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SILENCE

This repository contains source code and data of the paper "Understanding and Remediating Open-Source License Incompatibilities in the PyPI Ecosystem" published at 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE).

  • Weiwei Xu, Hao He, Kai Gao, Minghui Zhou. Understanding and Remediating Open-Source License Incompatibilities in the PyPI Ecosystem. ASE'2023

Tool

📢 A tool based on SILENCE for compliance analysis and incompatibility remediation for Python projects is now available at https://licenserec.com/#/compliance.

Intorduction

In this paper, we first conduct a large-scale empirical study of license incompatibility in PyPI ecosystem. Inspired by our findings, we propose SILENCE, an SMT-solver-based incompatibility remediator for licenses in the dependency graph. Given a release and its dependency graph with one or more license incompatibilities, SILENCE

  1. finds alternative licenses that are compatible with the dependency graph, and
  2. searches for alternative graphs with no license incompatibilities and minimal difference with the original graph. The results are aggregated as a report of recommended remediations (i.e., migrations, removals, version pinnings, or license changes) for developers to consider.

Dirs and files

  1. licensing_data_collection: licensing information collection
  2. dep_resolve : Python dependency tree resolution
  3. knowledge_base contains license compatibility matrix, migration patterns, license keywords and so on.
  4. analysis.py : data analysis of empirical study
  5. RQ1_license_distribution.ipynb: results of RQ1
  6. RQ1_license_evolution.ipynb: results of RQ1
  7. RQ2_license_incompatibility.ipynb: results of RQ2
  8. RQ3_license_remediation_practice.md: note of RQ3
  9. remediator.py: implementation of SILENCE's SMT-based part
  10. relicenser.py: implementation of SILENCE's relicenser
  11. res contains results and evaluation of SILENCE.
  12. data contains our dataset
  13. SILENCE.py contains the main function of SILENSE.

How to start?

  1. The dataset is stored in the package collection in the license database. You can get the dataset in data directory (due to the file size limit on GitHub, please download the dataset at here) and you need to import it into MongoDB. Run:
mongorestore --db=license --gzip data/package.bson.gz
  1. For results of the empirical study, you can run:
RQ1_license_distribution.ipynb
RQ1_license_evolution.ipynb
RQ2_license_incompatibility.ipynb
  1. To get remediations of all incompatibilities in top 5,000 downloaded packages, you can run:
python remediator.py all
python relicenser.py
  1. If you want to get remediations in dependency graph for a specific package version, run:
python SILENCE.py -n name -v version

For example, if you want to get remediations for fiftyone 0.18.0 in the paper, you can run:

python SILENCE.py -n fiftyone -v 0.18.0

you will get the output as follows:

Possible Remediations for fiftyone 0.18.0:
1. Change project license to GPL-3.0-only, GPL-3.0-or-later, or AGPL-3.0-only;
2. Or make the following dependency changes:
   a) Remove ndjson;
   b) Pin voxel51-eta to 0.1.9;
   c) Pin pillow to 6.2.2;
   d) Pin imageio to 2.9.0;
   e) Pin h11 to 0.11.0.
3. Or make the following dependency changes:
   a) Remove voxel51-eta;
   b) Remove ndjson;
   c) Pin h11 to 0.11.0.

License

The project is licensed under MulanPubL-2.0.

Citation

For citing, please use the following BibTex citation:

@inproceedings{SILENCE2023,
  title={Understanding and Remediating Open-Source License Incompatibilities in the PyPI Ecosystem},
  author={Xu, Weiwei and He, Hao and Gao, Kai and Zhou, Minghui},
  booktitle={2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE)},
  pages={178--190},
  year={2023},
  organization={IEEE}
}