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Modern C++ Project Structuring

For no particular reason whatsoever, I recently found myself dusting off an old repository, InterviewPracticeQuestions and thought it a good exercise to restructure it along the latest C++ and CMake principles.



I don't intend on writing a prescriptive argument on the absolute best possible configuration for a prospective new project. Rather, I just wanted to share some loose advice that I've collected, and demonstrate its application in context. As part of this walkthrough, there are three major components to this project that I'd like to focus upon in detail:


Anyone's that worked in C++ for long enough is painfully aware of the 'intractability' that legacy C++ projects can so often exhibit. Time and time again, the culprit is intransigent CMake that stiffles any chance of initiating any meaningful change, without upsetting the apple cart.

The inconvenient truth is the fact that CMake, is indeed, complex and difficult. This succinctly explains why it so often goes awry. That said, Modern CMake has come a long way in addressing these criticisms and provides entirely new features and paradigms for writing efficient, readable and maintainable CMake.

This article isn't an exposition on how to write Modern CMake per se, but as I delve deeper, I hope to highlight CMake best practices and how I've sought to incorporate them into my project's build system.


For the uninitiated, Conan is a package manager for C/C++ projects. Just as anyone is familiar with using pip to install third-party dependencies for their Python projects, Conan aims to do the very same for C/C++. Anecdotally, I haven't ever encountered it used seriously in production environments, but with the latest release, I hope it'll finally gain some traction going forward.

I've assimilated Conan into this project to highlight its use case for managing and installing external dependencies such as Google Test.

It's worth noting that the recent major release of Conan V2 is a complete re-architecture that differs significantly to previous versions. It does a great deal in simplifying the API and improving overall useability, however it's important to be mindful that most online documentation still serves versions prior to Conan V2, and hence is at best out-of-date, or at worst, incompatible. Thankfully, the latest Conan V2 examples here have proven to be very informative


Despite being part and parcel of the CMake distribution, it's always been a great surprise to me how often this little tool is overlooked and ignored. For all intents and purposes, CTest is simply a convenient test runner to execute test suites, but I'd also contest that that limited definition downplays its utility in facilitating the creation of more complex tests.

Unfortunately, this project is far too simplistic to illustrate the full capabilities of CTest, but perhaps I'll explore them further in a later article.

Project Structuring

The overall structure I chose for the project is customary. It consists of the usual conanfile.py, CMakeLists.txt and README.md at the root of the project. There is a cmake subdirectory to abstract away all my CMake helper scripts, a test subdirectory for my test binaries, and finally the src directory containing the project's source code:

├── conanfile.py
├── CMakeLists.txt
├── CMakeUserPresets.json
├── README.md
├── cmake
│   ├── CompilerWarnings.cmake
│   ├── GenerateAndInstallConfig.cmake
│   ├── InterviewPracticeQuestionsConfig.cmake.in
│   ├── ProjectOptions.cmake
│   ├── StandardProjectSettings.cmake
│   └── StaticAnalysers.cmake
├── src
│   ├── anagram
│   │   ├── CMakeLists.txt
│   │   ├── anagram.cpp
│   │   └── include
│   │       └── anagram.hpp
└── test
    ├── CMakeLists.txt
    └── anagram
        ├── CMakeLists.txt
        └── anagram_test.cpp

Within src I envision to have numerous subdirectories for each individual software component, which in turn will be wrapped up as a CMake target. I've chosen then to closely encapsulate any associated headers within their respective subdirectories, rather than abstract all headers into a root include directory.

This isn't a classical approach, but I have little reason to share these headers across any other libraries or targets in the project, so it makes little sense to fragment my code without any sound rationality behind that decision.

Root CMakeLists.txt

As the root CMakeLists.txt is the first port of call for a new user, first impressions count. It defines the project's fundamentals, its metadata and any high-level configuration. I like to keep this file succinct and targeted. Anything falling outside of its purview can be abstracted away elsewhere (namely the cmake subdirectory).

Indeed, in my CMakeLists.txt I include three such CMake files, namely:

# Set standard project settings

# set project options

# set static analysers


This file is straightforward for the most part. The first portion of the file concerns itself with defining the default built type to Release and specifying the output directories for executables and libraries respectively. What's more interesting is what follows.

For the purposes of compilation caching, I decided upon integrating the ccache tool:

# Include CCache for compilation caching if available
find_program(CCACHE_PROGRAM ccache)
    message("using ccache")
    message("ccache not available")

The intention of using ccache is in speeding up the build time by caching compilation results. Its mechanism is elementary to follow; it mitigates redudant compilation requests, by inspecting whether cached object files can be rendered in lieu of re-compilation.

Further along, I also choose to allow for the express inclusion of interprocedural optimisation (IPO) techniques if available for the compiler:

# Include Interprocedural Optimisation

# Enable Interprocedural Optimisation if available
check_ipo_supported(RESULT result OUTPUT output)
    message("using interprocedural optimisation")
    message(SEND_ERROR "IPO not available: ${output}")

For the uninitiated, IPO is a collection of compiler optimisation techniques used to improve performance on a project wide basis. It optimises code using a variety of approaches, such as inlining functions, dead code elimination (DCE), reducing redundancy, reordering routines for better locality .etc.

Next up I include yet another file, called GenerateAndInstallConfig.cmake which does exactly what it says on the tin. It's purpose is to generate and install the standard package configuration files for the project by leveraging a very useful module called CMakePackageConfigHelpers to provide the necessary utilities. Creating such files ensures the project can be seamlessly integrated as a dependency in external projects via the find_package() command:

# Include package configuration helper module

The first code block generates the package configuration file (i.e. InterviewPracticeQuestionsConfig.cmake) based on the input template file (i.e. InterviewPracticeQuestionsConfig.cmake.in) I have defined in my cmake subdirectory:

# Generate package config files

This 'blueprint' InterviewPracticeQuestionsConfig.cmake.in file contains the following:




Note that in the configure_package_config_file() step then, the placeholders in the above template file will be initialised with actual project-specific information during the CMake configuration step.

The second code block will then generate the InterviewPracticeQuestionsConfigVersion.cmake file that includes the versioning information for the package:

# Generate package version file
    COMPATIBILITY AnyNewerVersion

And last but not least, the final code block is concerned with installing the above configuration files to their specified destinations:

# Install package config files
    COMPONENT config

Finally then, I configure CPack; the package tool provided by CMake. Since I've installation rules already defined inside my build tree (i.e. INSTALL_* for my targets), the project has packaging support via CPack inherently.

When CPack is invoked then, it will find these installation directives specified in the project, and automatically generate the distribution packages required.

All I have to do is set some variables with some basic metadata for CPack support:

# Configure CPack


The ProjectOptions.cmake is a very neat little CMake file that defines an INTERFACE library called ProjectOptions:

# Create an interface library for project options
add_library(ProjectOptions INTERFACE)

While the PUBLIC and PRIVATE keywords are easily understood, the INTERFACE keyword can oftentimes leave people reaching for the documentation. Put simply, it's just a library that doesn't produce any build artefacts (e.g. object files or binaries). Rather its purpose is to define its own properties that other targets can link against and consume.

The ProjectOptions library here is a very good example of this use-case in action. Within my ProjectOptions library, I'm encapsulating all the specific options for my project that I'd like to propagate across all my project's targets. So whenever a target within src links to ProjectOptions it will inherit these properties.

In conclusion then, it's a very simple and clean mechanism to share a consistent set of global properties to all project targets.

I follow on then by calling a function called set_project_warnings() defined in CompilerWarnings.cmake to associate compiler warnings with the ProjectOptions library:

# Enable compiler warnings


And finally, this is yet another simple CMake file that adds the common static anaylsis tools, clang-tidy and cppcheck to the project:

# Include clang-tidy if available
find_program(CLANGTIDY clang-tidy)
    message("using clang-tidy")
    message(SEND_ERROR "clang-tidy not available")

# Include cppcheck if available
find_program(CPPCHECK cppcheck)
    message("using cppcheck")
    message(SEND_ERROR "cppcheck not available")

Source Code

As I introduced in the beginning, I'm encapsulating individual software components within subdirectories under src that define their own named target. To take the anagram target as an example, its CMakeLists.txt file is defined as follows:

# Create anagram library
add_library(Anagram anagram.cpp)

# Add include directories for building and installing anagram
target_include_directories(Anagram PUBLIC  

# add project options
target_link_libraries(Anagram PRIVATE ProjectOptions)

# Include module for GNU standard installation directories

# Install library and executable and export as a set
    EXPORT AnagramExportSet

# Install the export set
install(EXPORT AnagramExportSet
    FILE AnagramTargets.cmake
    NAMESPACE Anagram::

This is none too dissimilar to any prior CMake syntax I've introduced thus far. It defines the Anagram library and links to the ProjectOptions interface library that I've previously described in depth.

The target_include_directories() command may look slightly unusual to some, as it configures the include directories for the Anagram target for both the build and installation processes:

# Add include directories for building and installing anagram
target_include_directories(Anagram PUBLIC  

The syntax is a little obscure, but it's not too difficult to dicipher. To put simply, during build time, the Anagram target will include files from the build interface (i.e. ${CMAKE_CURRENT_SOURCE_DIR}/include> subdirectory). However, during installation, the headers from the local include subdirectory will be placed in the installation include directory. This ensures they're accessible to reference in other projects when using the Anagram as an installed library elsewhere.

Another CMake nugget that might be unfamiliar is the inclusion of the GNUInstallDirs module:

# Include module for GNU standard installation directories

This is quite helpful as it predefines variables specifying the installation directories following the GNU standards.

So rather than explicitly listing destinations in a manual fashion like this:

install(TARGETS Anagram EXPORT AnagramExportSet

Instead with GNUInstallDirs it will implicitly choose the appropriate destinations conforming to the GNU standard convention:

# Include module for GNU standard installation directories

# Install library and executable and export as a set
    # note no need to explicitly list any destination paths here
    EXPORT AnagramExportSet

In short then, it's simply a more robust and consistent method of ensuring that all artefacts and files are installed in commonly accepted locations.

Test Code

So with all the configuration and build stuff out of the way, it should now be possible to write some unit tests to validate the codebase.

As is conventional, I have a test subdirectory at the base of the project to encase all said tests. The base CMakelists.txt for the test subdirectory is straightfoward too:

# Locate Google Test
find_package(GTest REQUIRED)

# Include Google Test module

# Add tests

The find_package(GTest REQUIRED) and include(GoogleTest) can appear tautological at first glance, but they serve different purposes.

For starters, the find_package(GTest REQUIRED) command is used to locate and configure the GTest package, making it available to the project. The include(GoogleTest) directive then is used to include the CMake GoogleTest module, which in turn contains additional function definitions for the Google Test infrastructure.

One such definition is the new gtest_discover_tests() command that's introduced by this module. Typically, new tests would previously have been registered using add_test() or gtest_add_tests().

The latest gtest_discover_tests() differs slightly from gtest_add_tests() in that it automatically discovers tests using CTest by requesting the compiled test binaries to enumerate their tests. This strategy is more robust and offers imporved handling of parameterised tests. Since test discovery occurs at build time, it also removes the need for CMake to be re-run when tests are changed.

The use of gtest_discover_tests() is evident in test/anagram/CMakeLists.txt for example:

# Create test executable
add_executable(anagram_test anagram_test.cpp)

# Link test executable to dependent libraries

# Enable test discovery

Note from above that I'm linking my test binary against the GTest::gtest_main library too; the CMake target imported from the Google Test framework. This is a convenient mechanism to include the main function that initialises the testing environment and executes the tests.

Now, with test cases defined in anagram_test.cpp and things compiled, it's possible to list all available tests using ctest --show-only like so:

Test project /Users/gregorykelleher/Documents/interview_practice_questions/build
  Test #1: ExtractWordsTest.HandlesEmptyString
  Test #2: ExtractWordsTest.HandlesSingleWord
  Test #3: ExtractWordsTest.HandlesMultipleWords
  Test #4: ExtractWordsTest.HandlesRepeatedLetters
  Test #5: FindAnagramTest.HandlesEmptyInputs
  Test #6: FindAnagramTest.NoAnagramsInEmptyVector
  Test #7: FindAnagramTest.NoAnagramsInVector
  Test #8: FindAnagramTest.OneAnagramInVector

Total Tests: 8

For those unaware, it's also possible to run tests in parallel using ctest -j N where N is the desired number of threads


Underpinning this entire project is the Conan package manager. It's responsible for including and installing all of the above dependencies, such as GTest, CMake, CCache and CppCheck. All of this configuration is described in the root conanfile.py recipe as follows:

"""Conan package definition for Interview Practice Questions"""

from conan import ConanFile
from conan.tools.cmake import CMake, CMakeToolchain, CMakeDeps, cmake_layout
from conan.tools.build import check_min_cppstd

class InterviewPracticeQuestions(ConanFile):

    name = "interview_practice_questions"
    version = "1.0"
    label = "interview practice questions package"

    settings = "os", "arch", "compiler", "build_type"

    exports_sources = "CMakeLists.txt", "cmake/*", "src/*", "test/*"

    def build_requirements(self):

    def validate(self):
        check_min_cppstd(self, "20")

    def layout(self):

    def generate(self):

    def build(self):
        cmake = CMake(self)

    def package(self):
        cmake = CMake(self)

Since this is a CMake project of course, I'm including the necessary modules I need at the top of the conanfile.py file:


Responsible for generating the CMake config files for all required dependencies of the package. In other words, it enables the use of the CMake find_package() command to locate required dependency packages.


Generates a toolchain file for CMake that contains build information for CMake. This toolchain file can then be used in the command line invocation of CMake with -DCMAKE_TOOLCHAIN_FILE=conan_toolchain.cmake.


Build helper tool used by Conan to invoke CMake, passing whatever arguments specified such as the toolchain file, build type file and any definitions set in the recipe.

Conan Invocation

To invoke conan and install the dependencies outlined in the conanfile.py it's simply a matter of executing:

conan install . --output-folder=build --build=missing

This command will resolve the dependencies listed, fetch the specified packages and create the necessary build configurations, outputting everything to the build subdirectory.

Now everything is prepared to initiate a CMake build within the build tree using the generated Conan toolchain file:

cd build
cmake ..  -DCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE=build/Release/generators/conan_toolchain.cmake
cmake --build . --config Release

It's really as easy as that. Conan is a game-changer when it comes to setting up projects and their dependencies in this fashion.


Hopefully this post has gone some way in demonstrating my approach in defining a useful template for C++ project structuring. I've navigated a whole host of different topics, and in reflection now, it's really quite overwhelming for a beginner. That said, when embraced properly, CMake, Conan and CTest can vastly enhance a project, taming complexity and fostering maintainability.

It does take some strategic orchestration of tooling to craft such a development environment, but it pays dividends in the long run. A scalable and efficient project with readable configurations sets a stable foundation on which to build a codebase.

In essence then, while the initial learning curve may be rather steep, the rewards justify the investments made in my opinion. Adopting these modern tools can truly evelate a project's trajectory and set it down a course of future success.

Date: December 15th at 2:31pm