ace644030e
Currently, there is basically just one clang-tidy check to impose some sanity limits on functions - `clang-tidy-readability-function-size`. It is nice, allows to limit line count, total number of statements, number of branches, number of function parameters (not counting implicit `this`), nesting level. However, those are simple generic metrics. It is still trivially possible to write a function, which does not violate any of these metrics, yet is still rather unreadable. Thus, some additional, slightly more complicated metric is needed. There is a well-known [[ https://en.wikipedia.org/wiki/Cyclomatic_complexity | Cyclomatic complexity]], but certainly has its downsides. And there is a [[ https://www.sonarsource.com/docs/CognitiveComplexity.pdf | COGNITIVE COMPLEXITY by SonarSource ]], which is available for opensource on https://sonarcloud.io/. This check checks function Cognitive Complexity metric, and flags the functions with Cognitive Complexity exceeding the configured limit. The default limit is `25`, same as in 'upstream'. The metric is implemented as per [[ https://www.sonarsource.com/docs/CognitiveComplexity.pdf | COGNITIVE COMPLEXITY by SonarSource ]] specification version 1.2 (19 April 2017), with two notable exceptions: * `preprocessor conditionals` (`#ifdef`, `#if`, `#elif`, `#else`, `#endif`) are not accounted for. Could be done. Currently, upstream does not account for them either. * `each method in a recursion cycle` is not accounted for. It can't be fully implemented, because cross-translational-unit analysis would be needed, which is not possible in clang-tidy. Thus, at least right now, i completely avoided implementing it. There are some further possible improvements: * Are GNU statement expressions (`BinaryConditionalOperator`) really free? They should probably cause nesting level increase, and complexity level increase when they are nested within eachother. * Microsoft SEH support * ??? Reviewed By: aaron.ballman, JonasToth, lattner Differential Revision: https://reviews.llvm.org/D36836 |
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clang | ||
clang-tools-extra | ||
compiler-rt | ||
debuginfo-tests | ||
flang | ||
libc | ||
libclc | ||
libcxx | ||
libcxxabi | ||
libunwind | ||
lld | ||
lldb | ||
llvm | ||
mlir | ||
openmp | ||
parallel-libs | ||
polly | ||
pstl | ||
utils/arcanist | ||
.arcconfig | ||
.arclint | ||
.clang-format | ||
.clang-tidy | ||
.git-blame-ignore-revs | ||
.gitignore | ||
CONTRIBUTING.md | ||
README.md |
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:
-
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
-
-
Configure and build LLVM and Clang:
-
cd llvm-project
-
mkdir build
-
cd build
-
cmake -G <generator> [options] ../llvm
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 . [-- [options] <target>]
or your build system specified above directly.-
The default target (i.e.
ninja
ormake
) 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
, whereNNN
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.