Arlib

Arlib is toolkit for automated reasoning. It provides a set of tools for constraint solving, logical inference, and symbolic computation.

Local Development Environment

Run the following command to setup the local development environment.

bash setup_local_env.sh

The script will

• Create a Python virtual environment if it doesn't exist
• Activate the virtual environment and install dependencies from requirements.txt
• Download required solver binaries (CVC5, MathSAT, z3)
• Run unit tests if available

TBD:

• Test the scripts on different platforms, editors/IDEs, etc.

Install the Library Locally

Local installziation via setup.py

pip install -e .

Then you can use a few cli tools of this library, add call the Python API in your own Python code.

Release the Repo to PyPI

TBD (The repository is not yet released to PyPI.)

Contributing

Contributions are welcome. Please refer to the repository for detailed instructions on how to contribute.

arlib/
├── arlib/           # Main library code
├── benchmarks/      # Benchmark files and test cases
├── bin_solvers/     # Binary solver executables
├── docs/            # Documentation files
├── scripts/         # Utility scripts
├── examples/        # A few applications
├── setup.py         # Package setup configuration (not ready)
├── pytest.ini       # PyTest configuration
└── requirements.txt # Project dependencies

For Summer Research, Final Year Project Topics, please refer to docs/topics.rst or TODO.md.

Documentation

We release the docs here: https://pyarlib.readthedocs.io/en/latest/

Publications

Here are some of publications related to Arlib.

• Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning. Pingchuan Ma, Zhenlan Ji, Peisen Yao, Shuai Wang, and Kui Ren. ICSE 2024

Related Work

• pysat
• pysmt
• pyqbf
• sympy

Contributors

Primary contributors to this project:

• rainoftime / cutelimination
• JasonJ2021
• ZelinMa557
• Harrywwq
• little-d1d1
• ljcppp
• GooduckZ