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Installing HAROS

Here are some instructions to help you get HAROS running manually in your machine. A simplified version of these instructions, with convenience scripts, can be found at make-haros-easy.

These instructions assume that you already have a working installation of ROS. HAROS has been tested with ROS Indigo, ROS Kinetic, ROS Melodic and ROS Noetic, on Linux Mint and Linux Ubuntu. These setups should provide you with most of the basic dependencies of HAROS, namely Python 2.7+ (or Python 3.6+) and a web browser (if you want to use the visualiser).

For a full list of dependencies, see the Requirements section.

Quick links:

  1. Running From Source
  2. Installing HAROS
  3. Running With Docker

NOTE This tool assumes that the current terminal shell has a source /opt/ros/<distro>/setup.bash and a source /path/to/workspace/devel/setup.bash. In other words, you need a working ROS installation and a catkin workspace.

Method 1: Running From Source

Open a terminal, and move to a directory where you want to clone this repository.

mkdir ros
cd ros
git clone https://github.com/git-afsantos/haros.git

There is an executable script in the root of this repository to help you get started. It allows you to run haros without installing it. Make sure that your terminal is at the root of the repository.

cd haros
python haros-runner.py ARGS

You can also run it with the executable package syntax.

python -m haros ARGS

Method 2: Installing HAROS

HAROS is available on PyPi. You can install it from source or from a wheel with pip.

pip install haros

The command above will install HAROS for you. Alternatively, download and extract its source, move to the project's root directory, and then execute the following.

python setup.py install

After installation, you should be able to run the command haros in your terminal.

Note: To install via pip you might be asked to provide sudo privileges. If not, it is possible that the main executable is not found after installing locally, due to an issue with pip in Debian/Ubuntu. This issue causes executables to be placed at ~/.local/bin, which is not part of the default $PATH. A recommended alternative is to install haros within a virtualenv virtual environment.

Method 3: Running With Docker

See the Make HAROS Easy repository or the HAROS Tutorials repository.

Requirements

Before using HAROS, you need to install some additional dependencies from the Python requirements file.
(Not necessary if you install HAROS via pip)

pip install -r requirements.txt

In addition, you need to perform some initialisation operations. Do so with:

haros init

Note: if you opted for running HAROS from source, replace haros with the appropriate command.

HAROS is now installed and ready to use. The rest of the instructions depend on the type of analysis you want to perform.

Internal Code Quality

Analysis based on linters, code quality metrics, coding style, etc..

[sudo] apt-get install cppcheck
[sudo] apt-get install cccc

Model Extraction

These features are only working for C++ code as of now. Python code has limited support in the current version.

[sudo] apt-get install libclang-3.8-dev
pip install -Iv clang==3.8

Other versions of libclang are tested and supported, up to libclang-10-dev, at least. Just make sure that the versions of libclang and Python's clang match, as in the example above.

(Optional) If you want to ensure that your code compiles with Clang, you might want to install clang++ in addition to libclang-dev (for the same version).

(Optional) Set up the LD_LIBRARY_PATH environment variable to point to the libclang.so shared library. Example:

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib/llvm-3.8/lib

After running HAROS init: Open the configs.yaml file in the HAROS home directory (default: ~/.haros/configs.yaml) and provide the paths to the library and the include directories of your libclang version (uncomment any commented lines). Example:

~/.haros/configs.yaml:

%YAML 1.1
---
workspace: '/home/me/ros/ws'
cpp:
    parser_lib: '/usr/lib/llvm-4.0/lib'
    std_includes: '/usr/lib/llvm-4.0/lib/clang/4.0.1/include'
    compile_db: '/home/me/ros/ws/build'

Computation Graph Model Queries

Install pyflwor to enable queries to run on extracted models.

# without virtualenv
pip install -e git+https://github.com/timtadh/pyflwor.git#egg=pyflwor
# with virtualenv
pip install pyflwor-ext

Install also the respective HAROS plugin.

Runtime Monitor Generation

TODO

Property-based Test Generator

TODO