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Louis Dionne a0839b14df [libc++] Fix tuple assignment from types derived from a tuple-like
The implementation of tuple's constructors and assignment operators
currently diverges from the way the Standard specifies them, which leads
to subtle cases where the behavior is not as specified. In particular, a
class derived from a tuple-like type (e.g. pair) can't be assigned to a
tuple with corresponding members, when it should. This commit re-implements
the assignment operators (BUT NOT THE CONSTRUCTORS) in a way much closer
to the specification to get rid of this bug. Most of the tests have been
stolen from Eric's patch https://reviews.llvm.org/D27606.

As a fly-by improvement, tests for noexcept correctness have been added
to all overloads of operator=. We should tackle the same issue for the
tuple constructors in a future patch - I'm just trying to make progress
on fixing this long-standing bug.

PR17550
rdar://15837420

Differential Revision: https://reviews.llvm.org/D50106
2021-02-22 14:52:18 -05:00
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clang [clang] Tweaked fixit for static assert with no message 2021-02-22 17:43:53 +00:00
clang-tools-extra [clang-tidy] Harden PreferMemberInitializerCheck 2021-02-22 19:41:11 +00:00
compiler-rt Revert "[InstrProfiling] Use ELF section groups for counters, data and values" 2021-02-22 11:13:55 -08:00
debuginfo-tests [debuginfo-tests] Recommit test sret.cpp 2021-02-19 08:45:15 +00:00
flang Making FindCommonBlock a const member 2021-02-22 10:10:11 -08:00
libc [libc] Add implementations of the remaining fenv functions. 2021-02-18 13:29:40 -08:00
libclc
libcxx [libc++] Fix tuple assignment from types derived from a tuple-like 2021-02-22 14:52:18 -05:00
libcxxabi [libc++abi] Add builtins to dynamic library link 2021-02-17 17:05:59 -05:00
libunwind [libunwind] Add support for PC reg column in arm64 2021-02-17 17:42:19 -08:00
lld [lld-macho] Try to fix cross-platform test from D96565 2021-02-22 14:47:45 -05:00
lldb Revert "[lldb-vscode] Emit the breakpoint changed event on location resolved" 2021-02-21 13:08:06 -08:00
llvm [WebAssembly] Misc. fixes in cfg-stackify-eh.ll 2021-02-22 11:49:33 -08:00
mlir Add missing dep to fix shared libs build 2021-02-22 11:36:48 -08:00
openmp [OpenMP] Help static loop code avoid over/underflow 2021-02-22 13:22:01 -06:00
parallel-libs
polly [Polly] Fix test after D96534. 2021-02-19 12:49:29 -06:00
pstl [pstl] Iterator types renaming: ForwardIterator -> RandomAccessIterator; for parallel patterns/bricks 2021-02-13 20:28:50 +03:00
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CONTRIBUTING.md
README.md [doc] Use cmake's -S option to simplify the build instructions 2021-02-16 14:47:06 -06:00

README.md

The LLVM Compiler Infrastructure

This directory and its sub-directories contain source code for LLVM, a toolkit for the construction of highly optimized compilers, optimizers, and run-time environments.

The README briefly describes how to get started with building LLVM. For more information on how to contribute to the LLVM project, please take a look at the Contributing to LLVM guide.

Getting Started with the LLVM System

Taken from https://llvm.org/docs/GettingStarted.html.

Overview

Welcome to the LLVM project!

The LLVM project has multiple components. The core of the project is itself called "LLVM". This contains all of the tools, libraries, and header files needed to process intermediate representations and converts it into object files. Tools include an assembler, disassembler, bitcode analyzer, and bitcode optimizer. It also contains basic regression tests.

C-like languages use the Clang front end. This component compiles C, C++, Objective-C, and Objective-C++ code into LLVM bitcode -- and from there into object files, using LLVM.

Other components include: the libc++ C++ standard library, the LLD linker, and more.

Getting the Source Code and Building LLVM

The LLVM Getting Started documentation may be out of date. The Clang Getting Started page might have more accurate information.

This is an example work-flow and configuration to get and build the LLVM source:

  1. Checkout LLVM (including related sub-projects like Clang):

    • git clone https://github.com/llvm/llvm-project.git

    • Or, on windows, git clone --config core.autocrlf=false https://github.com/llvm/llvm-project.git

  2. Configure and build LLVM and Clang:

    • cd llvm-project

    • cmake -S llvm -B build -G <generator> [options]

      Some common build system generators are:

      • Ninja --- for generating Ninja build files. Most llvm developers use Ninja.
      • Unix Makefiles --- for generating make-compatible parallel makefiles.
      • Visual Studio --- for generating Visual Studio projects and solutions.
      • Xcode --- for generating Xcode projects.

      Some Common options:

      • -DLLVM_ENABLE_PROJECTS='...' --- semicolon-separated list of the LLVM sub-projects you'd like to additionally build. Can include any of: clang, clang-tools-extra, libcxx, libcxxabi, libunwind, lldb, compiler-rt, lld, polly, or debuginfo-tests.

        For example, to build LLVM, Clang, libcxx, and libcxxabi, use -DLLVM_ENABLE_PROJECTS="clang;libcxx;libcxxabi".

      • -DCMAKE_INSTALL_PREFIX=directory --- Specify for directory the full path name of where you want the LLVM tools and libraries to be installed (default /usr/local).

      • -DCMAKE_BUILD_TYPE=type --- Valid options for type are Debug, Release, RelWithDebInfo, and MinSizeRel. Default is Debug.

      • -DLLVM_ENABLE_ASSERTIONS=On --- Compile with assertion checks enabled (default is Yes for Debug builds, No for all other build types).

    • cmake --build build [-- [options] <target>] or your build system specified above directly.

      • The default target (i.e. ninja or make) will build all of LLVM.

      • The check-all target (i.e. ninja check-all) will run the regression tests to ensure everything is in working order.

      • CMake will generate targets for each tool and library, and most LLVM sub-projects generate their own check-<project> target.

      • Running a serial build will be slow. To improve speed, try running a parallel build. That's done by default in Ninja; for make, use the option -j NNN, where NNN is the number of parallel jobs, e.g. the number of CPUs you have.

    • For more information see CMake

Consult the Getting Started with LLVM page for detailed information on configuring and compiling LLVM. You can visit Directory Layout to learn about the layout of the source code tree.