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Perturbation Analysis of Database Queries

Summary: Perada enables parallel perturbation analysis of queries. API supports grouping, memoization, and pruning; automatically optimizes with runtime learning; adapts to workloads; hides concurrency and failures—demonstrated on computational journalism. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11491
Venue
VLDB
Year
2016
Pagerank
6.0350628e-05
Overall Rank
5,937 | 59.27%
DOI
10.14778/3007328.3007330

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{walenz_vldb16,
        title = {{Perturbation Analysis of Database Queries}},
        author = {Walenz, Brett and Yang, Jun},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {14},
        pages = {1635--1648},
        doi = {10.14778/3007328.3007330},
        url = {https://doi.org/10.14778/3007328.3007330},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
5,077 Verifying Text Summaries of Relational Data Sets 2019 SIGMOD 6.3730257e-05
7,870 Optimizing Iceberg Queries with Complex Joins 2017 SIGMOD 5.5272726e-05
10,717 Demonstrating CEDAR: A System for Cost-Efficient Data-Driven Claim Verification 2025 SIGMOD 5.093636e-05
10,983 CEDAR: A System for Cost-Efficient Data-Driven Claim Verification 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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