STL

MSVC's implementation of the C++ Standard Library.

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Quick Overview

The microsoft/STL repository is Microsoft's implementation of the C++ Standard Library. It provides the core components and algorithms used in C++ programming, including containers, iterators, and utility functions. This implementation is used in Microsoft Visual C++ and is now open-source for community contributions and improvements.

Pros

High-performance implementation optimized for Windows platforms
Regular updates and maintenance by Microsoft's C++ team
Open-source, allowing for community contributions and customizations
Extensive testing and compatibility with Microsoft's C++ compiler

Cons

Primarily focused on Windows platforms, potentially limiting cross-platform compatibility
May have some differences from other STL implementations, affecting portability
Learning curve for contributors due to the complexity of the codebase
Requires Visual Studio for building and testing on Windows

Code Examples

Using a vector container:

#include <vector>
#include <iostream>

int main() {
    std::vector<int> numbers = {1, 2, 3, 4, 5};
    for (const auto& num : numbers) {
        std::cout << num << " ";
    }
    return 0;
}

Utilizing an algorithm (std::find):

#include <algorithm>
#include <vector>
#include <iostream>

int main() {
    std::vector<int> numbers = {10, 20, 30, 40, 50};
    auto it = std::find(numbers.begin(), numbers.end(), 30);
    if (it != numbers.end()) {
        std::cout << "Found: " << *it << std::endl;
    }
    return 0;
}

Working with strings:

#include <string>
#include <iostream>

int main() {
    std::string greeting = "Hello, ";
    greeting += "world!";
    std::cout << greeting << std::endl;
    return 0;
}

Getting Started

To use Microsoft's STL implementation:

Install Visual Studio with C++ support.
Create a new C++ project in Visual Studio.
Include the necessary headers in your code (e.g., <vector>, <algorithm>).
Write your C++ code using STL components.
Build and run your project.

For contributors:

git clone https://github.com/microsoft/STL.git
cd STL
cmake -B out/build -S . -G "Visual Studio 16 2019" -A x64
cmake --build out/build

This clones the repository, generates build files, and builds the project using CMake and Visual Studio 2019.

Competitor Comparisons

boost

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Super-project for modularized Boost

Pros of Boost

Broader scope with a vast collection of libraries beyond just the standard template library
Cross-platform support for multiple compilers and operating systems
Active community with frequent updates and contributions

Cons of Boost

Larger footprint and potential overhead due to its extensive feature set
Steeper learning curve for newcomers due to its size and complexity
Some components may become outdated as they're incorporated into the C++ standard

Code Comparison

STL (vector initialization):

#include <vector>
std::vector<int> v = {1, 2, 3, 4, 5};

Boost (using Boost.Array):

#include <boost/array.hpp>
boost::array<int, 5> arr = {1, 2, 3, 4, 5};

Both libraries provide essential functionality for C++ development, but they serve different purposes. STL focuses on providing a standardized set of containers, algorithms, and utilities, while Boost offers a wider range of libraries that extend beyond the standard library's scope. STL is typically more lightweight and comes bundled with most C++ compilers, making it a go-to choice for standard operations. Boost, on the other hand, excels in providing additional features and cross-platform compatibility, making it valuable for more specialized or advanced use cases.

llvm-project

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The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.

Pros of LLVM Project

Broader scope: Includes compiler infrastructure, tools, and libraries beyond just the C++ standard library
Larger community and more frequent updates
Cross-platform support for multiple programming languages

Cons of LLVM Project

More complex and potentially overwhelming for newcomers
Larger codebase may lead to longer build times
Less focused on Microsoft-specific optimizations

Code Comparison

STL (Microsoft):

template <class _Ty>
struct remove_reference {
    using type = _Ty;
};

LLVM Project:

template<typename _Tp>
struct remove_reference
{ typedef _Tp   type; };

Summary

While STL focuses specifically on the C++ Standard Template Library implementation for Microsoft platforms, LLVM Project offers a more comprehensive suite of compiler and toolchain components. STL may be more suitable for developers working primarily with Microsoft technologies, while LLVM Project provides broader language and platform support. The code comparison shows similar implementations of type traits, with minor syntactic differences.

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Pros of Abseil

Broader platform support, including non-Windows systems
More frequent updates and active community development
Additional utilities and data structures not found in the standard library

Cons of Abseil

Larger codebase and potential overhead
Less integrated with Microsoft-specific toolchains and ecosystems
May require additional setup and configuration compared to STL

Code Comparison

STL (vector initialization):

#include <vector>
std::vector<int> v = {1, 2, 3, 4, 5};

Abseil (vector initialization with inlined lambda):

#include "absl/container/inlined_vector.h"
absl::InlinedVector<int, 5> v = {1, 2, 3, 4, 5};

Summary

STL is a Microsoft-maintained implementation of the C++ Standard Library, focusing on Windows platforms and integration with Microsoft tools. Abseil, developed by Google, offers a broader range of utilities and platform support but may require more setup. STL is more tightly integrated with Microsoft ecosystems, while Abseil provides additional features and more frequent updates. The choice between them depends on project requirements, target platforms, and desired feature set.

folly

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An open-source C++ library developed and used at Facebook.

Pros of Folly

Broader scope with utilities beyond standard C++ library
Optimized for high-performance, large-scale systems
Active development with frequent updates

Cons of Folly

Steeper learning curve due to extensive features
Potentially larger binary size when including the library
May introduce dependencies on Facebook's ecosystem

Code Comparison

STL (vector initialization):

std::vector<int> vec = {1, 2, 3, 4, 5};

Folly (dynamic vector):

folly::dynamic vec = folly::dynamic::array(1, 2, 3, 4, 5);

Key Differences

STL focuses on standard C++ containers and algorithms
Folly extends beyond standard library with additional utilities
STL is part of the C++ standard, while Folly is a third-party library
Folly includes more specialized data structures and concurrency primitives

Use Cases

STL: General-purpose C++ development, cross-platform compatibility
Folly: High-performance systems, large-scale applications, Facebook-specific projects

Community and Support

STL: Widely adopted, extensive documentation, part of C++ standard
Folly: Growing community, Facebook-backed, detailed documentation available

googletest

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GoogleTest - Google Testing and Mocking Framework

Pros of GoogleTest

Extensive testing framework with support for various test types (unit, integration, etc.)
Cross-platform compatibility and easy integration with CI/CD pipelines
Rich set of assertions and matchers for flexible test case creation

Cons of GoogleTest

Steeper learning curve for beginners compared to STL's simpler structure
Larger codebase and potential overhead for small projects
May require additional setup and configuration for complex test scenarios

Code Comparison

STL (vector initialization):

#include <vector>
std::vector<int> v = {1, 2, 3, 4, 5};

GoogleTest (basic test case):

#include <gtest/gtest.h>
TEST(ExampleTest, AdditionWorks) {
  EXPECT_EQ(2 + 2, 4);
}

Summary

While STL provides essential C++ standard library components, GoogleTest focuses on comprehensive testing capabilities. STL is more lightweight and integral to C++ development, whereas GoogleTest offers robust testing features but may introduce additional complexity. The choice between them depends on project requirements, with STL being fundamental for C++ programming and GoogleTest excelling in test-driven development scenarios.

fmt

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A modern formatting library

Pros of fmt

Lightweight and header-only library, easy to integrate
Cross-platform compatibility (Windows, macOS, Linux)
Faster compilation times compared to STL

Cons of fmt

Smaller community and ecosystem compared to STL
Less comprehensive feature set than STL's full standard library
May require additional dependencies in some cases

Code Comparison

STL (iostream):

#include <iostream>
#include <string>

std::string name = "Alice";
int age = 30;
std::cout << "Name: " << name << ", Age: " << age << std::endl;

fmt:

#include <fmt/core.h>
#include <string>

std::string name = "Alice";
int age = 30;
fmt::print("Name: {}, Age: {}\n", name, age);

The fmt library offers a more concise and readable syntax for formatting output, while STL's iostream provides a more familiar approach for C++ developers. fmt's syntax is similar to Python's string formatting, which some developers find more intuitive. However, STL's iostream is part of the standard library and doesn't require additional dependencies.

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README

Microsoft's C++ Standard Library

This is the official repository for Microsoft's implementation of the C++ Standard Library (also known as the STL), which ships as part of the MSVC toolset and the Visual Studio IDE.

Our Changelog tracks which updates to this repository appear in each VS release.
Our Status Chart displays our overall progress over time.
Join our Discord server.
(STL-CI build status)
(STL-ASan-CI build status)

What This Repo Is Useful For

If you're a programmer who just wants to use the STL, you don't need this repo. Simply install the Visual Studio IDE and select the "Desktop development with C++" workload.

If you want to participate in the STL's development, welcome! You can report issues, comment on pull requests, and learn about what we're working on. You can also submit pull requests to fix bugs or add features: see CONTRIBUTING.md for more information.

Finally, you can take our code and use it in other apps and libraries (according to the terms of our license, like everything else).

GitHub Migration Status

We're in the process of moving all of our work on the STL to GitHub. Current status:

Code: Done. Our source code is available under the Apache License v2.0 with LLVM Exception. (See LICENSE.txt and NOTICE.txt for more information.)
Build System: In progress. We're working on a CMake build system, which is currently capable of building one flavor of the STL (native desktop). We need to extend this to build all of the flavors required for the MSVC toolset (e.g. /clr, /clr:pure, OneCore, Spectre). Until that's done, we're keeping our legacy build system around in the stl/msbuild subdirectory. (We're keeping those files in this repo, even though they're unusable outside of Microsoft, because they need to be updated whenever source files are added/renamed/deleted. We'll delete the legacy machinery as soon as possible.)
Tests: In progress. We rely on three test suites: std, tr1, and libcxx. We've partially ported std and tr1, and fully ported libcxx to run under lit using the various configurations/compilers we test internally.
Continuous Integration: In progress. We've set up Azure Pipelines to validate changes to the repository. Currently, it builds the STL (native desktop for x86, x64, ARM, and ARM64). Also, it strictly verifies that all of our files have been formatted with clang-format and follow our other whitespace conventions.
Contribution Guidelines: Coming soon. Working on the STL's code involves following many rules. We have codebase conventions, Standard requirements, Microsoft-specific requirements, binary compatibility (ABI) requirements, and more. We're eager to begin accepting features and fixes from the community, but in addition to setting up a CI system, we need to write down all of the rules that are currently stored in our brains. (The ABI rules may be useful to other C++ libraries.)
Issues: In progress. We're going to use GitHub issues to track all of the things that we need to work on. This includes C++20 features, LWG issues, conformance bugs, performance improvements, and other todos. There are approximately 200 active bugs in the STL's Microsoft-internal database; we need to manually replicate all of them to GitHub issues. Currently, the cxx20 tag and LWG tag are done; every remaining work item is tracked by a GitHub issue. The bug tag and enhancement tag are being populated.
Plans: In progress. We're writing up our Roadmap.

Goals

We're implementing the latest C++ Working Draft, currently N4988, which will eventually become the next C++ International Standard. The terms Working Draft (WD) and Working Paper (WP) are interchangeable; we often informally refer to these drafts as "the Standard" while being aware of the difference. (There are other relevant Standards; for example, supporting /std:c++14 and /std:c++17 involves understanding how the C++14 and C++17 Standards differ from the Working Paper, and we often need to refer to the C Standard Library and ECMAScript regular expression specifications.)

Our primary goals are conformance, performance, usability, and compatibility.

Conformance: The Working Paper is a moving target; as features and LWG issue resolutions are added, we need to implement them. That can involve a lot of work because the STL is required to behave in very specific ways and to handle users doing very unusual things.
Performance: The STL needs to be extremely fast at runtime; speed is one of C++'s core strengths and most C++ programs use the STL extensively. As a result, we spend more time on optimization than most general-purpose libraries. (However, we're wary of changes that improve some scenarios at the expense of others, or changes that make code significantly more complicated and fragile. That is, there's a "complexity budget" that must be spent carefully.)
Usability: This includes parts of the programming experience like compiler throughput, diagnostic messages, and debugging checks. For example, we've extensively marked the STL with [[nodiscard]] attributes because this helps programmers avoid bugs.
Compatibility: This includes binary compatibility and source compatibility. We're keeping VS 2022 binary-compatible with VS 2015/2017/2019, which restricts what we can change in VS 2022 updates. (We've found that significant changes are possible even though other changes are impossible, which we'll be documenting in our Contribution Guidelines soon.) While there are a few exceptions to this rule (e.g. if a feature is added to the Working Paper, we implement it, and then the feature is significantly changed before the International Standard is finalized, we reserve the right to break binary compatibility because /std:c++latest offers an experimental preview of such features), binary compatibility generally overrides all other considerations, even conformance. Source compatibility refers to being able to successfully recompile user code without changes. We consider source compatibility to be important, but not all-important; breaking source compatibility can be an acceptable cost if done for the right reasons in the right way (e.g. in a controlled manner with escape hatches).

Non-Goals

There are things that we aren't interested in doing with this project, for various reasons (most importantly, we need to focus development effort on our goals). Some examples:

Non-goal: Porting to other platforms.
Non-goal: Adding non-Standard extensions.
Non-goal: Implementing Technical Specifications. (We're prioritizing features in the Working Paper. Occasionally, we might implement some or all of a TS, often when we're working on the specification itself.)

If you're proposing a feature to WG21 (the C++ Standardization Committee), you're welcome (and encouraged!) to use our code as a base for a proof-of-concept implementation. These non-goals simply mean that we're unable to consider pull requests for a proposed feature until it has been voted into a Working Paper. After that happens, we'll be delighted to review a production-ready pull request.

Reporting Issues

You can report STL bugs here, where they'll be directly reviewed by maintainers. You can also report STL bugs through Developer Community, or the VS IDE (Help > Send Feedback > Report a Problem...).

Please help us efficiently process bug reports by following these rules:

Only STL bugs should be reported here. If it's a bug in the compiler, CRT, or IDE, please report it through Developer Community or Report A Problem. If it's a bug in the Windows SDK, please report it through the Feedback Hub app. If you aren't sure, try to reduce your test case and see if you can eliminate the STL's involvement while still reproducing the bug.
You should be reasonably confident that you're looking at an actual implementation bug, instead of undefined behavior or surprising-yet-Standard behavior. Comparing against other implementations can help (but remember that implementations can differ while conforming to the Standard); try Compiler Explorer. If you still aren't sure, ask the nearest C++ expert.
You should prepare a self-contained command-line test case, ideally as small as possible. We need a source file, a command line, what happened (e.g. a compiler error, runtime misbehavior), and what you expected to happen. By "self-contained", we mean that your source file has to avoid including code that we don't have. Ideally, only CRT and STL headers should be included. If you have to include other MSVC libraries, or the Windows SDK, to trigger an STL bug, that's okay. But if you need parts of your own source code to trigger the STL bug, you need to extract that for us. (On Developer Community, we'll accept zipped IDE projects if you have no other way to reproduce a bug, but this is very time-consuming for us to reduce.)
A good title is helpful. We prefer "<header_name>: Short description of your issue". You don't usually need to mention std:: or C++. For example, "<type_traits>: is_cute should be true for enum class FluffyKittens".

It's okay if you report an apparent STL bug that turns out to be a compiler bug or surprising-yet-Standard behavior. Just try to follow these rules, so we can spend more time fixing bugs and implementing features.

How To Build With The Visual Studio IDE

Install Visual Studio 2022 17.12 Preview 1 or later.
- Select "Windows 11 SDK (10.0.22621.0)" in the VS Installer.
- Select "MSVC v143 - VS 2022 C++ ARM64/ARM64EC build tools (Latest)" in the VS Installer if you would like to build the ARM64/ARM64EC target.
- Select "MSVC v143 - VS 2022 C++ ARM build tools (Latest)" in the VS Installer if you would like to build the ARM target.
- We recommend selecting "C++ CMake tools for Windows" in the VS Installer. This will ensure that you're using supported versions of CMake and Ninja.
- Otherwise, install CMake 3.29.0 or later, and Ninja 1.12.1 or later.
- Make sure Python 3.12 or later is available to CMake.
Open Visual Studio, and choose the "Clone or check out code" option. Enter the URL of this repository, https://github.com/microsoft/STL.
Open a terminal in the IDE with Ctrl + ` (by default) or press on "View" in the top bar, and then "Terminal".
In the terminal, invoke git submodule update --init --progress
Choose the architecture you wish to build in the IDE, and build as you would any other project. All necessary CMake settings are set by CMakePresets.json.

How To Build With A Native Tools Command Prompt

Install Visual Studio 2022 17.12 Preview 1 or later.
- Select "Windows 11 SDK (10.0.22621.0)" in the VS Installer.
- Select "MSVC v143 - VS 2022 C++ ARM64/ARM64EC build tools (Latest)" in the VS Installer if you would like to build the ARM64/ARM64EC target.
- Select "MSVC v143 - VS 2022 C++ ARM build tools (Latest)" in the VS Installer if you would like to build the ARM target.
- We recommend selecting "C++ CMake tools for Windows" in the VS Installer. This will ensure that you're using supported versions of CMake and Ninja.
- Otherwise, install CMake 3.29.0 or later, and Ninja 1.12.1 or later.
- Make sure Python 3.12 or later is available to CMake.
Open a command prompt.
Change directories to a location where you'd like a clone of this STL repository.
git clone https://github.com/microsoft/STL.git --recurse-submodules

To build the x86 target:

Open an "x86 Native Tools Command Prompt for VS 2022 Preview".
Change directories to the previously cloned STL directory.
cmake --preset x86
cmake --build --preset x86

To build the x64 target (recommended):

Open an "x64 Native Tools Command Prompt for VS 2022 Preview".
Change directories to the previously cloned STL directory.
cmake --preset x64
cmake --build --preset x64

To build the ARM target:

"C:\Program Files\Microsoft Visual Studio\2022\Preview\VC\Auxiliary\Build\vcvarsall.bat" x64_arm
- If you installed VS to a non-default location, change this path accordingly.
Change directories to the previously cloned STL directory.
cmake --preset ARM
cmake --build --preset ARM

To build the ARM64 target:

"C:\Program Files\Microsoft Visual Studio\2022\Preview\VC\Auxiliary\Build\vcvarsall.bat" x64_arm64
- If you installed VS to a non-default location, change this path accordingly.
Change directories to the previously cloned STL directory.
cmake --preset ARM64
cmake --build --preset ARM64

To build the ARM64EC target:

"C:\Program Files\Microsoft Visual Studio\2022\Preview\VC\Auxiliary\Build\vcvarsall.bat" x64_arm64
- If you installed VS to a non-default location, change this path accordingly.
Change directories to the previously cloned STL directory.
cmake --preset ARM64EC
cmake --build --preset ARM64EC

How To Consume

Consumption of the built library is largely based on the build system you're using. There are at least 2 directories you need to hook up. Assuming you built the x64 target with the Visual Studio IDE, with the STL repository cloned to C:\Dev\STL, build outputs will end up at C:\Dev\STL\out\x64\out. Ensure that the inc directory is searched for headers, and that lib\{architecture} is searched for link libraries, before any defaults supplied by MSVC. The names of the import and static libraries are the same as those that ship with MSVC. As a result, the compiler /MD, /MDd, /MT, or /MTd switches will work without modification of your build scripts or command-line muscle memory.

Should you choose to use the DLL flavors, the DLLs to deploy are built to bin\{architecture}. Note that the DLLs generated by the CMake build system here have a suffix, defaulting to _oss, which distinguishes them from the binaries that ship with MSVC. That avoids any conflict with the DLLs installed by the redistributables into System32 and ensures that other components wanting to be a "guest in your process", like print drivers and shell extensions, see the export surface of the STL they were built with. Otherwise, the "msvcp140.dll" you deployed in the same directory as your .exe would "win" over the versions in System32.

The compiler looks for include directories according to the INCLUDE environment variable, and the linker looks for import library directories according to the LIB environment variable, and the Windows loader will (eventually) look for DLL dependencies according to directories in the PATH environment variable. The build generates a batch script named set_environment.bat in the output directory. If you run this script in a VS Developer Command Prompt, it will insert the proper directories into the INCLUDE, LIB, and PATH environment variables to ensure that the built headers and libraries are used.

Complete Example Using x64 DLL Flavor

From an "x64 Native Tools Command Prompt for VS 2022 Preview":

C:\Users\username\Desktop>C:\Dev\STL\out\x64\set_environment.bat

C:\Users\username\Desktop>type example.cpp
#include <iostream>

int main() {
    std::cout << "Hello STL OSS world!\n";
}

C:\Users\username\Desktop>cl /nologo /EHsc /W4 /WX /MDd /std:c++latest .\example.cpp
example.cpp

C:\Users\username\Desktop>.\example.exe
Hello STL OSS world!

C:\Users\username\Desktop>dumpbin /DEPENDENTS .\example.exe | findstr msvcp
    msvcp140d_oss.dll

How To Run The Tests With A Native Tools Command Prompt

Follow either How To Build With A Native Tools Command Prompt or How To Build With The Visual Studio IDE.
Acquire Python 3.12 or newer and have it on the PATH (or run it directly using its absolute or relative path).
Have LLVM's bin directory on the PATH (so clang-cl.exe is available).
- We recommend selecting "C++ Clang tools for Windows" in the VS Installer. This will automatically add LLVM to the PATH of the x86 and x64 Native Tools Command Prompts, and will ensure that you're using a supported version.
- Otherwise, use LLVM's installer and choose to add LLVM to your PATH during installation.
Follow the instructions below.

Running All The Tests

After configuring and building the project, running ctest from the build output directory will run all the tests. CTest will only display the standard error output of tests that failed. In order to get more details from CTest's lit invocations, run the tests with ctest -V.

Running A Subset Of The Tests

${PROJECT_BINARY_DIR}\tests\utils\stl-lit\stl-lit.py can be invoked on a subdirectory of a test suite and will execute all the tests under that subdirectory. This can mean executing the entirety of a single test suite, running all tests under a category in libcxx, or running a single test in std and tr1.

Examples

These examples assume that your current directory is C:\Dev\STL\out\x64.

This command will run all of the test suites with verbose output.
- ctest -V
This command will also run all of the test suites.
- python tests\utils\stl-lit\stl-lit.py ..\..\llvm-project\libcxx\test ..\..\tests\std ..\..\tests\tr1
This command will run all of the std test suite.
- python tests\utils\stl-lit\stl-lit.py ..\..\tests\std
If you want to run a subset of a test suite, you need to point it to the right place in the sources. The following will run the single test found under VSO_0000000_any_calling_conventions.
- python tests\utils\stl-lit\stl-lit.py ..\..\tests\std\tests\VSO_0000000_any_calling_conventions
You can invoke stl-lit with any arbitrary subdirectory of a test suite. In libcxx this allows you to have finer control over what category of tests you would like to run. The following will run all the libcxx map tests.
- python tests\utils\stl-lit\stl-lit.py ..\..\llvm-project\libcxx\test\std\containers\associative\map
You can also use the --filter option to include tests whose names match a regular expression. The following command will run tests with "atomic_wait" in their names in both the std and libcxx test suites.
- python tests\utils\stl-lit\stl-lit.py ..\..\llvm-project\libcxx\test ..\..\tests\std --filter=atomic_wait
There's also a --filter-out option to exclude tests matching a regular expression; --filter=iota --filter-out=view would run tests with names matching "iota" but not "view".

Interpreting The Results Of Tests

CTest

When running the tests via CTest, all of the test suites are considered to be a single test. If any single test in a test suite fails, CTest will simply report that the stl test failed.

Example:

0% tests passed, 1 tests failed out of 1

Total Test time (real) = 2441.55 sec

The following tests FAILED:
      1 - stl (Failed)

The primary utility of CTest in this case is to conveniently invoke stl-lit.py with the correct set of arguments.

CTest will output everything that was sent to stderr for each of the failed test suites, which can be used to identify which individual test within the test suite failed. It can sometimes be helpful to run CTest with the -V option in order to see the stdout of the tests.

stl-lit

When running the tests directly via the generated stl-lit.py script the result of each test will be printed. The format of each result is {Result Code}: {Test Suite Name} :: {Test Name}:{Configuration Number}.

Example:

-- Testing: 28 tests, 12 workers --
PASS: tr1 :: tests/cwchar1:01 (1 of 28)
PASS: tr1 :: tests/cwchar1:11 (2 of 28)
PASS: tr1 :: tests/cwchar1:02 (3 of 28)
PASS: tr1 :: tests/cwchar1:03 (4 of 28)
PASS: tr1 :: tests/cwchar1:00 (5 of 28)
PASS: tr1 :: tests/cwchar1:04 (6 of 28)
PASS: tr1 :: tests/cwchar1:05 (7 of 28)
PASS: tr1 :: tests/cwchar1:09 (8 of 28)
PASS: tr1 :: tests/cwchar1:06 (9 of 28)
UNSUPPORTED: tr1 :: tests/cwchar1:20 (10 of 28)
UNSUPPORTED: tr1 :: tests/cwchar1:21 (11 of 28)
UNSUPPORTED: tr1 :: tests/cwchar1:22 (12 of 28)
UNSUPPORTED: tr1 :: tests/cwchar1:23 (13 of 28)
UNSUPPORTED: tr1 :: tests/cwchar1:24 (14 of 28)
PASS: tr1 :: tests/cwchar1:07 (15 of 28)
PASS: tr1 :: tests/cwchar1:08 (16 of 28)
PASS: tr1 :: tests/cwchar1:10 (17 of 28)
PASS: tr1 :: tests/cwchar1:16 (18 of 28)
PASS: tr1 :: tests/cwchar1:17 (19 of 28)
PASS: tr1 :: tests/cwchar1:14 (20 of 28)
PASS: tr1 :: tests/cwchar1:12 (21 of 28)
PASS: tr1 :: tests/cwchar1:13 (22 of 28)
PASS: tr1 :: tests/cwchar1:19 (23 of 28)
PASS: tr1 :: tests/cwchar1:18 (24 of 28)
PASS: tr1 :: tests/cwchar1:15 (25 of 28)
PASS: tr1 :: tests/cwchar1:25 (26 of 28)
PASS: tr1 :: tests/cwchar1:26 (27 of 28)
PASS: tr1 :: tests/cwchar1:27 (28 of 28)

Testing Time: 3.96s
  Expected Passes    : 23
  Unsupported Tests  : 5

In the above example, we see that 23 tests succeeded and 5 were unsupported.

Result Code Values

Our tests use the standard lit result codes, and an undocumented result code: SKIPPED. For our tests, only the PASS, XFAIL, XPASS, FAIL, UNSUPPORTED, and SKIPPED result codes are relevant.

The PASS and FAIL result codes are self-explanatory. We want our tests to PASS and not FAIL.

The XPASS and XFAIL result codes are less obvious. XPASS is actually a failure result and indicates that we expected a test to fail but it passed. XFAIL is a successful result and indicates that we expected the test to fail and it did. Typically an XPASS result means that the expected_results.txt file for the test suite needs to be modified. If the XPASS result is a test legitimately passing, the usual course of action would be to remove a FAIL entry from the expected_results.txt. However, some tests from libcxx mark themselves as XFAIL (meaning they expect to fail) for features they have added tests for but have yet to implement in libcxx. If the STL implements those features first the tests will begin passing unexpectedly for us and return XPASS results. In order to resolve this it is necessary to add a PASS entry to the expected_results.txt of the test suite in question.

The UNSUPPORTED result code means that the requirements for a test are not met and so it will not be run. Currently, all tests which use the /clr or /clr:pure options are unsupported. Also, the /BE option is unsupported for x86.

The SKIPPED result code indicates that a given test was explicitly skipped by adding a SKIPPED entry to the expected_results.txt. A test may be skipped for a number of reasons, which include, but are not limited to:

being an incorrect test
taking a very long time to run
failing or passing for the incorrect reason

Debugging Individual Tests

While stl-lit is super awesome in finding out that something is wrong or not even compiling, it is not really helpful in debugging what is going wrong. However, debugging individual tests is rather simple given some additional steps. Let's assume we want to debug a new feature with tests located in tests\std\tests\GH_XXXX_meow.

As always, build the STL from your branch and run the tests:

C:\STL\out\x64> ninja
C:\STL\out\x64> python tests\utils\stl-lit\stl-lit.py -v C:\STL\tests\std\tests\GH_XXXX_meow

Let's assume one of the tests fails an assert and we want to debug that configuration. stl-lit will conveniently print the build command, which is far too long to provide here in full. The important part is to add the following options to provide debug symbols: /Zi /Fdbark.pdb.

You can replace bark with any descriptive name you like. Add these before the "-link" option in the command line and recompile. Example:

C:\STL\out\x64>cl "C:\STL\tests\std\tests\GH_XXXX_meow\test.cpp" [... more arguments ...]
"-FeC:\STL\out\x64\tests\std\tests\GH_XXXX_meow\Output\02\GH_XXXX_meow.exe" /Zi /Fdbark.pdb "-link"
[... more arguments ...]

You can now start debugging the test via:

devenv "C:\STL\out\x64\tests\std\tests\GH_XXXX_meow\Output\02\GH_XXXX_meow.exe"
       "C:\STL\tests\std\tests\GH_XXXX_meow\test.cpp"

However, this might not work right away, as Visual Studio may complain about a missing msvcp140_oss.dll. The reason is that the STL builds those and other DLLs itself and we should under no circumstances overwrite the installed ones. If you are testing one of the configurations with dynamic linkage (/MD or /MDd) the easiest solution is to add the build folder to your path:

set PATH=C:\STL\out\x64\out\bin\amd64;%PATH%

Benchmarking

For performance-sensitive code – containers, algorithms, and the like – you may wish to write and/or run benchmarks, and the STL team will likely run any benchmarks we do have in our PR process. Additionally, if you are writing a "performance improvement" PR, please add and run benchmarks to show that the PR does, in fact, improve performance.

The benchmarking code is located in benchmarks. Adding a new benchmark is as easy as adding a new file to benchmarks/src, and then adding add_benchmark(<name> <source_file>) to benchmarks/CMakeLists.txt. You may also modify an existing benchmark file. We use Google's Benchmark library, so you may find their documentation helpful, and you can also read the existing code for how we use it.

To run benchmarks, you'll need to first build the STL, then build the benchmarks:

cmake --preset x64
cmake --build --preset x64
cmake -B out\bench -S benchmarks -G Ninja -DSTL_BINARY_DIR=out\x64
cmake --build out\bench

You can then run your benchmark with:

out\bench\benchmark-<benchmark-name> --benchmark_out=<file> --benchmark_out_format=csv

And then you can copy this CSV file into Excel, or another spreadsheet program. For example:

out\bench\benchmark-std_copy --benchmark_out=benchmark-std_copy-results.csv --benchmark_out_format=csv

If you want to see all the other flags you can pass, run:

out\bench\benchmark-<benchmark-name> --help

Editing And Testing The Debugger Visualizer

Modify The Visualizer

To modify how components are visualized in the debugger, edit the file stl\debugger\STL.natvis. For more information on how to modify this file, check the natvis documentation.

Test Your Changes

You can add the natvis file to any Visual Studio C++ project if you right-click your project > Add > Existing Item and select the STL.natvis file. After doing this you should be able to see your changes in a Visual Studio debugging session.

Block Diagram

The STL is built atop other compiler support libraries that ship with Windows and Visual Studio, like the UCRT, VCRuntime, and VCStartup. The following diagram describes the dependencies between those components and their ship vehicles.

flowchart TB
%%{ init: {"flowchart": {"htmlLabels": true}} }%%
    classDef default text-align:left
    subgraph VisualStudioSubgraph[Visual Studio]
        direction TB
        STLNode("<b>STL</b>
        This repo; provides C++ Standard Library headers, separately
        compiled implementations of most of the iostreams functionality,
        and a few runtime support components like std::exception_ptr.")
        subgraph VCRuntimeSubgraph[VCRuntime]
            direction TB
            VCStartupNode("<b>VCStartup</b>
            Provides compiler support mechanisms that
            live in each binary; such as machinery to
            call constructors and destructors for global
            variables, the entry point, and the /GS cookie.

            Merged into static and import libraries of VCRuntime.")
            VCRuntimeNode("<b>VCRuntime</b>
            Provides compiler support mechanisms that can be
            shared between binaries; code that the compiler calls
            on your behalf, such as the C++ exception handling
            runtime, string.h intrinsics, math intrinsics, and
            declarations for CPU-vendor-specific intrinsics.")
        end
    end
    subgraph WindowsSDKSubgraph[Windows SDK]
        UniversalCRTNode("<b>Universal CRT</b>
        Windows component that provides C library support, such as printf,
        C locales, and some POSIX-like shims for the Windows API, like _stat.")
    end
    STLNode ==> VCRuntimeSubgraph & UniversalCRTNode
    VCStartupNode ==> VCRuntimeNode ==> UniversalCRTNode

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

See CONTRIBUTING.md for more information.

Code Of Conduct

This project has adopted the Microsoft Open Source Code of Conduct.

See CODE_OF_CONDUCT.md for more information.

License

SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception

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