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To generate repeatable test addresses with AddressLab, define the target country and fields, choose a record count and fixture mode, set a fixed seed, preview the rows, then export and save the settings and fixture version with them. This creates reproducible synthetic inputs for software tests—not proof that an address, person, property, or delivery point exists.
What AddressLab test addresses can—and cannot—prove
Synthetic address data is useful when you need to test whether an application accepts, stores, displays, imports, or exports the address formats its users may enter. AddressLab lists software development, form validation, product demonstrations, QA scripts, and database seed records as intended use cases. Its US address generator guidance puts the key distinction plainly: “A syntax pass is not a delivery check.”
| Approach | What it checks | What it does not establish |
|---|---|---|
| Synthetic fixture generation | Whether software handles field structures, formats, boundary cases, and repeatable test inputs. | Whether a real person, property, or deliverable address exists. |
| Postal or address validation | Whether an address can be matched or checked through an applicable postal or validation service. | Whether your application handles its own form, storage, display, or export behavior correctly. |
For US computerized mailing lists, the USPS Domestic Mail Manual, section 602, describes use of CASS-certified address-matching software and current USPS address products. A separate service such as Google’s Address Validation API addresses validation rather than application testing; Google also notes a restriction involving artificially created address inputs. Check a provider’s terms before submitting synthetic fixtures.
Build a repeatable fixture in AddressLab
- Set the country and schema. Identify the form, API, import, or database fields your test must cover. Select the needed fields and their order deliberately. Address layouts vary by country, so use the relevant country-specific generator guidance rather than assuming a US layout applies everywhere. AddressLab describes its regional coverage; consult the relevant country page for specific fixture coverage.
- Choose the number and type of records. The current generator documents an input range of 1–100 records. Decide whether ordinary cases are enough or whether you also need labeled boundary cases. AddressLab’s generator documentation identifies the current range and fixture options.
- Set a fixed seed and note the fixture version. The same seed and options are intended to reproduce the same synthetic rows. Reproduction also depends on keeping the same settings and fixture version: the documentation identifies version
2026-09-07.2, which is a version-specific identifier, not a permanent one. Save both the seed and version alongside your test case. - Preview for coverage and field alignment. Confirm that each value appears under the intended field and that paired fields remain together. Include cases relevant to your product’s failure modes, such as leading-zero postal codes, Unicode, apartment or unit data, punctuation, long values, and country-specific field arrangements.
- Export and preserve the fixture. Export CSV or JSON and keep the settings file and fixture version with the output. AddressLab warns that updates can change generated output. Treat postal codes as strings: a spreadsheet may convert
02108to2108if it imports the value as a number. Set the postal-code column to text when importing a CSV; in the documented workflow, JSON preserves postal codes as strings. - Replay the fixture through the system under test. Compare the saved, displayed, and exported values with the original input. A fixed seed makes it easier to reproduce a defect, but does not independently establish geographic or operational validity.
AddressLab says generation and export take place locally in the browser. That is a claim about this documented tool, not a general privacy guarantee for all test-data generators.
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Test the boundaries that commonly break address handling
- Postal-code typing: Check that leading zeros survive CSV import, database storage, display, and re-export.
- Character handling: Test Unicode, punctuation, and long address lines through validation and serialization.
- Units and field layout: Verify apartment or unit values stay associated with the right address and that country-specific fields map to the expected schema.
- Round trips: Compare input values against persisted, displayed, and exported output to catch truncation, normalization, or field-order errors.
- Deterministic regression cases: Retain the seed, options, settings file, and fixture version so a defect can be replayed against the same inputs.
Keep synthetic records out of real-world workflows
AddressLab states that its records are synthetic and intended for development and testing, not delivery or identity use. Plausible formatting does not verify a house number, building, person, or delivery point. Do not use generated records in production registration, shipping, financial, authentication, or identity workflows.
Generated email-format values need particular care: AddressLab warns they may use common provider domains and could coincide with real mailboxes. Do not send mail to generated samples or use them for real registrations. For delivery testing, use a mailbox controlled by your QA team. AddressLab’s form-testing guidance discusses that safeguard.
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