The previous LLM-generated knowledge files contained factual
hallucinations. The most visible was the claim that `FindFirst` /
`FindLast` "forces a full-table scan" on an unfiltered record - it does
not; those APIs return a single row via the current key.
Other inaccuracies the audit found and fixed:
* `FindSet(true)` was described as "taking a LockTable". The correct
upstream phrasing is that `FindSet(true)` sets
`ReadIsolation::UpdLock` on the read. UpdLock and LockTable are
related but distinct mechanisms.
* The list of production-scale tables had been invented beyond the
upstream source (e.g. "Detailed Cust. Ledg. Entry") without a
citation. The regenerated list matches the ten tables upstream lists
with their P95 row counts.
* `SetLoadFields` guidance had been augmented with an extra mechanism
claim ("the database resolves the filter using the index without
hydrating the value") not present in upstream.
Approach: full regeneration of `microsoft/knowledge/` from the six
upstream BCApps Code Review instruction files, with Microsoft Learn /
the AL language reference as a secondary source. Every claim in every
regenerated file is anchored to a verbatim upstream quote (or a Learn
URL); the audit trail lives in artifacts/trace-<domain>.json on the
session workspace.
The PR #11 transaction/error-handling cluster is preserved verbatim:
* performance/understand-implicit-transaction-boundary.md
* performance/codeunit-run-as-atomic-sub-operation.{md,good.al,bad.al}
* performance/codeunit-run-requires-prior-commit-inside-transaction.{md,good.al,bad.al}
* performance/use-tryfunction-for-error-catching-not-rollback.{md,good.al,bad.al}
* performance/avoid-commit-inside-loops.{md,good.al,bad.al}
* security/commitbehavior-attribute-scopes-explicit-commits.{md,good.al,bad.al}
* testing/transactionmodel-attribute-governs-test-transactions.{md,good.al,bad.al}
These articles already cite Microsoft Learn and were carefully
cross-referenced; the regeneration skips their topics rather than
duplicating them.
File counts after regeneration:
performance 35 .md (5 preserved + 30 new)
privacy 17 .md
security 18 .md (1 preserved + 17 new)
style 33 .md
testing 1 .md (preserved)
ui 19 .md
upgrade 18 .md
Total 141 atomic knowledge files, each strictly one rule. All pass
.github/scripts/validate_frontmatter.py with 0 errors and 0 warnings.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
1.6 KiB
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DataClassification is required on table fields containing sensitive data
Description
DataClassification is the AL property that tells the platform what kind of data a table field stores so that telemetry, GDPR data-subject requests, and the platform's audit surfaces can treat it correctly. It is required on any field that holds personal or customer data. The default value SystemMetadata means "no user or customer data" — applying it to a field that actually holds PII (an email address, a customer name, an employee code) is an under-classification and a privacy bug, even though the code still compiles.
Best Practice
Set DataClassification to the value that matches the data the field actually stores. A Customer."E-Mail"-style field is CustomerContent (data belonging to the tenant's customers); a personal identifier such as an employee number or user ID is EndUserIdentifiableInformation or EndUserPseudonymousIdentifiers depending on whether it is directly identifying. Choose the classification at field definition time — fixing it later is a schema change.
See sample: data-classification-required-on-pii-fields.good.al.
Anti Pattern
Declaring a field that stores PII with DataClassification = SystemMetadata to silence the compiler warning. The field compiles but the platform now treats customer data as system metadata in telemetry, GDPR exports and admin reports.
See sample: data-classification-required-on-pii-fields.bad.al.