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Shedding Light on Opaque Application Queries

Summary: UNMASQUE, an active-learning, non-invasive extractor, unmasks hidden SQL queries in applications by observing results from mutated/generated data. Optimizations trim overhead; evaluations on hidden/imperative variants show accurate, efficient recovery of a basal warehouse-query class. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6144
Venue
SIGMOD
Year
2021
Pagerank
4.4173276e-05
Overall Rank
8,960 | 37.73%
DOI
10.1145/3448016.3457252

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
5,533 QueryBooster: Improving SQL Performance Using Middleware Services for Human-Centered Query Rewriting 2023 VLDB 5.4555519e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,107 Froid: Optimization of Imperative Programs in a Relational Database 2018 VLDB 0.0001397627
1,575 Reverse Engineering Complex Join Queries 2013 SIGMOD 0.00011288804
2,182 Querying Data Provenance 2010 SIGMOD 9.3596252e-05
2,717 REGAL+: Reverse Engineering SPJA Queries 2018 VLDB 8.2370772e-05
2,990 FastQRE: Fast Query Reverse Engineering 2018 SIGMOD 7.7727915e-05
3,668 Reverse Engineering Aggregation Queries 2017 VLDB 6.8581987e-05
6,681 SQUARES : A SQL Synthesizer Using Query Reverse Engineering 2020 VLDB 4.9608812e-05
11,609 UNMASQUE: A Hidden SQL Query Extractor 2020 VLDB 4.1905499e-05
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