ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal

This is the artifact submission for the paper “Learning and Repair of Deep Reinforcement Learning Policies from Fuzz-Testing Data”. The artifact is available at “https://figshare.com/articles/software/Supplementary_Material_for_Learning_and_Repair_of_Deep_Reinforcement_Learning_Policies_from_Fuzz-Testing_Data_/22353712” or under the DOI “10.6084/m9.figshare.22353712.v2”.

We apply for the “available” badge, for which we meet the requirements by publishing the material on figshare.com under the MIT license.

While we documented the artifact, provided a README file, and included all the material to replicate our results, we do not apply for the “Reusable” badge. The main reason is that the reviewing period is likely too short to replicate our experiments, as the runtime of individual experiments is between 12 hours and 3 days for the SMB. environments.