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NOTICES.md

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+# NOTICES — MBPP held-out benchmark
+
+Derived from **MBPP (Mostly Basic Python Problems)**, Austin et al., 2021, Google Research, distributed as `google-research-datasets/mbpp` under **CC-BY-4.0** (Creative Commons Attribution 4.0 International).
+
+Licence: https://creativecommons.org/licenses/by/4.0/
+
+CHANGES MADE TO THE ORIGINAL, as CC-BY-4.0 §3(a)(1)(B) requires be indicated:
+each reference solution was rewritten through `ast.unparse` (normalising formatting and comments away), compiled to a `.pyc` at `optimize=0`, and paired with a disassembly of the resulting code object. The task text and tests are unmodified. Every row carries its original `task_id`.

README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - text-generation
+language:
+  - en
+tags:
+  - decompilation
+  - python
+  - bytecode
+  - code
+  - mbpp
+size_categories:
+  - n<1K
+configs:
+  - config_name: default
+    data_files: bench.jsonl
+---
+
+# Data card — MBPP held-out decompilation benchmark
+
+383 MBPP reference solutions compiled to Python 3.12 bytecode and paired with their source, with
+the original `task_id` restored on every row. Built 2026-08-04 by `tools/build_mbpp_ood.py`.
+
+**Redistributable** under CC-BY-4.0, provided `NOTICES.md` ships alongside.
+
+---
+
+## The set
+
+| | |
+|---|---|
+| Rows | **383** (400 candidates − 17 contaminated) |
+| Source | `google-research-datasets/mbpp`, config `full` |
+| Licence | **CC-BY-4.0** |
+| `task_id` restored | **383 / 383** (all distinct, range 11–973) |
+| Untraceable rows dropped | 0 |
+| **Contaminated rows dropped** | **17** (see below) |
+| Disassembly length | mean 47.5 lines, median 41, max 187 |
+| Python | 3.12, `optimize=0` |
+
+### In what sense this set is independent of training — stated precisely, not as an adjective
+
+It is a **different corpus** (`google-research-datasets/mbpp`, not
+`codeparrot/github-code-clean`) and a **different kind of code**: short, self-contained,
+hand-written answers to stated problems, against the training trunk's real project code with its
+framework coupling and helper chains. Both differences are verifiable from row provenance.
+
+That matters because the pilot's failure mode was a model learning the *source of the data*
+rather than the task, and a test set drawn from the training source cannot detect it.
+
+It is **not** described as out-of-distribution anywhere, and no divergence statistic was computed,
+so no distributional-shift claim is made. The defensible claim is exactly three things:
+different source, different task style, and the verified non-overlap below.
+
+### Contamination — the defect that cost 17 rows
+
+**This set was originally decontaminated against the wrong corpus.** `build_ood_mbpp.py` checked
+against the v1-era 10k training labels, but the shipping model (v3) trained on 48,196 rows.
+Re-checked against the corpus v3 actually trained on:
+
+| gate | result |
+|---|---|
+| exact canonical match vs v3 corpus | 0 / 400 |
+| **identifier-blind fingerprint vs v3 corpus** | **17 / 400 (4.25%)** |
+
+Those 17 are dropped. They are structural collisions rather than copied code — the fingerprint
+erases literals, so `re.sub(' +', ' ', t)` and `re.sub('[- ()]', '', s)` collide despite computing
+different things. The gate is applied anyway: it is the same gate `build_final.py` and the CSN
+builder apply, and arguing with it case by case is precisely how the earlier provenance defects
+happened.
+
+After rebuild: **0 / 383** contamination against the v3 corpus, by either gate.
+
+## Task ids restored
+
+`build_ood_mbpp.py` wrote only `{input, expected}`, so no row could be traced to its task, prompt
+or tests. Recovery is exact rather than approximate: `expected == canonicalise(mbpp["code"])`, a
+deterministic transform, so rebuilding the map over all 974 MBPP rows (974 rows → 965 distinct
+canonical forms) recovers the id by lookup. All 400 rows matched; the builder refuses to emit a
+row it cannot trace.
+
+Each row now carries `provenance.task_id`, `mbpp_split`, the task `prompt`, and the `test_list`.
+The tests travel with the row, so a behavioural check is possible on this set without going back
+to the dataset.
+
+## Decontamination
+
+Two stages. At original build time, against the 10k training labels of that era, by exact
+canonical match and by identifier-blind fingerprint (which caught 15 items exact match missed).
+At rebuild, against the **48,196-row corpus the shipping model actually trained on**, removing a
+further 17 rows as above. Rows not adjudicable by the differential-execution oracle were excluded
+at original build time, so every row here was labelled by running it.
+
+## Changes made to the original, as CC-BY-4.0 §3(a)(1)(B) requires be indicated
+
+Each reference solution was rewritten through `ast.unparse` — normalising away formatting,
+comments and redundant parentheses — then compiled to a `.pyc` at `optimize=0` and paired with a
+disassembly of the resulting code object. Task text and tests are unmodified.
+
+## Harness soundness on this set
+
+`grade.py --self-test-only`: pre-flight **383/383 = 100%**, mutation kill rate **199/199 = 100%**,
+0 survivors. Note what pre-flight does and does not prove — see `../../ORACLE-LIMITS.md`.
+
+## Read this before quoting any "OOD" figure
+
+The published PyBytecode figures labelled *OOD-MBPP* — 91.04% strict greedy, 97.49% certified@32,
+100% docstring recovery — **were not measured on this set.** They were measured on
+the superseded held-out set (n=279), which despite its name contains no MBPP at all: it is
+GitHub source from the held-out shards of the training corpus. Matching all 974 canonicalised
+MBPP rows against it yields 0 hits, against 400/400 for this set. Evidence in
+`../../LICENSING-DETERMINATION.md` §4.
+
+Those numbers remain valid measurements of **held-out generalisation**. They are not
+out-of-distribution measurements, and the label should be corrected wherever it appears.
+
+**No scores have been measured on this benchmark.** Doing so requires a generation run (GPU).
+
+## Limitations
+
+- MBPP solutions are short and stylistically uniform. Success here says little about long or
+  framework-coupled functions; the CSN set is the harder distribution.
+- Rows are the first 400 adjudicable MBPP tasks in split order, minus the 17 contaminated ones. Not a random sample.
+- Two MBPP tasks with identical canonical solutions collapse to one row; 974 rows yield 965
+  distinct canonical forms, and the first `task_id` wins.
+
+## Attribution
+
+MBPP (Mostly Basic Python Problems), Austin et al., 2021, Google Research.
+<https://huggingface.co/datasets/google-research-datasets/mbpp> — CC-BY-4.0
+(<https://creativecommons.org/licenses/by/4.0/>).

build_stats.json

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+{
+  "in": 400,
+  "kept": 383,
+  "drop_untraceable": 0,
+  "drop_compile": 0,
+  "drop_contaminated_exact": 0,
+  "drop_contaminated_fingerprint": 17,
+  "task_ids_restored": 383,
+  "task_id_min": 11,
+  "task_id_max": 973,
+  "distinct_task_ids": 383
+}