Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022

This project is developed using Python 3.6.9 on Ubuntu 18.04 LTS.

We have opened our knowledge graphs in releases. If you need to create a new knowledge graph, follow the instructions below:

First, you need to install Neo4j 4.1.1 and its required Java version (Java SE 11).

Install extra Python dependencies:

pip install -r build_KG/requirements.txt

Automatically acquire knowledge and build KG for specific Python packages:

python build_KG/run.py <packages_file> <neo4j_HOME> <Python_version>

Load data from CSV files into an unused Neo4j database and dump the database into a single-file archive:

./build_KG/data/Pythonxxx/csv-data/run.sh

NEO4J_HOME/bin/neo4j-admin dump --database=neo4j --to=neo4j.dump

Move the dump files to the specific folder:

mv py2.dump py3.dump docker_env/neo4j

Build the docker images and start the deamon service:

cd docker_env

./build_images.sh

docker-compose up --detach

Install extra Python dependencies:

pip install -r bin/requirements.txt

Compile CryptoMiniSat SAT solver.

Now, you can use PyCRE to infer a compatible runtime environment to a Python code:

python bin/run.py <snippet_path> <dependencies_dir>

If you use this work or code, please kindly cite it as follows:

@inproceedings{PyCRE,
  author    = {Wei Cheng and Xiangrong Zhu and Wei Hu},
  title     = {Conflict-aware Inference of Python Compatible Runtime Environments with
               Domain Knowledge Graph},
  booktitle = {International Conference on Software Engineering (ICSE)},
  year      = {2022}
}