Metraipolis › archive › dc_67fa54520e95

Distribution-Aware Distributed Database Testing (Extended Version) — arXiv:2609.18501

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.18501
License (as archived): CC0-1.0
Archived: 2026-10-15T17:06:07.856Z
SHA-256 of the archived text: ceae922b38a834264f641ae518f69f5bb211f7aff54c767a679638f26f7ae627
Stable URL of this page: https://metraipolis.com/documento/dc_67fa54520e95

How to cite

Distribution-Aware Distributed Database Testing (Extended Version) — arXiv:2609.18501 — arXiv (en), https://arxiv.org/abs/2609.18501 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_67fa54520e95 (Metraipolis archive dc_67fa54520e95, sha256 ceae922b38a834264f641ae518f69f5bb211f7aff54c767a679638f26f7ae627)

BibTeX

@misc{dc67fa54520e95,
  title = {Distribution-Aware Distributed Database Testing (Extended Version) — arXiv:2609.18501},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.18501},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_67fa54520e95; sha256 ceae922b38a834264f641ae518f69f5bb211f7aff54c767a679638f26f7ae627},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.18501. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Distributed database management systems (DDBMSs) introduce new challenges for assessing their reliability due to distribution-specific characteristics that affect query execution and optimization. Existing testing approaches, largely designed for centralized DBMSs, often fail to explore diverse distributed execution behaviors and suffer from low executability of generated test queries, thereby limiting their effectiveness in bug detection. We propose DAT (Distribution-Aware Testing), a novel automated approach for detecting query-processing bugs related to distribution strategies and distributed optimizations in DDBMSs, by systematically leveraging distribution-aware information throughout the testing pipeline. DAT builds on a set of techniques that capture diverse combinations of logical schemas and data distribution strategies, and performs guided query mutation to trigger a wide range of distributed query execution behaviors and optimizations, while improving query executability via historical feedback. We implement our approach in a tool, DistRanger, and evaluate it on four widely used production DDBMSs. It uncovers 31 previously unknown bugs, including 28 related to distributed query processing and optimization, and outperforms state-of-the-art testers.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-17 in cs.DB).
Categorie arXiv: Databases (cs.DB).
Pagina del lavoro: https://arxiv.org/abs/2609.18501 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-15T16:16:30.700Z dalla pagina https://arxiv.org/catchup/cs.DB/2026-09-17?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).