- Paper Q: Unified Grammar Engine for AI-Language Collaboration (緊急性高)
- Paper R: ScopeBox Theory - Zero-Cost Abstraction (Gemini絶賛)
- Paper S: LoopForm Revolution - PHI Problem Solution (技術革新)
Updated PAPER_INDEX.md with new papers and reorganized priorities.
Added comprehensive README documentation for each new paper.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
## Summary
Documented the "init block vs fields-at-top" design discussion as a valuable example of AI-human collaboration in language design.
## Changes
### Paper G (AI Collaboration)
- Added field-declaration-design.md documenting the entire discussion flow
- Showcased how complex init block proposal evolved to simple "fields at top" rule
- Demonstrates AI's tendency toward complexity vs human intuition for simplicity
### Paper H (AI Practical Patterns)
- Added Pattern #17: "Gradual Refinement Pattern" (段階的洗練型)
- Documents the process: Complex AI proposal → Detailed analysis → Human insight → Convergence
- Field declaration design as a typical example
### Paper K (Explosive Incidents)
- Added Incident #046: "init block vs fields-at-top incident"
- Updated total count to 46 incidents
- Shows how a single human comment redirected entire design approach
## Design Decision
After analysis, decided that BoxIndex should remain a compiler-internal structure, not a core Box:
- Core Boxes: User-instantiable runtime values (String, Integer, Array, Map)
- Compiler internals: BoxIndex for name resolution (compile-time only)
- Clear separation of concerns between language features and compiler tools
## Philosophy
This discussion exemplifies key principles:
- The best design needs no explanation
- Constraints provide clarity, not limitation
- "Everything is Box" doesn't mean "compiler internals are Boxes"
- AI tends toward theoretical completeness; humans toward practical simplicity
🐱 Sometimes the simplest answer is right in front of us\!
Changes to resolver.py:
- Improved PHI value tracking in _value_at_end_i64() (lines 268-285)
- Added trace logging for snap hits with PHI detection
- Fixed PHI placeholder reuse logic to preserve dominance
- PHI values now returned directly from snapshots when valid
Changes to llvm_builder.py:
- Fixed externcall instruction parsing (line 522: 'func' instead of 'name')
- Improved block snapshot tracing (line 439)
- Added PHI incoming metadata tracking (lines 316-376)
- Enhanced definition tracking for lifetime hints
This should help debug the string carry=0 issue in esc_dirname_smoke where
PHI values were being incorrectly coerced instead of preserved.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Added paper-g-ai-assisted-compiler folder documenting:
- Week-long LLVM backend development with AI assistance
- Key insights from PHI/SSA struggles to Resolver API solution
- Development log capturing the chaotic reality
- Abstract in both English and Japanese
Key quote: 'I don't remember anymore' - capturing the authentic
experience of intensive AI-assisted development where the process
itself becomes the research data.
This represents potentially the first fully documented case of
building a compiler backend primarily through AI assistance.
## LLVM Call Instruction Modularization
- Moved MirInstruction::Call lowering to separate instructions/call.rs
- Follows the principle of one MIR instruction per file
- Call implementation was already complete, just needed modularization
## Phase 21 Documentation
- Moved all Phase 21 content to private/papers/paper-f-self-parsing-db/
- Preserved AI evaluations from Gemini and Codex
- Academic paper potential confirmed by both AIs
- Self-parsing AST database approach validated
## Next Steps
- Continue monitoring ChatGPT5's LLVM improvements
- Consider creating separate nyash-llvm-compiler crate when LLVM layer is stable
- This will reduce build times by isolating LLVM dependencies
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
