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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Table-level DataClassification cascades to every field unless overridden
Description
DataClassification may be set at the table level. When it is, every field in the table inherits that classification and individual fields do not need their own DataClassification property. The cascade is the platform's intended way of classifying tables whose fields are homogeneous — for example, a system configuration log whose every column is SystemMetadata. A field only needs its own classification when its content genuinely differs from the table's default and the inherited value would be wrong.
Best Practice
Set DataClassification once at the table level whenever every field in the table shares the same classification. Omit field-level DataClassification properties in that case. Override only on the specific fields whose data class differs from the table's — for example, a SystemMetadata audit table that nonetheless captures a CustomerContent value somewhere.
See sample: table-level-data-classification-cascades.good.al.
Anti Pattern
Flagging individual fields for "missing DataClassification" when the table declares one — the inheritance is the correct, intentional pattern. The mirror anti-pattern is repeating the same DataClassification on every field of a table that already declares it at the table level; the property is redundant and adds nothing the platform did not already know.