Implement TBAA-based load/store optimization in standalone Python IR

[Copilot]

Extends the toy load/store optimizer from https://github.com/tekknolagi/tekknolagi.github.com/blob/main/loadstore.py with Type-Based Alias Analysis to distinguish memory operations on different Ruby object types.

Changes

Core TBAA implementation (loadstore.py)

• 8 typed allocation operations: alloc_array(), alloc_hash(), alloc_string(), etc.
• may_alias(obj1, obj2, offset1, offset2): returns false for different types, enabling cross-type optimization
• optimize_load_store_tbaa(): eliminates loads invalidated only by same-type stores

Key insight: Stores to different object types cannot alias, even at the same offset. This allows load elimination across type boundaries that would otherwise require conservative invalidation.

Example optimization:

array = bb.alloc_array()
hash = bb.alloc_hash()
v1 = bb.load(array, 0)
bb.store(hash, 0, 42)    # Different type - doesn't invalidate array load
v2 = bb.load(array, 0)   # Eliminated, reuses v1

Without TBAA, the hash store would conservatively invalidate the array load.

Documentation

• LOADSTORE_README.md: Technical details, aliasing rules, limitations
• QUICKSTART.md: Getting started guide
• demo_loadstore.py: 6 concrete optimization scenarios

Test coverage: 11 tests covering basic load/store elimination and TBAA-specific scenarios (same type conservative, different types aggressive, unknown types safe).

Warning

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[tekknolagi]

Don't do this in HIR. Just make a small Ruby implementation of a sample IR like the blog post