Google Test
benchmark

Google Test | benchmark | |
---|---|---|
71 | 21 | |
35,395 | 9,230 | |
0.8% | 1.0% | |
6.4 | 8.8 | |
12 days ago | 6 days ago | |
C++ | C++ | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Google Test
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The Two Factions of C++
> Googletest ... declares a direct dependency on an older LTS release of absl
Looking at the build configuration code:
https://github.com/google/googletest/blob/main/CMakeLists.tx...
it seems like the dependence on Abseil is optional. i.e. you can use googltest on its own. I wouldn't recommend it (I kinda like doctest), but still.
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Getting started with GoogleTest and CMake
include(FetchContent) # Fetch GoogleTest FetchContent_Declare( googletest GIT_REPOSITORY https://github.com/google/googletest.git GIT_TAG release-1.11.0 ) FetchContent_MakeAvailable(googletest) # Collect C++ source files recursively file(GLOB_RECURSE CXX_FILES "${CMAKE_CURRENT_LIST_DIR}/*.cpp") add_executable(unit_tests ${CXX_FILES}) # Link GoogleTest libraries target_link_libraries(unit_tests PRIVATE gtest_main ${PROJECT_NAME}_lib # Link to the main project library ) # Include directories (including where GoogleTest is built) target_include_directories(unit_tests PRIVATE ${gtest_SOURCE_DIR}/include) # Add include directories for tests to find headers target_include_directories(unit_tests PRIVATE ${PROJECT_SOURCE_DIR}/src) # Enable testing and discover tests # Discover and run tests include(GoogleTest) gtest_discover_tests(unit_tests)
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Open Source C++ Stack
Google Test
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Creating k-NN with C++ (from Scratch)
cmake_minimum_required(VERSION 3.5) project(knn_cpp CXX) include(FetchContent) FetchContent_Declare( googletest GIT_REPOSITORY https://github.com/google/googletest.git GIT_TAG release-1.11.0 ) FetchContent_MakeAvailable(googletest) FetchContent_Declare(matplotplusplus GIT_REPOSITORY https://github.com/alandefreitas/matplotplusplus GIT_TAG origin/master) FetchContent_GetProperties(matplotplusplus) if(NOT matplotplusplus_POPULATED) FetchContent_Populate(matplotplusplus) add_subdirectory(${matplotplusplus_SOURCE_DIR} ${matplotplusplus_BINARY_DIR} EXCLUDE_FROM_ALL) endif() function(knn_cpp_test TEST_NAME TEST_SOURCE) add_executable(${TEST_NAME} ${TEST_SOURCE}) target_link_libraries(${TEST_NAME} PUBLIC matplot) aux_source_directory(${CMAKE_CURRENT_SOURCE_DIR}/../lib LIB_SOURCES) target_link_libraries(${TEST_NAME} PRIVATE gtest gtest_main gmock gmock_main) target_include_directories(${TEST_NAME} PRIVATE ${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_SOURCE_DIR}/../) target_sources(${TEST_NAME} PRIVATE ${LIB_SOURCES} ) include(GoogleTest) gtest_discover_tests(${TEST_NAME}) endfunction() knn_cpp_test(LinearAlgebraTest la_test.cc) knn_cpp_test(KnnTest knn_test.cc) knn_cpp_test(UtilsTest utils_test.cc)
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Starting with C
Okay, time to start unit tests!!! We will use Unity Test Framework to do unit testing. It is one of widely used testing frameworks alongside with Check, Google Test etc. Just downloading source code, and putting it to the project folder is enough to make it work (that is also why it is portable).
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Just in case: Debian Bookworm comes with a buggy GCC
Updating GCC (it happened to GoogleTest).
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Automatically run tests, formatters & linters with CI!
Roy's project uses Google Test, a C++ testing framework. His testing setup is similar to mine as we both keep source files in one directory and tests in another. The key difference is that I can run the tests using the Visual Studios run button. It was fairly easy to write the new tests as there were existing ones that I could reference to check the syntax!
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C++ Unit Testing Using Google Test - My Experience
The Google Test Documentation provides a primer for first-time users. The primer introduces some basic concepts and terminology, some of which I've been able to learn for this lab exercise.
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Basic C++ Unit Testing with GTest, CMake, and Submodules
> git submodule add https://github.com/google/googletest.git > git submodule update --init --recursive
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VS code + cmake + gtest?
cmake_minimum_required(VERSION 3.14) project(my_project) # GoogleTest requires at least C++14 set(CMAKE_CXX_STANDARD 14) set(CMAKE_CXX_STANDARD_REQUIRED ON) include(FetchContent) FetchContent_Declare( googletest URL https://github.com/google/googletest/archive/03597a01ee50ed33e9dfd640b249b4be3799d395.zip ) # For Windows: Prevent overriding the parent project's compiler/linker settings set(gtest_force_shared_crt ON CACHE BOOL "" FORCE) FetchContent_MakeAvailable(googletest) enable_testing() add_executable( hello_test hello_test.cpp ) target_link_libraries( hello_test GTest::gtest_main ) include(GoogleTest) gtest_discover_tests(hello_test)
benchmark
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std::array in C++ isn't slower than array in C
As with the assembly code analysis, let's look at two types of operations: sequentially filling an array with random numbers, and randomly accessing arbitrary array elements when we pass it to a function. To compile the code, we used GCC and Clang. We checked both debug (with the -DDEBUG flag) and release builds (with the -O3 level optimizations and the -DNDEBUG flag). And of course, we used Google Benchmark to run the tests.
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Open Source C++ Stack
''' Uchen core - ML framework ''' module(name = "uchen-core", version = "0.1", compatibility_level = 1) bazel_dep(name = "abseil-cpp", version = "20240116.2") bazel_dep(name = "googletest", version = "1.14.0") git_override( module_name = "googletest", remote = "https://github.com/google/googletest.git", commit = "1d17ea141d2c11b8917d2c7d029f1c4e2b9769b2", ) bazel_dep(name = "google_benchmark", version = "1.8.3") git_override( module_name = "google_benchmark", remote = "https://github.com/google/benchmark.git", commit = "447752540c71f34d5d71046e08192db181e9b02b", ) # Dev dependencies bazel_dep(name = "hedron_compile_commands", dev_dependency = True) git_override( module_name = "hedron_compile_commands", remote = "https://github.com/hedronvision/bazel-compile-commands-extractor.git", commit = "a14ad3a64e7bf398ab48105aaa0348e032ac87f8", )
- How can I check the execution time of a program rendered in SFML?
- How to Perf profile functions?
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how do you properly benchmark?
I'm aware of one by Google that I used a couple times, but IMO it's better to capture real runtime data from a fully-operational process than to carve out the benchmarkable bits and test them in isolation, so I track information during program testing and print it all to a log instead of using things like that.
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Benchmarking my data structure
If you just want to do some quick benchmarks, you can just use std::chrono::high_resolution_clock::now(). Call it before the code that you are benchmarking and then immediately after. Take them away and you have your duration. If you want to use a proper benchmarking tool then I can totally recommend Google Benchmark. Fantastic benchmarking tool. Honourable mention would be Quick Bench which is an online tool that uses Google Benchmark.
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Google benchmark : No rule to make Target***
I tried to install google benchmark(https://github.com/google/benchmark) in my ubuntu machine by :
- Best accurate way to measure/compare elapsed time in C++
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Don’t Be Scared Of Functional Programming
We don't know if it's a lie until we verify it and that's not difficult, you have a quicksort implementation in a couple of languages, you'll need to pass the necessary parameters to show the time needed by a function call to execute to the compiler or interpreter or you may use use a library(like benchmark for C++) and you're good to go.
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How to identify inefficient method calls?
If you are uncertain about the performance characteristics of a function you should ALWAYS benchmark it. Googles Benchmark library is wonderful for quick micro benchmarks. For more complex things, perhaps look into profiling and then look at invocation counts of copy constructors.
What are some alternatives?
Catch - A modern, C++-native, test framework for unit-tests, TDD and BDD - using C++14, C++17 and later (C++11 support is in v2.x branch, and C++03 on the Catch1.x branch)
Celero - C++ Benchmark Authoring Library/Framework
CppUTest - CppUTest unit testing and mocking framework for C/C++
hayai - C++ benchmarking framework
CppUnit - C++ port of JUnit
Nonius - A C++ micro-benchmarking framework
Boost.Test - The reference C++ unit testing framework (TDD, xUnit, C++03/11/14/17)
doctest - The fastest feature-rich C++11/14/17/20/23 single-header testing framework
Unity Test API - Simple Unit Testing for C
easy_profiler - Lightweight profiler library for c++
