# Google Test Demo

## Introduction

[Google Test](https://github.com/google/googletest) is a unit testing framework
for C++ programming developed by Google. It is currently being used for unit
testing in the [OpenTelemetry
C++](https://github.com/open-telemetry/opentelemetry-cpp) repo, along with tools
like [codecov.io](http://codecov.io/) to thoroughly test the code in the
repository. A primer for using Google Test can be found
[here](https://github.com/google/googletest/blob/master/googletest/docs/primer.md).

## Features

Google Test provides a vast set of tools to be used for unit testing. The two
most important are assertions and tests.

### Assertions

Google Test allows a developer to write test cases that use assertions to verify
code behavior. Refer to the
[assertions](https://github.com/google/googletest/blob/master/googletest/docs/primer.md#assertions)
section in the primer for more details.

### Tests

To create a test, use the `TEST()` macro to define a test function. This is
similar to a normal C++ function that returns no value. Google Test assertions
are used inside the test function, and the result of the test is determined by
the assertions used inside the test function. If any assertion fails (can be
either fatal or nonfatal), then the test fails; if all assertions pass, the test
succeeds. A sample test function is outlined below.

```cpp
TEST(TestSuiteName, TestName) {

    // Test body goes here

}
```

A [sample unit
test](https://github.com/open-telemetry/opentelemetry-cpp/blob/master/sdk/test/trace/tracer_provider_test.cc)
from the OTel C++ repo, testing the `GetTracer()` method in the `TracerProvider`
class, is shown below.

```cpp
#include "opentelemetry/sdk/trace/tracer_provider.h"
#include "opentelemetry/context/threadlocal_context.h"
#include "opentelemetry/sdk/trace/samplers/always_off.h"
#include "opentelemetry/sdk/trace/samplers/always_on.h"
#include "opentelemetry/sdk/trace/simple_processor.h"
#include "opentelemetry/sdk/trace/tracer.h"

#include <gtest/gtest.h>

using namespace opentelemetry::sdk::trace;

TEST(TracerProvider, GetTracer)
{
  std::shared_ptr<SpanProcessor> processor(new SimpleSpanProcessor(nullptr));

  TracerProvider tp1(processor);
  auto t1 = tp1.GetTracer("test");
  auto t2 = tp1.GetTracer("test");
  auto t3 = tp1.GetTracer("different", "1.0.0");
  ASSERT_NE(nullptr, t1);
  ASSERT_NE(nullptr, t2);
  ASSERT_NE(nullptr, t3);

  // Should return the same instance each time.
  ASSERT_EQ(t1, t2);
  ASSERT_EQ(t1, t3);

  // Should be an sdk::trace::Tracer with the processor attached.
  auto sdkTracer1 = dynamic_cast<Tracer *>(t1.get());
  ASSERT_NE(nullptr, sdkTracer1);
  ASSERT_EQ(processor, sdkTracer1->GetProcessor());
  ASSERT_EQ("AlwaysOnSampler", sdkTracer1->GetSampler()->GetDescription());

  TracerProvider tp2(processor, std::make_shared<AlwaysOffSampler>());
  auto sdkTracer2 = dynamic_cast<Tracer *>(tp2.GetTracer("test").get());
  ASSERT_EQ("AlwaysOffSampler", sdkTracer2->GetSampler()->GetDescription());
}
```

### Test Coverage Reports

Another feature that Google Test provides is test coverage reports; along with
this, Google Test also allows us to easily integrate code coverage tools such as
[codecov.io](http://codecov.io/) with the project.

## Integration and Usage

One of the base requirements to build and use Google Test from a source package
are to use either Bazel or CMake; the other is a C++14-standard-compliant
compiler like GCC or Clang.

### Bazel

First, to install bazel, refer to the instructions
[here](https://docs.bazel.build/versions/3.3.0/install.html), and for an example
build using bazel, refer to the tutorial
[here](https://docs.bazel.build/versions/3.3.0/tutorial/cpp.html).

Bazel makes use of a `BUILD` file, which gives instructions to bazel on how to
build the project. The file contains targets that point to a set of source files
and dependencies. Along with a `BUILD` file, a `WORKSPACE` file exists that
identifies the directory it resides in as a bazel workspace. In the OTel C++
repository, the SDK unit tests using the Google Test framework to ensure code
functionality. In the
[BUILD](/sdk/test/trace)
file for trace tests, there are six different targets, each corresponding to a
different unit test. An example target taken from this file is shown below.

```cmake
cc_test(
    name = "tracer_provider_test",
    srcs = [
        "tracer_provider_test.cc",
    ],
    deps = [
        "//sdk/src/trace",
        "@com_google_googletest//:gtest_main",
    ],
    tags = ["test",],
)
```

Integrating Google Tests with bazel is as simple as creating a target with:

- name: The target name, aka the name of the binary to build
- srcs: The source file containing the tests
- deps: The dependencies of the build; here, `//sdk/src/trace` refers to the
  directory of the source code being tested, and
  `@com_google_googletest//:gtest_main` is the Google Test dependency.

Building and executing a unit test is also very simple. On terminal, navigate to
the directory the WORKSPACE file resides in, and execute two commands:

```console
bazel build //path/to/package:target-name
bazel-bin/path/to/package/target-name
```

The first command builds the unit test with the given target name; the second
runs the unit test.

This next command runs the above two commands at once, though you may get a
message stating `There were tests whose specified size is too big` and they may
not run without modifying some options.

```console
bazel test //path/to/package:target-name
```

For our example the commands above would be:

```console
bazel build //sdk/test/trace:tracer_provider_test
bazel-bin/sdk/test/trace/tracer_provider_test
```

or

```console
bazel test //sdk/test/trace:tracer_provider_test
```

Additionally, all Bazel tests can be ran in a Docker container by navigating to
the root of the directory and executing the command:

```console
./ci/run_docker.sh ./ci/do_ci.sh bazel.test
```

### CMake

CMake can be installed following instructions from
[here](https://cmake.org/download/). You will also need to install Google Test,
along with libbenchmark.

Download a zip of the Google Test source code
[here](https://github.com/google/googletest/releases/tag/release-1.10.0). Then,
navigate into the source code directory and run the following commands:

```console
mkdir build && cd build
cmake ..
make
make install
```

This will install Google Test for you; you can delete the source code after
running these commands.

Next, follow the instructions
[here](https://github.com/google/benchmark#installation) to download Google
Benchmark. The section following this one will detail performance benchmarking
using Google Benchmark.

CMake makes use of a `CMakeLists.txt` file that provides instructions for a
project’s source files and targets. There is a main `CMakeLists.txt` file in the
root of the project directory, and a `CMakeLists.txt` for each subdirectory. In
the main `CMakeLists.txt` file, the `cmake_minimum_required`  and
`CMAKE_CXX_STANDARD` are set, the project name is set with `project()`,
directories are included and subdirectories added, and much more. However, more
importantly, in the context of Google Test within the OTel C++ repo, the
`CMakeLists.txt` to look at is the one located in the directory your tests are
being written in; for this example, it’s `opentelemetry-cpp/sdk/test/trace`.
This
[CMakeLists.txt](https://github.com/open-telemetry/opentelemetry-cpp/blob/master/sdk/test/trace/CMakeLists.txt)
file, shown below, describes the names of the tests to be added as executables.

```cmake
foreach(
  testname
  tracer_provider_test
  span_data_test
  simple_processor_test
  tracer_test
  always_off_sampler_test
  always_on_sampler_test
  parent_or_else_sampler_test
  probability_sampler_test
  batch_span_processor_test
  attribute_utils_test)
  add_executable(${testname} "${testname}.cc")
  target_link_libraries(
    ${testname} ${GTEST_BOTH_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT}
    opentelemetry_common opentelemetry_trace)
  gtest_add_tests(TARGET ${testname} TEST_PREFIX trace. TEST_LIST ${testname})
endforeach()

add_executable(sampler_benchmark sampler_benchmark.cc)
target_link_libraries(sampler_benchmark benchmark::benchmark
                      ${CMAKE_THREAD_LIBS_INIT} opentelemetry_trace)

```

This is how a `CMakeLists.txt` file will be written with the purpose of unit
testing. After writing a unit test, navigate to the `CMakeLists.txt` file for
that subdirectory and add the test name to the list of test names in
`foreach()`.

To build and execute using CMake, navigate into the root directory
(`opentelemetry-cpp` here), and run the following commands from terminal:

```console
mkdir build && cd build
cmake .. // or cmake -DCMAKE_BUILD_TYPE=Debug -DCMAKE_CXX_FLAGS=“-Werror —coverage” ..
make
make test
```

This will run all tests in the repo.

To run tests individually, in terminal, navigate to the `build` directory and
execute the following command:

```console
ctest -R <name_of_your_test>
```

For example, this command will build and execute the test named TEST(Meter,
CollectSyncInstruments) in the metrics library:

```console
ctest -R metrics.Meter.CollectSyncInstruments
```

The second cmake option creates test coverage reports; these are able to be
viewed using a tool like lcov (instructions to download
[here](http://ltp.sourceforge.net/coverage/lcov.php)), and running the command

```console
lcov --directory $PWD --capture --output-file coverage.info
```

Additionally, all CMake tests can be ran in a Docker container by navigating to
the root of the directory and executing the command:

```console
./ci/run_docker.sh ./ci/do_ci.sh cmake.test
```

### Performance Benchmarking

While Google Test itself does not provide performance benchmarking, Google
Benchmark, a closely related tool, does. Follow the instructions
[here](https://github.com/google/benchmark#installation) to download Google
Benchmark using CMake. A basic usage example can be viewed
[here](https://github.com/google/benchmark#usage), while a more in depth usage
guide can be found [here](https://github.com/google/benchmark#user-guide).
Generally, it is very similar to the Googletest unit testing structure and we
can easily convert unit tests into benchmarked routines.

A benchmark consists of a “benchmarked function” which takes a benchmark state
as a parameter.  The library automatically decides how many iterations to run
based on the duration of the first few run iterations.  This function is called
directly underneath using the benchmark macro.  Finally, a call to
BENCHMARK_MAIN() runs all benchmarks.  As a proof of concept, below is a unit
test for the PrometheusCollector class into a benchmark:

```cpp
#include "opentelemetry/exporters/prometheus/prometheus_collector.h"
#include "opentelemetry/sdk/metrics/aggregator/counter_aggregator.h"
#include "opentelemetry/sdk/metrics/record.h"
#include "opentelemetry/version.h"
#include <benchmark/benchmark.h>

OPENTELEMETRY_BEGIN_NAMESPACE
namespace exporters
{
namespace prometheus
{

void CreateRecordsAndCollect(benchmark::State &state) {


    for (auto _ : state) {

        // construct a collection to add metric records
        int num_records = 2;
        std::vector<opentelemetry::sdk::metrics::Record> records;

        for (int i = 0; i < num_records; i++)
        {
            std::string name        = "record_" + std::to_string(i);
            std::string description = "record_" + std::to_string(i);
            std::string labels      = "{label1:v1,label2:v2,}";
            auto aggregator         = std::shared_ptr<opentelemetry::sdk::metrics::Aggregator<int>>(
                new opentelemetry::sdk::metrics::CounterAggregator<int>(
                    opentelemetry::metrics::InstrumentKind::Counter));
            aggregator->update(10);
            aggregator->checkpoint();

            opentelemetry::sdk::metrics::Record r{name, description, labels, aggregator};
            records.push_back(r);
        }

        opentelemetry::exporter::prometheus::PrometheusCollector collector;

        collector.AddMetricData(records);

        collector.Collect();

    }
}
BENCHMARK(CreateRecordsAndCollect);

} //namespace prometheus
} //namespace exporters
OPENTELEMETRY_END_NAMESPACE

BENCHMARK_MAIN();
```

Output

```console
------------------------------------------------------------------
Benchmark                        Time             CPU   Iterations
------------------------------------------------------------------
CreateRecordsAndCollect      51989 ns        51821 ns        12438
```

OTel also provides a bazel shortcut to build tests which can be seen
[here](https://github.com/open-telemetry/opentelemetry-cpp/blob/573696f3fdc1fd85e24ac19860ae6f2345837a3e/bazel/otel_cc_benchmark.bzl).
This not only creates a benchmark executable, but a “smoketest” which runs each
benchmark for one iteration.

We can use benchmarking to measure performance of exporting, data translation,
and collecting. Additionally, creating benchmarks for each component will help
us determine which areas of the pipeline can be optimized further.