mandrean opened a new pull request, #3514:
URL: https://github.com/apache/fory/pull/3514

   ## Why?
   
   This is a follow-up to #3342 and #3344 for the `.withAsyncCompilation(true)` 
path.
   
   While investigating a downstream flaky serialization failure on the same 
general `ObjectStreamSerializer`/customized JDK serialization area, I found a 
separate issue in the async meta-shared layer JIT path. 
`ObjectStreamSerializer` can trigger that path for classes such as 
`TreeSet`/`TreeMap` subclasses, and the generated layer serializer could be 
bootstrapped through the wrong path, causing failures such as 
`NoSuchMethodException` and `ClassCastException`.
   
   ## What does this PR do?
   
   This PR fixes async meta-shared layer bootstrap for `ObjectStreamSerializer` 
by:
   
   - caching layer context for generated meta-shared layer codec classes
   - using that cached context to initialize the interpreter 
`MetaSharedLayerSerializer` delegate
   - removing the broken second-stage async swap for layer serializers
   - adding regression coverage for async-compatible `ObjectStreamSerializer` 
cases with nested `TreeSet`/`TreeMap` subclasses and customized JDK 
serialization
   
   ## Related issues
   
   - Follow-up to #3342
   - Follow-up to #3344
   
   ## AI Contribution Checklist
   
   - [x] Substantial AI assistance was used in this PR: `yes`
   - [x] If `yes`, I included a completed [AI Contribution 
Checklist](https://github.com/apache/fory/blob/main/AI_POLICY.md#9-contributor-checklist-for-ai-assisted-prs)
 in this PR description and the required `AI Usage Disclosure`.
   
   - [x] If `yes`, I can explain and defend all important changes without AI 
help.
   - [x] If `yes`, I reviewed AI-assisted code changes line by line before 
submission.
   - [x] If `yes`, I ran adequate human verification and recorded evidence 
(checks run locally or in CI, pass/fail summary, and confirmation I reviewed 
results).
   - [x] If `yes`, I added/updated tests and specs where required.
   - [x] If `yes`, I validated protocol/performance impacts with evidence when 
applicable.
   - [x] If `yes`, I verified licensing and provenance compliance.
   
   AI Usage Disclosure
   - substantial_ai_assistance: yes
   - scope: refactor suggestions, tests
   - affected_files_or_subsystems: `java/fory-core` meta-shared layer codec 
bootstrap, `ObjectStreamSerializer` async layer JIT path, 
`ObjectStreamSerializerTest`
   - human_verification: reviewed changes line by line; ran `mvn -pl fory-core 
-am -Dtest=ObjectStreamSerializerTest,JITContextTest 
-Dsurefire.failIfNoSpecifiedTests=false test` locally and reviewed the passing 
results; also validated the downstream reproducer with the patched local Fory 
build and reviewed the passing targeted test result (which fails without the 
fixes here)
   - performance_verification: exploratory local benchmark checks did not show 
a consistent overall regression in the general compatible/meta-shared proxy 
suite; no formal performance claim is made in this PR
   - provenance_license_confirmation: Apache-2.0-compatible provenance 
confirmed; no incompatible third-party code introduced
   
   ## Does this PR introduce any user-facing change?
   
   - [ ] Does this PR introduce any public API change?
   - [ ] Does this PR introduce any binary protocol compatibility change?
   
   ## Benchmark
   
   No formal benchmark claim is included in this PR.
   
   This PR is a correctness fix for async layer serializer bootstrap. I did run 
exploratory local checks against the existing general compatible/meta-shared 
proxy benchmarks and did not see a consistent overall regression.
   
   I also locally created a focused JMH benchmark intended to exercise the 
exact `ObjectStreamSerializer` async layer JIT hot path touched by this change. 
However, on the baseline code that benchmark reproduces the bug fixed by this 
PR and fails during setup with the same `NoSuchMethodException` / 
`ClassCastException` async layer bootstrap errors, so it was not possible to 
establish a reliable before-fix baseline from that targeted benchmark.


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