The paper [1] introduces DProvDB, a fine-grained privacy provenance framework. Our reproducibility evaluation shows that the key findings of the paper have been successfully reproduced, with minor discrepancies from the original figures explained by inherent randomness.
Reproducibility Report for ACM SIGMOD 2024 Paper: “DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance”
Giorgio Vinciguerra
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In corso di stampa
Abstract
The paper [1] introduces DProvDB, a fine-grained privacy provenance framework. Our reproducibility evaluation shows that the key findings of the paper have been successfully reproduced, with minor discrepancies from the original figures explained by inherent randomness.File in questo prodotto:
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