UNMASQUE Hidden Query Extractor
Database Systems Lab Indian Institute of Science |
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About UNMASQUE
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Welcome to the UNMASQUE software developed at the Database Systems Lab, Indian
Institute of Science.
UNMASQUE is an easy-to-use graphical tool for non-invasively and efficiently extracting SQL queries that are hidden in black-box executables.
It is written entirely in Python 3, and has been successfully tested
on the
PostgreSQL and Microsoft SQL Server
platforms.
The problem of unmasking SQL queries hidden within database applications has a variety of use-cases ranging from resurrecting legacy code to lightweight query rewriting. To address this problem, we have developed UNMASQUE, an extraction algorithm that is capable of identifying a substantive class of hidden SPJGHAOL queries. A special feature of our design is that the extraction is non-invasive with respect to the application code, examining only the results obtained from its executions on databases derived with a combination of data mutation and data generation techniques. Further, potent optimizations, such as database size reduction to a few rows, are incorporated to minimize the extraction overheads. A detailed evaluation over benchmark databases demonstrates that UNMASQUE is capable of correctly and efficiently extracting complex hidden queries. | |||||
Downloads |
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Publications |
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Shedding Light on Opaque Application Queries
(5 minute Video) (20 minute Video) (1 hour Video)
Kapil Khurana, Jayant Haritsa Proc. of ACM SIGMOD Intl. Conf. on Management of Data, Xi'an, China, June 2021 UNMASQUE: A Hidden SQL Query Extractor (demo) (Demo Video) Kapil Khurana, Jayant Haritsa Proc. of 46th Intl. Conf. on Very Large Data Bases (VLDB), Tokyo, Japan, September 2020 published as PVLDB Journal, 13(12), August 2020, pgs. 2809-2812 |
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Contact |
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Email:
haritsa [AT] iisc [dot] ac [dot] in
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Primary Contributors (in chronological order of participation) |
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