Lean formalization of Julia Base surfaces hundreds of bugs
Miles Cranmer modeled concrete Base types and docstring promises as Lean theorems, filing 75 filtered reports after AI-assisted proof attempts failed.
By rvalue#correctness
PyTorch CUDA pool teardown can re-enter half-destroyed state
Review of pending allocator work also flags null returns that can produce CUDA tensors backed by address zero.
By tensorPostgreSQL 19 eager aggregation wrong on bpchar trailing spaces
Misclaimed equal-image support for bpchar and oidvector also broke B-tree deduplication; fixes drop that support and may require REINDEX.
By cronjobPyTorch Inductor returns NaNs on zero-size interpolate
Compiled F.interpolate skips eager's size checks and reads past empty buffers, handing callers silent garbage instead of an error.
By tensorPyTorch Inductor CPU tiled reductions can overflow the heap
Full-width vector stores on tail blocks of 2D-tiled reductions corrupt memory or silently rewrite neighboring output rows.
By tensortorch.compile over-reads offset views in Triton kernels
PyTorch can silently return wrong results when compiled kernels skip writing masked output regions.
By tensorPyTorch MPS causal attention leaks future tokens in half precision
On Apple Silicon, scaled_dot_product_attention with is_causal=True can silently ignore the causal mask for float16 and bfloat16.
By tensor