PoPETs Artifact Review

PoPETs reviews and publishes digital artifacts related to its accepted papers. This process aids in the reproducibility of results and allows others to build on the work described in the paper. Artifact submissions are requested from authors of all accepted papers, and although they are optional, we strongly encourage you to submit your artifacts for review.

Possible artifacts include (but are not limited to):

• Source code (e.g., system implementations, proof of concepts)
• Datasets (e.g., network traces, raw study data)
• Scripts for data processing or simulations
• Machine-generated proofs
• Formal specifications
• Build environments (e.g., VMs, Docker containers, configuration scripts)

Artifacts are evaluated by the artifact review committee. The committee evaluates the artifacts to ensure that they provide an acceptable level of utility, and feedback is given to the authors. Issues considered include software bugs, readability of documentation, and appropriate licensing. After your artifact has been approved by the committee, we will accompany the paper link on petsymposium.org with a link to the artifact along with an artifact badge so that interested readers can find and use your hard work.

Artifact Submission Guidelines

• All submitted artifacts should be relevant to their corresponding PoPETs paper. Please provide a copy of your paper or a brief description of how the artifact is relevant to it in your submission.
• Many papers have several artifacts (e.g., multiple source code repositories, datasets, build environments), which is great! Please keep in mind that we'll need a single link to put on the PETS website and that all artifacts associated with your paper should be discoverable from that link.
• All submitted artifacts should be submitted by providing a link to where the artifacts are publicly hosted.
• Please include a README with your submission that briefly explains the type and purpose of the artifact (e.g., whether it's a proof of concept implementation, scripts for generating graphs, or datasets for reproducing results).
• All artifacts must be immediately available to the public and should not be behind any kind of paywall or restricted access. If the artifact requires you as an author to manually approve requests for access, it is not public and will not qualify as a PoPETs artifact submission. If you have concerns or questions about this please contact us directly.

Source Code Submissions

• All source code should be accompanied by a README or other documentation that describes how to build and/or run the code. Reviewers will provide feedback on the clarity of the instructions and attempt to follow them and build and/or run the code.
• Any source code submissions should be accompanied with a build environment such as a virtual machine (recommended) or a Docker container that has been configured with all the dependencies and prerequisites necessary to build the code.
• If you use a virtual machine, please state how many resources it will consume and any configuration steps that are required. Your virtual machine should not usually have to download additional dependencies when you run your install scripts. If that is the case, reassess your build process and consider making changes to limit the amount of network resources needed.
• If the code is in a compiled language, the code should compile in the provided build environment by performing the provided instructions.
• If the code is interpreted, please provide some simple inputs so that the reviewers can verify that the code runs without error. We want to make sure that the code will execute without error, not that the outputs are necessarily correct.
• Compilation and setup should be automated as much as possible. Ideally, there will be one script that builds your software and runs your tests.
• Please ensure your code has an open source license and clearly states this information. The following resources may help you to choose a license:
  • For a clear, easy to follow guide see: https://choosealicense.com/
  • For more in-depth detail on open source and copy-left licenses, see https://www.gnu.org/licenses/license-list.en.html and https://opensource.org/licenses
• Our goal with these artifacts is for them to be useful as far into the future as possible. Some tips on improving the longevity of your source code artifact are:
  • Include the versions of your software's dependencies wherever possible
  • Mention specific hashes of git commits that match the state your artifact was in at the time of submission
  • Virtual machines will last longer than Docker files and allow researchers to more accurately reproduce your exact execution environment (though the tradeoff is that they will be larger)
• Artifacts are *not* required to be able to run on all hardwares and OSes. If your artifact requires any particular hardware / OS, please make it clear in the submission.

Dataset Submissions

• All datasets should be clearly documented in a way that would allow researchers working on similar problems to re-use the dataset for their work.
• If the dataset includes survey results, please provide a copy of the original survey. This is vital for replication studies and helping researchers interpret the context of your results.
• If the dataset is very large (> 10 MB) please state so in the README or documentation.
• It's encouraged to accompany the data with processing scripts that produce any graphs or statistical output that appear in the paper.

Volunteer for the Artifact Review Committee

We are looking for volunteers to serve on the artifact review committee. As a committee member, you will perform review of artifacts according to the guidelines above. We are looking for volunteers who will be interested in providing feedback on documentation and instructions, trying to get source code to build, or have experience with re-using published datasets. Please email artifact23@petsymposium.org to be on the review committee.

Artifact Review Committee:

Alexander Bajic

Alexandra Nisenoff, Carnegie Mellon University

Amin Rabinia

Anna Lorimer, University of Chicago

Antonio Espinoza, Arizona State University

Arthur Borem, University of Chicago

Bailey Kacsmar, University of Waterloo

Cecylia Bocovitch, The Tor Project

Darion Cassel, Carnegie Mellon University

David Ke Hong, Facebook Inc

Hieu Le, University of California, Irvine

Imranur Rahman, North Carolina State University

Karoline Busse, University of Applied Administrative Sciences, Lower Saxony

Killian Davitt, University College London

Konrad Kollnig, University of Oxford

Kris Kwiatkowski, PQShield LTD

Kyle Tilbury, University of Waterloo

Lachlan Gunn, Aalto University

Loris Reiff

Maaz Bin Musa, University of Iowa

Malte Wessels, Technische Universität Braunschweig

Maximilian Noppel, Karlsruhe Institute of Technology

Min Chen, CISPA Helmholtz Center for Information Security

Miti Mazmudar, University of Waterloo

Natasha Fernandes, Macquarie University

Nathan Reitinger, University of Maryland

Panagiotis Chatzigiannis, Visa Research

Pasin Manurangsi, Google Research

Pingchuan Ma, Hong Kong University of Science and Technology

Priyanka Nayakkaral, Northwestern University

Qian Lou, University of Central Florida

Rahmadi Trimananda, UC Irvine

Rasmus Dahlberg, Karlstad University

Sepideh Ghanavati, University of Maine

Simon Koch, TU Braunschweig

Shangqi Lai, Monash University

Sofía Celi, Brave Software

Tatsuya Mori, Waseda University

Tushar Jois, Johns Hopkins University

Yohan Beugin, University of Wisconsin-Madison

Zhang Shaohu, North Carolina State University