions.
2. Modify a MachineFunction other than the one currently being processed.
3. Add or remove MachineFunctions from the current Module.
4. Add or remove global variables from the current Module.
5. 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.

Passes can be registered in several different ways. Depending on the general classification of the pass, you should use one of the following templates to register the pass:

- `RegisterOpt` - This template should be used when you are registering a pass that logically should be available for use in the '`opt`' utility.
- `RegisterAnalysis` - This template should be used when you are registering a pass that logically should be available for use in the '`analyze`' utility.
- `RegisterPass` - This is the generic form of the `Register*` templates that should be used if you want your pass listed by multiple or no utilities. This template takes an extra third argument that specifies which tools it should be listed in. See the PassSupport.h file for more information.

Regardless of how you register your pass, you must specify at least two parameters. The first 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 `opt` or `analyze`). The second 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 a pass is registered to be used by the `analyze` utility, you should implement the virtual `print` method:

The `print` method

      virtual void print(std::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. The `analyze` tool uses this method to generate its output.

The `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 the 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 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 BasicBlockPass's).

`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 is an example implementation from an analysis, which does not modify
      // the program at all, yet has a prerequisite.
      void PostDominanceFrontier::getAnalysisUsage(AnalysisUsage &AU) const {
        AU.setPreservesAll();
        AU.addRequired<PostDominatorTree>();
      }

and:

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

The `getAnalysis<>` and `getAnalysisToUpdate<>` 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<LoopInfo>();
         ...
       }

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.

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

      ...
      if (DominatorSet *DS = getAnalysisToUpdate<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 the 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 supports the notion of Analysis Groups.

Analysis Group Concepts

An Analysis Group is a single simple interface that may be implemented by multiple different passes. Analysis Groups can be given human readable names just like passes, but unlike passes, they need not derive from the `Pass` class. An analysis group may have one or more implementations, one of which is the "default" implementation.

Analysis groups are used by client passes just like other passes are: the `AnalysisUsage::addRequired()` and `Pass::getAnalysis()` methods. In order to resolve this requirement, the PassManager scans the available passes to see if any implementations of the analysis group are available. If none is available, the default implementation is created for the pass to use. All standard rules for interaction between passes still apply.

Although Pass Registration is optional for normal passes, all analysis group implementations must be registered, and must use the `RegisterAnalysisGroup` template to join the implementation pool. Also, a default implementation of the interface must be registered with `RegisterAnalysisGroup`.

As a concrete example of an Analysis Group in action, consider the AliasAnalysis analysis group. The default implementation of the alias analysis interface (the `basicaa` pass) just does a few simple checks that don't require significant analysis to compute (such as: two different globals can never alias each other, etc). Passes that use the `AliasAnalysis` interface (for example the `gcse` pass), do not care which implementation of alias analysis is actually provided, they just use the designated interface.

From the user's perspective, commands work just like normal. Issuing the command '`opt -gcse ...`' will cause the `basicaa` class to be instantiated and added to the pass sequence. Issuing the command '`opt -somefancyaa -gcse ...`' will cause the `gcse` pass to use the `somefancyaa` alias analysis (which doesn't actually exist, it's just a hypothetical example) instead.

Using `RegisterAnalysisGroup`

The `RegisterAnalysisGroup` template is used to register the analysis group itself as well as add pass implementations to the analysis group. First, an analysis should be registered, with a human readable name provided for it. Unlike registration of passes, there is no command line argument to be specified for the Analysis Group Interface itself, because it is "abstract":

      static RegisterAnalysisGroup<AliasAnalysis> A("Alias Analysis");

Once the analysis is registered, passes can declare that they are valid implementations of the interface by using the following code:

    namespace {
      // Analysis Group implementations must be registered normally...
      RegisterOpt<FancyAA>
      B("somefancyaa", "A more complex alias analysis implementation");

      // Declare that we implement the AliasAnalysis interface
      RegisterAnalysisGroup<AliasAnalysis, FancyAA> C;
    }

This just shows a class `FancyAA` that is registered normally, then uses the `RegisterAnalysisGroup` template to "join" the `AliasAnalysis` analysis group. Every implementation of an analysis group should join using this template. A single pass may join multiple different analysis groups with no problem.

    namespace {
      // Analysis Group implementations must be registered normally...
      RegisterOpt<BasicAliasAnalysis>
      D("basicaa", "Basic Alias Analysis (default AA impl)");

      // Declare that we implement the AliasAnalysis interface
      RegisterAnalysisGroup<AliasAnalysis, BasicAliasAnalysis, true> E;
    }

Here we show how the default implementation is specified (using the extra argument to the `RegisterAnalysisGroup` template). There must be exactly one default implementation available at all times for an Analysis Group to be used. Here we declare that the `BasicAliasAnalysis` pass is the default implementation for the interface.

Pass Statistics

The `Statistic` class, is designed to be an easy way to expose various success metrics from passes. These statistics are printed at the end of a run, when the -stats command line option is enabled on the command line. See the Statistics section in the Programmer's Manual for details.

What PassManager does

The `PassManager` class takes a list of passes, ensures their prerequisites are set up correctly, and then schedules passes to run efficiently. All of the LLVM tools that run passes use the `PassManager` for execution of these passes.

The `PassManager` does two main things to try to reduce the execution time of a series of passes:

1. Share analysis results - The PassManager attempts to avoid recomputing analysis results as much as possible. This means keeping track of which analyses are available already, which analyses get invalidated, and which analyses are needed to be run for a pass. An important part of work is that the `PassManager` tracks the exact lifetime of all analysis results, allowing it to free memory allocated to holding analysis results as soon as they are no longer needed.
2. Pipeline the execution of passes on the program - The `PassManager` attempts to get better cache and memory usage behavior out of a series of passes by pipelining the passes together. This means that, given a series of consequtive `FunctionPass`'s, it will execute all of the `FunctionPass`'s on the first function, then all of the `FunctionPass`es on the second function, etc... until the entire program has been run through the passes.

   This improves the cache behavior of the compiler, because it is only touching the LLVM program representation for a single function at a time, instead of traversing the entire program. It reduces the memory consumption of compiler, because, for example, only one `DominatorSet` needs to be calculated at a time. This also makes it possible some interesting enhancements in the future.

The effectiveness of the `PassManager` is influenced directly by how much information it has about the behaviors of the passes it is scheduling. For example, the "preserved" set is intentionally conservative in the face of an unimplemented `getAnalysisUsage` method. Not implementing when it should be implemented will have the effect of not allowing any analysis results to live across the execution of your pass.

The `PassManager` class exposes a `--debug-pass` command line options that is useful for debugging pass execution, seeing how things work, and diagnosing when you should be preserving more analyses than you currently are (To get information about all of the variants of the `--debug-pass` option, just type '`opt --help-hidden`').

By using the `--debug-pass=Structure` option, for example, we can see how our Hello World pass interacts with other passes. Lets try it out with the `gcse` and `licm` passes:

    $ opt -load ../../../lib/Debug/libhello.so -gcse -licm --debug-pass=Structure < hello.bc > /dev/null
    Module Pass Manager
      Function Pass Manager
        Dominator Set Construction
        Immediate Dominators Construction
        Global Common Subexpression Elimination
    --  Immediate Dominators Construction
    --  Global Common Subexpression Elimination
        Natural Loop Construction
        Loop Invariant Code Motion
    --  Natural Loop Construction
    --  Loop Invariant Code Motion
        Module Verifier
    --  Dominator Set Construction
    --  Module Verifier
      Bytecode Writer
    --Bytecode Writer

This output shows us when passes are constructed and when the analysis results are known to be dead (prefixed with '`--`'). Here we see that GCSE uses dominator and immediate dominator information to do its job. The LICM pass uses natural loop information, which uses dominator sets, but not immediate dominators. Because immediate dominators are no longer useful after the GCSE pass, it is immediately destroyed. The dominator sets are then reused to compute natural loop information, which is then used by the LICM pass.

After the LICM pass, the module verifier runs (which is automatically added by the '`opt`' tool), which uses the dominator set to check that the resultant LLVM code is well formed. After it finishes, the dominator set information is destroyed, after being computed once, and shared by three passes.

Lets see how this changes when we run the Hello World pass in between the two passes:

    $ opt -load ../../../lib/Debug/libhello.so -gcse -hello -licm --debug-pass=Structure < hello.bc > /dev/null
    Module Pass Manager
      Function Pass Manager
        Dominator Set Construction
        Immediate Dominators Construction
        Global Common Subexpression Elimination
    --  Dominator Set Construction
    --  Immediate Dominators Construction
    --  Global Common Subexpression Elimination
        Hello World Pass
    --  Hello World Pass
        Dominator Set Construction
        Natural Loop Construction
        Loop Invariant Code Motion
    --  Natural Loop Construction
    --  Loop Invariant Code Motion
        Module Verifier
    --  Dominator Set Construction
    --  Module Verifier
      Bytecode Writer
    --Bytecode Writer
    Hello: __main
    Hello: puts
    Hello: main

Here we see that the Hello World pass has killed the Dominator Set pass, even though it doesn't modify the code at all! To fix this, we need to add the following `getAnalysisUsage` method to our pass:

        // We don't modify the program, so we preserve all analyses
        virtual void getAnalysisUsage(AnalysisUsage &AU) const {
          AU.setPreservesAll();
        }

Now when we run our pass, we get this output:

    $ opt -load ../../../lib/Debug/libhello.so -gcse -hello -licm --debug-pass=Structure < hello.bc > /dev/null
    Pass Arguments:  -gcse -hello -licm
    Module Pass Manager
      Function Pass Manager
        Dominator Set Construction
        Immediate Dominators Construction
        Global Common Subexpression Elimination
    --  Immediate Dominators Construction
    --  Global Common Subexpression Elimination
        Hello World Pass
    --  Hello World Pass
        Natural Loop Construction
        Loop Invariant Code Motion
    --  Loop Invariant Code Motion
    --  Natural Loop Construction
        Module Verifier
    --  Dominator Set Construction
    --  Module Verifier
      Bytecode Writer
    --Bytecode Writer
    Hello: __main
    Hello: puts
    Hello: main

Which shows that we don't accidentally invalidate dominator information anymore, and therefore do not have to compute it twice.

The `releaseMemory` method

      virtual void releaseMemory();

The `PassManager` automatically determines when to compute analysis results, and how long to keep them around for. Because the lifetime of the pass object itself is effectively the entire duration of the compilation process, we need some way to free analysis results when they are no longer useful. The `releaseMemory` virtual method is the way to do this.

If you are writing an analysis or any other pass that retains a significant amount of state (for use by another pass which "requires" your pass and uses the getAnalysis method) you should implement `releaseMEmory` to, well, release the memory allocated to maintain this internal state. This method is called after the `run*` method for the class, before the next call of `run*` in your pass.

Using GDB with dynamically loaded passes

Unfortunately, using GDB with dynamically loaded passes is not as easy as it should be. First of all, you can't set a breakpoint in a shared object that has not been loaded yet, and second of all there are problems with inlined functions in shared objects. Here are some suggestions to debugging your pass with GDB.

For sake of discussion, I'm going to assume that you are debugging a transformation invoked by `opt`, although nothing described here depends on that.

Setting a breakpoint in your pass

First thing you do is start `gdb` on the `opt` process:

    $ gdb opt
    GNU gdb 5.0
    Copyright 2000 Free Software Foundation, Inc.
    GDB is free software, covered by the GNU General Public License, and you are
    welcome to change it and/or distribute copies of it under certain conditions.
    Type "show copying" to see the conditions.
    There is absolutely no warranty for GDB.  Type "show warranty" for details.
    This GDB was configured as "sparc-sun-solaris2.6"...
    (gdb)

Note that `opt` has a lot of debugging information in it, so it takes time to load. Be patient. Since we cannot set a breakpoint in our pass yet (the shared object isn't loaded until runtime), we must execute the process, and have it stop before it invokes our pass, but after it has loaded the shared object. The most foolproof way of doing this is to set a breakpoint in `PassManager::run` and then run the process with the arguments you want:

    (gdb) break PassManager::run
    Breakpoint 1 at 0x2413bc: file Pass.cpp, line 70.
    (gdb) run test.bc -load $(LLVMTOP)/llvm/lib/Debug/[libname].so -[passoption]
    Starting program: opt test.bc -load $(LLVMTOP)/llvm/lib/Debug/[libname].so -[passoption]
    Breakpoint 1, PassManager::run (this=0xffbef174, M=@0x70b298) at Pass.cpp:70
    70      bool PassManager::run(Module &M) { return PM->run(M); }
    (gdb)

Once the `opt` stops in the `PassManager::run` method you are now free to set breakpoints in your pass so that you can trace through execution or do other standard debugging stuff.

Miscellaneous Problems

Once you have the basics down, there are a couple of problems that GDB has, some with solutions, some without.

- Inline functions have bogus stack information. In general, GDB does a pretty good job getting stack traces and stepping through inline functions. When a pass is dynamically loaded however, it somehow completely loses this capability. The only solution I know of is to de-inline a function (move it from the body of a class to a .cpp file).
- Restarting the program breaks breakpoints. After following the information above, you have succeeded in getting some breakpoints planted in your pass. Nex thing you know, you restart the program (i.e., you type '`run`' again), and you start getting errors about breakpoints being unsettable. The only way I have found to "fix" this problem is to `delete` the breakpoints that are already set in your pass, run the program, and re-set the breakpoints once execution stops in `PassManager::run`.

Hopefully these tips will help with common case debugging situations. If you'd like to contribute some tips of your own, just contact Chris.

Future extensions planned

Although the LLVM Pass Infrastructure is very capable as it stands, and does some nifty stuff, there are things we'd like to add in the future. Here is where we are going:

Multithreaded LLVM

Multiple CPU machines are becoming more common and compilation can never be fast enough: obviously we should allow for a multithreaded compiler. Because of the semantics defined for passes above (specifically they cannot maintain state across invocations of their `run*` methods), a nice clean way to implement a multithreaded compiler would be for the `PassManager` class to create multiple instances of each pass object, and allow the separate instances to be hacking on different parts of the program at the same time.

This implementation would prevent each of the passes from having to implement multithreaded constructs, requiring only the LLVM core to have locking in a few places (for global resources). Although this is a simple extension, we simply haven't had time (or multiprocessor machines, thus a reason) to implement this. Despite that, we have kept the LLVM passes SMP ready, and you should too.

`ModulePass`es requiring `FunctionPass`es

Currently it is illegal for a `ModulePass` to require a `FunctionPass`. This is because there is only one instance of the `FunctionPass` object ever created, thus nowhere to store information for all of the functions in the program at the same time. Although this has come up a couple of times before, this has always been worked around by factoring one big complicated pass into a global and an interprocedural part, both of which are distinct. In the future, it would be nice to have this though.

Note that it is no problem for a `FunctionPass` to require the results of a `ModulePass`, only the other way around.