Source-based Code Coverage — Clang 3.9 documentation

# Clang 3.9 documentation

## Source-based Code Coverage

- Introduction
- The code coverage workflow
- Compiling with coverage enabled
- Running the instrumented program
- Creating coverage reports
- Format compatibility guarantees
- Using the profiling runtime without static initializers
- Drawbacks and limitations

## Introduction

This document explains how to use clang’s source-based code coverage feature. It’s called “source-based” because it operates on AST and preprocessor information directly. This allows it to generate very precise coverage data.

Clang ships two other code coverage implementations:

- SanitizerCoverage - A low-overhead tool meant for use alongside the various sanitizers. It can provide up to edge-level coverage.
- gcov - A GCC-compatible coverage implementation which operates on DebugInfo.

From this point onwards “code coverage” will refer to the source-based kind.

## The code coverage workflow

The code coverage workflow consists of three main steps:

- Compiling with coverage enabled.
- Running the instrumented program.
- Creating coverage reports.

The next few sections work through a complete, copy-‘n-paste friendly example based on this program:

    % cat <<EOF > foo.cc
    #define BAR(x) ((x) || (x))
    template <typename T> void foo(T x) {
      for (unsigned I = 0; I < 10; ++I) { BAR(I); }
    }
    int main() {
      foo<int>(0);
      foo<float>(0);
      return 0;
    }
    EOF

## Compiling with coverage enabled

To compile code with coverage enabled, pass `-fprofile-instr-generate -fcoverage-mapping` to the compiler:

    # Step 1: Compile with coverage enabled.
    % clang++ -fprofile-instr-generate -fcoverage-mapping foo.cc -o foo

Note that linking together code with and without coverage instrumentation is supported: any uninstrumented code simply won’t be accounted for.

## Running the instrumented program

The next step is to run the instrumented program. When the program exits it will write a raw profile to the path specified by the `LLVM_PROFILE_FILE` environment variable. If that variable does not exist, the profile is written to `default.profraw` in the current directory of the program. If `LLVM_PROFILE_FILE` contains a path to a non-existent directory, the missing directory structure will be created. Additionally, the following special pattern strings are rewritten:

- “%p” expands out to the process ID.
- “%h” expands out to the hostname of the machine running the program.
- “%Nm” expands out to the instrumented binary’s signature. When this pattern is specified, the runtime creates a pool of N raw profiles which are used for on-line profile merging. The runtime takes care of selecting a raw profile from the pool, locking it, and updating it before the program exits. If N is not specified (i.e the pattern is “%m”), it’s assumed that `N = 1`. N must be between 1 and 9. The merge pool specifier can only occur once per filename pattern.

    # Step 2: Run the program.
    % LLVM_PROFILE_FILE="foo.profraw" ./foo

## Creating coverage reports

Raw profiles have to be indexed before they can be used to generate coverage reports. This is done using the “merge” tool in `llvm-profdata`, so named because it can combine and index profiles at the same time:

    # Step 3(a): Index the raw profile.
    % llvm-profdata merge -sparse foo.profraw -o foo.profdata

There are multiple different ways to render coverage reports. One option is to generate a line-oriented report:

    # Step 3(b): Create a line-oriented coverage report.
    % llvm-cov show ./foo -instr-profile=foo.profdata

To demangle any C++ identifiers in the output, use:

    % llvm-cov show ./foo -instr-profile=foo.profdata | c++filt -n

This report includes a summary view as well as dedicated sub-views for templated functions and their instantiations. For our example program, we get distinct views for `foo<int>(...)` and `foo<float>(...)`. If `-show-line-counts-or-regions` is enabled, `llvm-cov` displays sub-line region counts (even in macro expansions):

       20|    1|#define BAR(x) ((x) || (x))
                               ^20     ^2
        2|    2|template <typename T> void foo(T x) {
       22|    3|  for (unsigned I = 0; I < 10; ++I) { BAR(I); }
                                       ^22     ^20  ^20^20
        2|    4|}
    ------------------
    | void foo<int>(int):
    |      1|    2|template <typename T> void foo(T x) {
    |     11|    3|  for (unsigned I = 0; I < 10; ++I) { BAR(I); }
    |                                     ^11     ^10  ^10^10
    |      1|    4|}
    ------------------
    | void foo<float>(int):
    |      1|    2|template <typename T> void foo(T x) {
    |     11|    3|  for (unsigned I = 0; I < 10; ++I) { BAR(I); }
    |                                     ^11     ^10  ^10^10
    |      1|    4|}
    ------------------

It’s possible to generate a file-level summary of coverage statistics (instead of a line-oriented report) with:

    # Step 3(c): Create a coverage summary.
    % llvm-cov report ./foo -instr-profile=foo.profdata
    Filename                    Regions    Miss   Cover Functions  Executed
    -----------------------------------------------------------------------
    /tmp/foo.cc                      13       0 100.00%         3   100.00%
    -----------------------------------------------------------------------
    TOTAL                            13       0 100.00%         3   100.00%

A few final notes:

- The `-sparse` flag is optional but can result in dramatically smaller indexed profiles. This option should not be used if the indexed profile will be reused for PGO.

- Raw profiles can be discarded after they are indexed. Advanced use of the profile runtime library allows an instrumented program to merge profiling information directly into an existing raw profile on disk. The details are out of scope.

- The `llvm-profdata` tool can be used to merge together multiple raw or indexed profiles. To combine profiling data from multiple runs of a program, try e.g:

      % llvm-profdata merge -sparse foo1.profraw foo2.profdata -o foo3.profdata

## Format compatibility guarantees

- There are no backwards or forwards compatibility guarantees for the raw profile format. Raw profiles may be dependent on the specific compiler revision used to generate them. It’s inadvisable to store raw profiles for long periods of time.
- Tools must retain backwards compatibility with indexed profile formats. These formats are not forwards-compatible: i.e, a tool which uses format version X will not be able to understand format version (X+k).
- There is a third format in play: the format of the coverage mappings emitted into instrumented binaries. Tools must retain backwards compatibility with these formats. These formats are not forwards-compatible.

## Using the profiling runtime without static initializers

By default the compiler runtime uses a static initializer to determine the profile output path and to register a writer function. To collect profiles without using static initializers, do this manually:

- Export a `int __llvm_profile_runtime` symbol from each instrumented shared library and executable. When the linker finds a definition of this symbol, it knows to skip loading the object which contains the profiling runtime’s static initializer.
- Forward-declare `void __llvm_profile_initialize_file(void)` and call it once from each instrumented executable. This function parses `LLVM_PROFILE_FILE`, sets the output path, and truncates any existing files at that path. To get the same behavior without truncating existing files, pass a filename pattern string to `void __llvm_profile_set_filename(char *)`. These calls can be placed anywhere so long as they precede all calls to `__llvm_profile_write_file`.
- Forward-declare `int __llvm_profile_write_file(void)` and call it to write out a profile. This function returns 0 when it succeeds, and a non-zero value otherwise. Calling this function multiple times appends profile data to an existing on-disk raw profile.

## Drawbacks and limitations

- Code coverage does not handle unpredictable changes in control flow or stack unwinding in the presence of exceptions precisely. Consider the following function:

      int f() {
        may_throw();
        return 0;
      }

  If the call to `may_throw()` propagates an exception into `f`, the code coverage tool may mark the `return` statement as executed even though it is not. A call to `longjmp()` can have similar effects.