SACB — corpus source
The parquet files in this repository are the materialised benchmark: each record carries a full file map, hidden tests and reference fix, which is everything a harness needs to run SACB.
This directory is what those records were built from, so the corpus can be regenerated, extended, or ported to another language.
Layout
corpus/<lang>/<repo>/repo/ the base tree, in its CORRECT state
corpus/<lang>/<repo>/tasks/<id>/task.json metadata + the bug report
corpus/<lang>/<repo>/tasks/<id>/break/ overlay that injects the defect
corpus/<lang>/<repo>/tasks/<id>/tests/ hidden tests
corpus/<lang>/<repo>/tasks/<id>/gold/ optional; defaults to the base tree
The base repository is the correct code and each task overlays a defect on top of it. The reference fix is therefore the base itself, which is why a task cannot ship with a "solution" that does not work. For add-a-feature tasks the break overlay simply removes the implementation.
Tools
| script | role |
|---|---|
tools/build_corpus.py |
validate every task and emit the JSONL the parquet is built from |
tools/make_tasks.py |
helper used by the authoring scripts |
tools/tasks_*.py |
the authoring batches, one defect or compound per entry |
tools/gen_compounds.py |
compose compound tasks from validated single defects |
tools/select_corpus.py |
choose the shipped mix to hit a target resolved rate |
tools/upload_sacb.py |
publish to this repository |
tools/harness-tests/ |
tests for the llama-eval harness itself |
These import eval_sandbox and agentic_eval from examples/llama-eval/ in
llama.cpp, so point sys.path at a checkout that has them.
Regenerating
python3 tools/build_corpus.py --corpus corpus --out agentic-corpus.jsonl
fail_to_pass and pass_to_pass are derived, never written by hand: the
tests are run once against the defective tree and once against the reference,
and the sets fall out of the difference. The builder rejects a task whose defect
no test exercises, and one whose reference fix does not itself pass. It caught
several authoring mistakes that way, which is the point.
Adding a task
Add an entry to a tasks_*.py batch giving the exact anchor text to replace and
the tests, run the builder, and fix whatever it rejects. Anchors are matched
exactly and must occur exactly once, so a defect can never silently fail to be
injected.
Adding a language
The harness takes a new language as a LangSpec entry (linter argv, test
runner, packages) without any other change. Java was scoped out of this release
but needs no harness work — a JDK tarball plus the JUnit console-standalone jar
would keep the no-container property.
Calibration
CALIBRATION.md records every measurement taken while tuning this corpus, and
in particular the four assumptions about difficulty that measurement
contradicted. Read it before changing the composition — the headline is that
repository size, not defect count, is what makes these tasks hard.