Reproducible Evaluation of Systems
Website: getpopper.io (archived)
Funding: NSF OAC-1450488, NSF OAC-1836650, CROSS
Overview: USENIX ;login: Winter 2016
Workshops and Conferences:
- 1st International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS 2018) held in conjunction with ACM HPDC 2018.
- 2nd International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS 2019) held in conjunction with ACM HPDC 2019. Annual forum for the ACM Emerging Interest Group for Reproducibility and Replicability (EIGREP).
- 3rd International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS 2020) held in conjunction with ACM HPDC 2020. Annual forum for the ACM Emerging Interest Group for Reproducibility and Replicability (EIGREP).
- 4th International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS 2021) held in conjunction with ACM HPDC 2021. Annual forum for the ACM Emerging Interest Group for Reproducibility and Replicability (EIGREP).
- 5th International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS 2022) held in conjunction with ACM HPDC 2022. Annual forum for the ACM Emerging Interest Group for Reproducibility and Replicability (EIGREP).
- 2023 ACM Conference on Reproducibility and Replicability (ACM REP ‘23). Annual forum for the ACM Emerging Interest Group for Reproducibility and Replicability (EIGREP).
- 2024 ACM Conference on Reproducibility and Replicability (ACM REP ‘24). Annual forum for the ACM Emerging Interest Group for Reproducibility and Replicability (EIGREP).
- 2025 ACM Conference on Reproducibility and Replicability (ACM REP ‘25). Annual forum for the ACM Emerging Interest Group for Reproducibility and Replicability (EIGREP).
Independently validating experimental results in the field of computer systems research is a challenging task. Recreating an environment that resembles the one where an experiment was originally executed is a time-consuming endeavor. Popper is a convention (or protocol) for conducting experiments following a DevOps approach that allows researchers to make all associated artifacts publicly available with the goal of maximizing automation in the re-execution of an experiment and validation of its results.