Differentially Testing Database Transactions for Fun and Profit

Ziyu Cui, Wensheng Dou, Qianwang Dai, Jiansen Song, Wei Wang, Jun Wei, Dan Ye. 2022. International Conference on Automated Software Engineering.

Read the paper · doi:10.1145/3551349.3556924

What this paper does with SQLancer

DT2 generates its databases and transactions mainly on the basis of SQLancer, revised for the transaction setting, and its artifact carries SQLancer's source under a renamed package. PQS, NoREC and TLP are cited as the approaches confined to single SELECT statements -- the limitation DT2 sets out to pass. DT2 tests transaction implementations by differential testing across DBMSs. It randomly generates a database and a group of concurrent transactions over it, supporting complex features such as varied schemas and cross-table queries, then compares execution results on several systems to find discrepancies. Because concurrency makes results non-deterministic, the authors add a transaction test protocol that forces deterministic execution. Across MySQL, MariaDB and TiDB it found 10 unique transaction bugs and 88 compatibility issues. Written by claude-opus-5 from the 3 places 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 — yes (generator)

M2 states the transactions are generated mainly based on SQLancer with slight revision for the target. The artifact carrying SQLancer source under a renamed package agrees.

We generate them mainly based on SQLancer [ 16], and slightly revise the approach for our target. M2 · 4.1 Transaction Test Case Generation · page 5

extends technique — no

No technique is extended; the citation is background.

compares with — no

No empirical comparison against SQLancer is reported in the mentions.

describes as state of the art — no

The citation does not characterise SQLancer as the state of the art.

Its artifact

criszy/DT2 carries renamed sqlancer package, sqlancer source content match.

Repository is named after DT2, the tool this paper says it built, and is about database testing.
# DT2
source

src/DT2/Randomly.java is SQLancer's Randomly.java, with the package renamed to DT2 (8 of 8 identifiers match: StringGenerationStrategy, SOPHISTICATED, cachedLongs, cachedStrings, cachedDoubles).
private static StringGenerationStrategy stringGenerationStrategy = StringGenerationStrategy.SOPHISTICATED;
source

SQLancer publications it cites (4)

Bibliography entries that resolved to a SQLancer publication, or to a paper by one of the project's authors. A sentence citing one of these numbers is a reference to SQLancer even when it never writes the name.

#	Entry	Matched as
16	2022. SQLancer. https://www.manuelrigger.at/dbms-bugs.	sqlancer publication
58	Manuel Rigger and Zhendong Su. 2020. Detecting Optimization Bugs in Database Engines via Non-Optimizing Reference Engine Construction. In Proceedings of ACM Joint European Software Engineering Conference and Symposium...	sqlancer publication · NOREC
59	Manuel Rigger and Zhendong Su. 2020. Finding Bugs in Database Systems via Query Partitioning. In Proceedings of ACMSIGPLAN Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA). 211:1...	sqlancer publication · TLP
60	Manuel Rigger and Zhendong Su. 2020. Testing Database Engines via Pivoted Query Synthesis. In Proceedings of USENIX Symposium on Operating Systems Design and Implementation (OSDI). 667–682.	sqlancer publication · PQS

Every place it refers to SQLancer (3)

3 sentences, 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	, PQS [ 60], NoREC [ 58], TLP [ 59] and RAGS [61], can detect DBMS bugs that involve these complex features in single SELECT statements.	technique motivation	1 INTRODUCTION page 2
M2	We generate them mainly based on SQLancer [ 16], and slightly revise the approach for our target.	name reuse component	4.1 Transaction Test Case Generation page 5
M3	[ 58–60] has proposed a series of works to find logical bugs by generating single SQL queries.	citation marker motivation	7.2 Limitations page 11

This page is rendered from _data/papers/paper_doi_10_1145_3551349_3556924.json, extracted from supplied pdf. 12 pages, 67 references parsed.