bcquality/microsoft/knowledge/testing/test-data-must-be-random-and-complete.md
Michael Dieringer cc7c1f2ee0 Address Jesper Schulz-Wedde's review on PR #156
- Rename 3 articles so their .good.al/.bad.al companion stems match
  (do-not-change-primary-key, testfield-required-setup-field,
  al-identifiers-english), fixing the R14 orphan-sample errors.
- do-not-change-primary-key.good.al: include Flow in the new table's
  own primary key so it actually models the discriminating dimension.
- al-build-output-must-not-pollute-project-root.md: drop the
  unsubstantiated AL0197 causal claim and the non-existent
  al.outputPath setting; reframe as build-artifact hygiene sourced
  from ALTool --outfolder / al_build outputPath.
- prefer-email-module.md: Email Message is Codeunit 8904, not a table;
  distinguish it from the underlying Sent/Outbox/Draft storage.
- file-datatype-saas.md: File.Open/Create/Read/Write fails to compile
  against a Cloud-scoped project, it does not compile and silently
  fail at runtime.
- namespace-must-be-verified-from-source.md: narrow to "resolve from
  the referenced object's source or symbols," since source-file line
  one is not the only authoritative source (symbol packages, comments
  before the namespace line).
- test-data-must-be-random-and-complete.md: drop "assume an empty
  database" and "collision-free" absolutes; reframe around
  independence from unrelated business records and reserving explicit
  values for scenario-defining inputs.
- binary-choice-must-be-boolean.md: scope to genuine true/false
  semantics, not mechanical two-member-enum-to-boolean conversion.
- document-report-word-layout.md: scope down to a sourced Microsoft
  Learn recommendation instead of an unconditional performance
  guarantee; cite the three Learn pages.
- Wire the new articles into their review skills' candidate-selection
  signals (file-datatype-saas, prefer-email-module,
  namespace-must-be-verified-from-source, var-parameters-require-an-
  addressable-variable) so they can actually enter a worklist.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-09-21 22:25:26 +02:00

2.4 KiB

bc-version domain keywords technologies countries application-area
all
testing
testing
test-data
random
library
any
al
w1
all

Generate Test Data Programmatically, Never Assume Existing Records

Contributions welcome — open a PR to refine or extend this article.

Description

A BC test company normally contains initialized system/setup data — an AL test suite should not assume an empty database, but it must be independent of unrelated business records: create the records and setup it owns rather than looking up a specific code, number, or name assumed to already exist, since that makes the test fail for reasons unrelated to the code under test. Every mandatory field on a created record also needs a value that respects its declared length; a partial setup that merely passes validation is not sufficient.

Not every value should be generated, though. Incidental fixture data — identifiers, names, descriptions — should generally come from the standard library codeunits rather than be tied to specific existing data. But values that materially define the scenario under test — amounts, quantities, percentages, dates, thresholds, rounding precision — should stay explicit and deliberately chosen, not randomized: a rounding test needs values placed deliberately around the rounding boundary, not a random one that might miss it entirely.

Best Practice

Use the standard library codeunits (Library - ERM, Library - Inventory, Library - Sales, Library - Utility) to generate incidental fixture values — they produce valid, unique-enough data via number series and controlled randomness, not a mathematical collision-free guarantee — and fill every mandatory field with correctly-sized data. Keep values that define the scenario's expected outcome explicit and fixed. Reserve hardcoded values for tests that validate an external contract itself — a fixed JSON schema, an EDIFACT message, a counterparty code — where the hardcoded value documents the specification rather than arbitrary test logic.

See sample: test-data-must-be-random-and-complete.good.al.

Anti Pattern

Looking up a record assumed to already exist (a hardcoded payment method or customer number) instead of creating it, or leaving mandatory fields empty or underfilled because validation happens to allow it.

See sample: test-data-must-be-random-and-complete.bad.al.