← Research building on SQLancer

Shuqi Liu, Yu Zhou, Wenhua Yang, Taolue Chen, Harald C. Gall. 2025. Empirical Software Engineering.

Read the paper · doi:10.1007/s10664-025-10662-w

What this paper does with SQLancer

The single mention places SQLancer's work as the database-side precedent: the paper notes that existing studies have detected CRUD errors in database management systems, but that those approaches are not tailored for Android apps, where the errors surface through the application's own data layer rather than through SQL. The citation is author-year, so the tool is not named directly. This work finds data manipulation errors in Android applications by exploring the app through its user interface, guided by scenes -- coherent groups of screens -- so that create, read, update and delete operations are exercised in realistic sequences rather than at random. Written by claude-opus-5 from the 1 place this paper refers to SQLancer. The quotations below are the paper's own words, stored verbatim when the text was extracted.

How it was classified

uses infrastructure — no

SQLancer is cited as related work; no reuse of its code, generator or workload is described.

extends technique — no

No SQLancer technique is extended; the citation is background.

compares with — no

No empirical comparison against SQLancer or one of its oracles is reported.

describes as state of the art — no

The text does not describe SQLancer as the state of the art.

Every place it refers to SQLancer (1)

1 sentence, each stored verbatim from the extracted text with where it was found and how. “Citation marker” means the sentence names no tool at all and was reached through a reference number that resolved to a SQLancer publication.

Id Sentence Found by Where
M1 Existingstudies (Rigger and Su 2020a ,bhave detected CRUD errors in database management systems, but these approaches are not specifically tailored for Android apps. author year citation
background
7 Related Work
page 34

This page is rendered from _data/papers/paper_doi_10_1007_s10664_025_10662_w.json, extracted from supplied pdf. 38 pages, 0 references parsed.