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nyash-codex 4ef5eec162 feat(mir): Phase 84-2 CopyTypePropagator for Copy chain type propagation

- Add CopyTypePropagator box (ChatGPT Pro design) for fixed-point
  Copy instruction type propagation
- Integrate into lifecycle.rs before return type inference
- Case D reduced from 12 to 9 (25% reduction)

Implementation:
- src/mir/phi_core/copy_type_propagator.rs: New box with fixed-point loop
- src/mir/phi_core/mod.rs: Add module export
- src/mir/builder/lifecycle.rs: Call propagator before return inference

Test results:
- Baseline: 494 passed, 33 failed (was 489/34)
- Case D: 9 remaining (from 12)
- Unit tests: 4/4 passed

Remaining 9 Case D breakdown:
- GroupA: Loop Edge Copy (7 cases) - PHI incoming needs Copy trace
- GroupB: Multi-level PHI (2 cases) - Recursive PHI resolution needed

Phase 84-3 will address GroupA with Edge Copy tracing in GenericTypeResolver.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

2025-12-02 19:37:01 +09:00

llvm

docs: add MIR13 mode doc and set PHI-off as default; bridge lowering split (if/loop/try); llvmlite resolver stabilization; curated runner default PHI-off; refresh CURRENT_TASK.md

2025-09-17 10:58:12 +09:00

main

feat(mir): Phase 84-2 CopyTypePropagator for Copy chain type propagation

2025-12-02 19:37:01 +09:00

self_current_task

phase: 20.49 COMPLETE; 20.50 Flow+String minimal reps; 20.51 selfhost v0/v1 minimal (Option A/B); hv1-inline binop/unop/copy; docs + run_all + CURRENT_TASK -> 21.0

2025-11-06 15:41:52 +09:00

selfhost

phase: 20.49 COMPLETE; 20.50 Flow+String minimal reps; 20.51 selfhost v0/v1 minimal (Option A/B); hv1-inline binop/unop/copy; docs + run_all + CURRENT_TASK -> 21.0