
Differential Fuzzer
FreeCatch SQL correctness bugs in Turso with ease.
Free · Opens the source repo
What Differential Fuzzer does
The Differential Fuzzer is a specialized tool designed to identify correctness bugs in the Turso database by comparing its results against those from SQLite for generated SQL statements. This skill is essential for developers working with Turso who need to ensure that their SQL statements produce consistent and accurate results across different database systems. By running the fuzzer, users can uncover discrepancies that may lead to runtime errors or unexpected behaviors in applications that rely on Turso.
To use the Differential Fuzzer, developers can execute a series of commands in a bash environment. The tool allows for both single runs and continuous fuzzing, enabling users to generate a specified number of SQL statements and check for correctness against SQLite. The fuzzer also supports reproducibility through the use of deterministic seeds, making it easier to track down specific bugs when they occur. Additionally, users can opt to keep database files for further debugging, providing a comprehensive output that includes executed SQL statements, database schemas, and state files.
The fuzzer is particularly valuable in continuous integration (CI) and production environments where maintaining database integrity is critical. By integrating the fuzzer into the CI pipeline, developers can automatically run tests against their SQL statements, ensuring that any regressions are caught early in the development process. The tool's output files, which include detailed logs and minimized reproduction scripts, facilitate a deeper understanding of any issues that arise, allowing developers to quickly address and resolve them.
In summary, the Differential Fuzzer is a powerful asset for developers using Turso, providing a systematic approach to identifying and fixing SQL correctness bugs. Its ability to automate testing and generate detailed reports makes it an indispensable tool for maintaining high-quality database interactions.
When to use it
Use the Differential Fuzzer when you need to validate SQL statements in Turso against expected results from SQLite, especially during testing phases.
When not to use it
This tool is not suitable for general-purpose SQL debugging or for databases other than Turso and SQLite.
What you can build with it
Validating SQL Statements
Use the fuzzer to ensure that SQL statements in your Turso application produce the same results as those in SQLite.
Automating Bug Detection
Incorporate the fuzzer into your CI pipeline to automatically catch SQL bugs before they reach production.
Debugging SQL Errors
Leverage the fuzzer's output to pinpoint and reproduce SQL errors for easier debugging.
How to install Differential Fuzzer
View source1. Install with the skills CLI
npx skills add tursodatabase/turso/differential-fuzzer --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by tursodatabaseDifferential Fuzzer
Always load Debugging skill for reference
The differential fuzzer compares Turso results against SQLite for generated SQL statements to find correctness bugs.
Location
testing/differential-oracle/fuzzer/
Running the Fuzzer
Single Run
# Basic run (100 statements, random seed)
cargo run --bin differential_fuzzer
# With specific seed for reproducibility
cargo run --bin differential_fuzzer -- --seed 12345
# More statements with verbose output
cargo run --bin differential_fuzzer -- -n 1000 --verbose
# Keep database files after run (for debugging)
cargo run --bin differential_fuzzer -- --seed 12345 --keep-files
# All options
cargo run --bin differential_fuzzer -- \
--seed <SEED> # Deterministic seed
-n <NUM> # Number of statements (default: 100)
-t <NUM> # Number of tables (default: 2)
-c <NUM> # Columns per table (default: 5)
--verbose # Print each SQL statement
--keep-files # Persist .db files to disk
Continuous Fuzzing (Loop Mode)
# Run forever with random seeds
cargo run --bin differential_fuzzer -- loop
# Run 50 iterations
cargo run --bin differential_fuzzer -- loop 50
Docker Runner (CI/Production)
# Build and run from repo root
docker build -f testing/differential-oracle/fuzzer/docker-runner/Dockerfile -t fuzzer .
docker run -e GITHUB_TOKEN=xxx -e SLACK_WEBHOOK_URL=xxx fuzzer
Environment variables for docker-runner:
TIME_LIMIT_MINUTES- Total runtime (default: 1440 = 24h)PER_RUN_TIMEOUT_SECONDS- Per-run timeout (default: 1200 = 20min)NUM_STATEMENTS- Statements per run (default: 1000)LOG_TO_STDOUT- Print fuzzer output (default: false)GITHUB_TOKEN- For auto-filing issuesSLACK_WEBHOOK_URL- For notifications
Output Files
All output goes to simulator-output/ directory:
| File | Description |
|---|---|
test.sql | All executed SQL statements. Failed statements prefixed with -- FAILED:, errors with -- ERROR: |
schema.json | Database schema at end of run (or at failure) |
test.db | Turso database file (only with --keep-files) |
test-sqlite.db | SQLite database file (only with --keep-files) |
Reproducing Errors
Always follow these steps
-
Find the seed and profile in the error output:
INFO: Starting differential_fuzzer with config: SimConfig { seed: 12345, ..., weight_profile: Writes } -
Re-run with that seed and profile (a seed only replays under the same profile):
cargo run --bin differential_fuzzer -- --seed 12345 --profile writes --verbose --keep-files -
Read the minimized reproduction first. On an oracle failure the fuzzer writes these files to
simulator-output/:minimized.sql- a shrunken state script plus the shrunken failing statement, produced automatically. Start here.turso-state.sql/sqlite-state.sql- each engine's full state as a replayable script, when you need more than the minimized version kept.test.sql- every executed statement (the failing one is marked-- FAILED:). The minimizer falls back to replaying this history when the failure depends on how the state was built, not just its contents.schema.json- table structure at failure time.
-
Probe the reproduction with
differential_probe. It runs a statement-per-line script on Turso and SQLite side by side, prints both outcomes for every statement, marks divergences, and compares the final table contents. Exit code 1 means something diverged.cargo run -q -p differential-fuzzer --bin differential_probe -- \ simulator-output/minimized.sqlUse it instead of piping SQL into the two shells: the tursodb shell cannot
ATTACH ':memory:' AS aux, so fuzzer reproductions with anauxschema only run correctly through the probe. Reading from stdin also works:echo "SELECT ~X'96';" | cargo run -q -p differential-fuzzer --bin differential_probe. -
Bisect by editing the script. Copy
minimized.sql, simplify one thing at a time (replace an expression with a constant, drop a column, drop a state line), and re-run the probe after each edit. The divergence marker tells you immediately whether the edit kept the bug. This loop usually ends at a one-line kernel you can hand toEXPLAINon both engines. -
Create a regression test in
.sqltest(preferred) or.rsfrom the kernel. Always load the Debugging skill for reference.
Understanding Failures
Oracle Failure Types
- Row set mismatch - Turso returned different rows than SQLite
- Turso errored but SQLite succeeded - Turso rejected valid SQL
- SQLite errored but Turso succeeded - Turso accepted invalid SQL
- Schema mismatch - Tables/columns differ after DDL
Warning (non-fatal)
- Unordered LIMIT mismatch - LIMIT without ORDER BY may return different valid rows
Key Source Files
| File | Purpose |
|---|---|
main.rs | CLI parsing, entry point |
runner.rs | Main simulation loop, executes statements on both DBs |
oracle.rs | Compares Turso vs SQLite results |
schema.rs | Introspects schema from both databases |
memory/ | In-memory IO for deterministic simulation |
Tracing
Set RUST_LOG for more detailed output:
RUST_LOG=debug cargo run --bin differential_fuzzer -- --seed 12345
Frequently asked questions about Differential Fuzzer
Similar skills
ClickHouse Logs Queries
Efficiently manage Supabase logs with ClickHouse SQL.
EF Core D2 Database Diagram Generator
Visualize your EF Core models as D2 diagrams effortlessly.
Safe SQL Execution
Ensure secure SQL execution in Supabase applications.
Oracle to PostgreSQL Migration
Identify migration risks between Oracle and PostgreSQL.
SSMA Console
Streamline Oracle to SQL Server migrations with ease.
SQL Performance Optimization
Enhance SQL query efficiency across all databases.
