Java parsed already, but the producer failed every Java row because no obligation facts existed for the
language and that failure took roles and def_use down with it. PHP had no grammar. Now: tree-sitter-php in the
semantic extra with PHP node kinds in the CST reader; obligation facts for Jenkins/Stapler, Spring Security and
Servlet code (java.toml) and for Laravel, WordPress and Symfony (php.toml), each header naming the training
clones and references the names were checked against; a language with an IR but no obligation facts keeps
roles and def_use and records obligations as unchecked (None), which the engineered features treat as missing,
never as zero. Proven on the committed pool: 6 of 6 Java rows and 33 of 33 PHP rows of one fix change each now
carry semantic features. Implemented by Codex; gated here with ruff, mypy and the full suite.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Two instrument findings from the first access-control feature table (952 rows, 74 positive rows):
1. A fix that adds a guard is, replayed base-to-head, a push that removes it. The diff producer only kept
hunks with added lines at head, so 38 of 74 positive rows had no hunk in their file at all and 69 of 74
were "not on a changed line", while 60% of ordinary rows were. The diff annotation separated the labels
by construction and was blind to exactly the access-control shape. The producer (version 2) now records
per file the head lines after which the push removed code; distance and on_changed_line count them, the
model's hunks input renders them as removed_after_line, and diff.deletion_count is an engineered feature.
2. 150 rows (16%, every positive of one repository) read empty files from the worktree although git holds
the blobs; the build ran while another process checked out from the same clone. _full_checkout now
proves the checkout: git status must be clean, a dirty tree is restored once, then InstrumentFailure
checkout_incomplete. The table script cross-checks every unread row against the blob size and refuses
to screen a partly unread tree, and records the diff-scoped recall ceiling (positive rows a label-blind
enumeration would reach).
Co-Authored-By: Claude Fable 5.1 <[email protected]>
openultrasast.stats: Wilson intervals (statsmodels), exact McNemar, a
repository-clustered percentile bootstrap and its paired form with one
quantile convention, grouped folds (GroupKFold, leave-one-group-out), and
per-column separation (ROC AUC) for the leak audit and the signal screen.
Checked against the benchmark scorer's Wilson and the learn harness's
McNemar. hunt/features.py turns the feature table into the engineered
frame (distances, counts, flags) and keeps the map from every engineered
feature to the annotation the model is shown, so an ablation mask drops
both, and screen() says which annotation carries signal before a model
call is spent. The [hunt] extra now carries the libraries; the core
install is unchanged. The learn harness's own copies stay until that line
is revived.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
