Name
Abstract | ||
|---|---|---|
AbstractGiven a database instance and a populated result, query reverse-engineering attempts to identify candidate SQL queries that produce this result on the instance. A variant of this problem arises when a ground-truth is additionally available, but hidden within an opaque database application. In this demo, we present UN-MASQUE, an extraction algorithm that is capable of precisely identifying a substantive class of such hidden queries. A hallmark of its design is that the extraction is completely non-invasive to the application. Specifically, it only examines the results obtained from application executions on databases derived with a combination of data mutation and data generation techniques, thereby achieving platform-independence. Further, potent optimizations, such as database size reduction to a few rows, are incorporated to minimize the extraction overheads. The demo showcases these features on both declarative and imperative applications. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.14778/3415478.3415481 | Hosted Content |
DocType | Volume | Issue |
Journal | 13 | 12 |
ISSN | Citations | PageRank |
2150-8097 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kapil Khurana | 1 | 0 | 0.68 |
| Jayant R. Haritsa | 2 | 2004 | 228.38 |