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Guides

The reference behind the generators

Why a check digit is worth computing, which ranges a standards body has reserved so your fixtures cannot collide with anything real, and what makes a random dataset reproducible. The reasoning the tools are built on, written out.

  1. 01

    Reserved Ranges for Test Data: A Working Reference

    Every block that a standards body has set aside so your fixtures can never collide with something real — phone numbers, IP addresses, domains, MAC addresses, identifiers.

    2026-08-10 · 11 min read

  2. 02

    Checksums Your Test Data Has to Satisfy

    Luhn, mod-97, ABA, GTIN and the VIN transliteration — how the five check digits you meet most often actually work, and why faking them wastes your fixture.

    2026-08-08 · 12 min read

  3. 03

    Seeded Randomness: How to Make Test Fixtures Reproducible

    Math.random() cannot be seeded, and that is why your test suite is flaky. What to use instead, and how to derive a whole dataset from one string.

    2026-08-06 · 11 min read

  4. 04

    Why Copying Production Data Into Staging Is a Liability

    Under the GDPR a database dump does not stop being personal data because you renamed the environment. What the law actually says, why masking usually fails, and where synthetic data fits.

    2026-08-04 · 12 min read

  5. 05

    Unicode Edge Cases Every Form Should Survive

    Combining marks, the Turkish dotless i, ZWJ emoji, bidi overrides and the utf8mb4 trap — the inputs that break text handling, and why they belong in your fixtures.

    2026-08-02 · 13 min read