Profiling the validator showed roughly half of all validation time re-deriving
answers that cannot change — collectConstraints 22%, getOwnMetadata 12%,
getMetadataChain 9%, getProperties 4%, getMetadata 3%, plus 8% GC from the
allocation churn. The constraint predicates themselves were under 1%.
Decorator metadata is fixed once classes are declared, so the derived structures
are now memoized per prototype: the validation plan, the serialization plan, the
deserialization plan, and serializer/deserializer instances, which were being
constructed fresh for every property of every object. MetadataStorage carries a
version counter that invalidates the caches when metadata is written, so
registerDecorator after first use still works — covered by a test.
Measured against JSON.parse + JSON.stringify as a fixed reference:
validate (50 orders) 221.6 us -> 49.6 us 4.5x
validate (10 orders) 47.8 us -> 12.9 us 3.7x
toInstance (50 orders) 255.1 us -> 74.0 us 3.4x
toInstance (10 orders) 64.6 us -> 19.0 us 3.4x
toPlain (50 orders) 294.4 us -> 95.3 us 3.1x
Reliability, in the same pass:
- maxDepth option (default 64) on every mapping function, on validate(), and on
configure(). All three engines recurse, so a payload nested thousands of levels
deep could exhaust the call stack. Cycles were already handled; legitimate deep
nesting was not bounded.
- each: true failures now name the element that failed ("failed at index 3"). A
bad entry in a 200-item array previously produced a message that could not
locate it. A message function now receives the failing element as args.value
rather than the whole array; caller-supplied strings stay verbatim.
150 tests (up from 136), all green on the existing suite unchanged.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SAcqrz3FcadkYr3xG32CjK
Claude
6e458fdd43