Experiments for 'Efficient Sensitivity Analysis for Parametric Robust Markov Chains'
<p>This artifact accompanies the CAV 2023 paper with the title 'Efficient Sensitivity Analysis for Parametric Robust Markov Chains'. The artifact contains a docker file, which can be unzipped and then loaded with:</p> <pre><code>docker load -i prmc_sensitivity_cav23_docker.tar</code></pre> <p>Depending on your permissions, you may need to run this command with sudo. Please refer to the ReadMe for more information.</p> <p>The source code of the docker container is available on GitHub: <a href="https://github.com/LAVA-LAB/prmc-sensitivity">https://github.com/LAVA-LAB/prmc-sensitivity</a>.</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 8
- Reuse readiness
- 8
- Engagement
- 4
Topics
Dataset details
- Repository
- zenodo
- Published
- May 11, 2023
- License
- apgl-v3
- DOI
- 10.5281/zenodo.7864260
Scored with release 0.9.0
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