Building on Mac OS X is as easy as downloading the code and building the Xcode project or workspace:

Preliminaries

• XCode 4.3 or newer requires the "Command Line Tools" component (XCode->Preferences->Downloads->Components).
• Mac OS X Lion or newer requires installing Swig.

Building LLDB

• Download the lldb sources.
• Follow the code signing instructions in lldb/docs/code-signing.txt
• In Xcode 3.x: lldb/lldb.xcodeproj, select the lldb-tool target, and build.
• In Xcode 4.x: lldb/lldb.xcworkspace, select the lldb-tool scheme, and build.

This document describes the steps needed to compile LLDB on most Linux systems, and FreeBSD.

Preliminaries

LLDB relies on many of the technologies developed by the larger LLVM project. In particular, it requires both Clang and LLVM itself in order to build. Due to this tight integration the Getting Started guides for both of these projects come as prerequisite reading:

• LLVM
• Clang

Supported compilers for building LLDB on Linux include:

• Clang 3.2
• GCC 4.6.2 (later versions should work as well)

It is recommended to use libstdc++ 4.6 (or higher) to build LLDB on Linux, but using libc++ is also known to work.

On FreeBSD the base system Clang and libc++ may be used to build LLDB, or the GCC port or package.

In addition to any dependencies required by LLVM and Clang, LLDB needs a few development packages that may also need to be installed depending on your system. The current list of dependencies are:

• Swig
• libedit (Linux only)
• Python

So for example, on a Fedora system one might run:

> yum install swig python-devel libedit-devel

On a Debian or Ubuntu system one might run:

> sudo apt-get install build-essential subversion swig python-dev libedit-dev

or

> sudo apt-get build-dep lldb-3.3 # or lldb-3.4

On FreeBSD one might run:

> pkg install swig python

If you wish to build the optional reference documentation, additional dependencies are required:

• Graphviz (for the 'dot' tool).
• doxygen (only if you wish to build the C++ API reference)
• epydoc (only if you wish to build the Python API reference)

To install the prerequisites for building the documentation (on Debian/Ubuntu) do:


> sudo apt-get install doxygen graphviz
> sudo pip install epydoc # or install package python-epydoc

Building LLDB

We first need to checkout the source trees into the appropriate locations. Both Clang and LLDB build as subprojects of LLVM. This means we will be checking out the source for both Clang and LLDB into the tools subdirectory of LLVM. We will be setting up a directory hierarchy looking something like this:

  
                  llvm
                  |
                  `-- tools
                      |
                      +-- clang
                      |
                      `-- lldb
                

For reference, we will call the root of the LLVM project tree $llvm, and the roots of the Clang and LLDB source trees $clang and $lldb respectively.

Change to the directory where you want to do development work and checkout LLVM:

> svn co http://llvm.org/svn/llvm-project/llvm/trunk llvm

Now switch to LLVM’s tools subdirectory and checkout both Clang and LLDB:

> cd $llvm/tools
> svn co http://llvm.org/svn/llvm-project/cfe/trunk clang
> svn co http://llvm.org/svn/llvm-project/lldb/trunk lldb

In general, building the LLDB trunk revision requires trunk revisions of both LLVM and Clang.

It is highly recommended that you build the system out of tree. Create a second build directory and configure the LLVM project tree to your specifications as outlined in LLVM’s Getting Started Guide. A typical build procedure might be:

> cd $llvm/..
> mkdir build
> cd build

To build with CMake

Using CMake is documented on the Building LLVM with CMake page. Building LLDB is possible using one of the following generators:

• Ninja
• Unix Makefiles

Using CMake + Ninja

Ninja is the fastest way to build LLDB! In order to use ninja, you need to have recent versions of CMake and ninja on your system. To build using ninja:

> cmake .. -G Ninja -DLLVM_ENABLE_CXX11=ON
> ninja lldb
> ninja check-lldb

Using CMake + Unix Makefiles

If you do not have Ninja, you can still use CMake to generate Unix Makefiles that build LLDB:

> cmake .. -DLLVM_ENABLE_CXX11=ON
> make
> make check-lldb

To build with autoconf

If you do not have CMake, it is still possible to build LLDB using the autoconf build system. If you are using Clang or GCC 4.7+, run:

> $llvm/configure --enable-cxx11
> make

Or, if you are using a version of GCC that does not support the -std=c++11 option:

> $llvm/configure
> make CXXFLAGS=-std=c++0x

If you are building with a GCC that isn't the default gcc/g++, like gcc-4.7/g++-4.7

> $llvm/configure --enable-cxx11 CC=gcc-4.7 CXX=g++-4.7
> make CC=gcc-4.7 CXX=g++-4.7

If you are running in a system that doesn't have a lot of RAM (less than 4GB), you might want to disable debug symbols by specifying DEBUG_SYMBOLS=0 when running make. You will know if you need to enable this because you will fail to link clang (the linker will get a SIGKILL and exit with status 9).

> make DEBUG_SYMBOLS=0

To run the LLDB test suite, run:


> make -C tools/lldb/test

Note that once both LLVM and Clang have been configured and built it is not necessary to perform a top-level make to rebuild changes made only to LLDB. You can run make from the build/tools/lldb subdirectory as well.

If you wish to build with libc++ instead of libstdc++ (the default), run configure with the --enable-libcpp flag.

If you wish to build a release version of LLDB, run configure with the --enable-optimized flag.

Testing

By default, the check-lldb target builds the 64-bit variants of the test programs with the same compiler that was used to build LLDB. It is possible to customize the architecture and compiler by appending -A and -C options respectively to the CMake variable LLDB_TEST_ARGS. For example, to test LLDB against 32-bit binaries built with a custom version of clang, do:


> cmake -DLLDB_TEST_ARGS="-A i386 -C /path/to/custom/clang" -G Ninja
> ninja check-lldb

Note that multiple -A and -C flags can be specified to LLDB_TEST_ARGS.

In addition to running all the LLDB test suites with the "check-lldb" CMake target above, it is possible to run individual LLDB tests. For example, to run the test cases defined in TestInferiorCrashing.py, run:


> cd $lldb/test
> python dotest.py --executable <path-to-lldb> -p TestInferiorCrashing.py

In addition to running a test by name, it is also possible to specify a directory path to dotest.py in order to run all the tests under that directory. For example, to run all the tests under the 'functionalities/data-formatter' directory, run:


> python dotest.py --executable <path-to-lldb> functionalities/data-formatter

To dump additional information to stdout about how the test harness is driving LLDB, run dotest.py with the -t flag. Many more options that are available. To see a list of all of them, run:


> python dotest.py -h

Building API reference documentation

LLDB exposes a C++ as well as a Python API. To build the reference documentation for these two APIs, ensure you have the required dependencies installed, and build the lldb-python-doc and lldb-cpp-doc CMake targets.

The output HTML reference documentation can be found in <build-dir>/tools/lldb/docs/.

Additional Notes

LLDB has a Python scripting capability and supplies its own Python module named lldb. If a script is run inside the command line lldb application, the Python module is made available automatically. However, if a script is to be run by a Python interpreter outside the command line application, the PYTHONPATH environment variable can be used to let the Python interpreter find the lldb module.

The correct path can be obtained by invoking the command line lldb tool with the -P flag:

> export PYTHONPATH=`$llvm/build/Debug+Asserts/bin/lldb -P`

If you used a different build directory or made a release build, you may need to adjust the above to suit your needs. To test that the lldb Python module is built correctly and is available to the default Python interpreter, run:

> python -c 'import lldb'