---
license: other
license_name: mixed-permissive-per-row
license_link: https://huggingface.co/datasets/BlazingCustoms/pybytecode-csn-3.12-licensed/blob/main/NOTICES.md
task_categories:
  - text-generation
language:
  - en
tags:
  - decompilation
  - python
  - bytecode
  - code
  - reverse-engineering
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files: bench.jsonl
---

# Data card — CSN-3.12-licensed decompilation benchmark

600 real Python functions from GitHub, compiled to Python 3.12 bytecode, each paired with the
source that produced it. Every row carries full provenance and a licence resolved at the exact
commit. Built 2026-08-04 by `tools/build_csn_licensed.py`.

**Redistributable**, provided `NOTICES.md` ships alongside. That file is not optional: MIT, BSD
and Apache-2.0 require the notice to travel with the copy.

---

## The set

| | |
|---|---|
| Rows | **600** |
| Source repositories | **117** |
| Max rows from any one repo | **6 (1.00%)** |
| Median rows per repo | 6 |
| Distinct commit SHAs | 117 |
| Rows with complete provenance | 600 / 600 |
| Rows with a resolved SPDX identifier | 600 / 600 |
| Disassembly length | mean 87.3 lines, median 59, max 1,622 |
| Rows with annotations | 63 |
| Python | 3.12, `optimize=0` |

Licences, all resolved at the row's own commit:

| SPDX | rows | share |
|---|---:|---:|
| MIT | 391 | 65.2% |
| BSD-3-Clause | 118 | 19.7% |
| Apache-2.0 | 64 | 10.7% |
| BSD-2-Clause | 15 | 2.5% |
| ISC | 12 | 2.0% |

### Why this replaces the previous 400-row set

The first CSN benchmark drew 400 rows from **24** repositories with **15% from one**
(`Karaage-Cluster/python-tldap`), recorded no commit SHA, and captured no licence. Auditing it
afterwards: **180 of its 400 rows (45%) cannot be redistributed** — 83 GPL-3.0 (including all 60
from that top repository) and 97 from repositories publishing no licence at all. Concentration at
that level also means per-repository idiosyncrasy was a large fraction of what the benchmark
measured. Details in `../../LICENSING-DETERMINATION.md` §2.

The cap was set at 6 rows per repo — about 1% of the set — chosen so that no single codebase can
move the headline number by more than a rounding error, while still admitting enough rows per
repo to be worth resolving a licence for. At n=600 the 95% confidence interval on an accuracy
near 93% is roughly ±2.0 points, against ±2.5 at n=400.

---

## Per-row fields

```jsonc
{
  "i": 0,
  "input":  "CODE <module>()\n  RESUME 0\n ...",   // model input: normalised disassembly
  "expected": "def f(x):\n    ...",                 // reference source
  "src_path": "src/00000.py",                       // RELATIVE to this directory
  "pyc_path": "pyc/00000.pyc",
  "provenance": {
    "repo": "owner/name",
    "repo_url": "https://github.com/owner/name",
    "file_path": "pkg/module.py",                   // path within the repo
    "commit_sha": "1b38e7cd...",                    // the commit the function was taken at
    "func_name": "Class.method",
    "line_start": 323, "line_end": 372,
    "permalink": "https://github.com/.../blob/<sha>/pkg/module.py#L323-L372",
    "dataset": "code-search-net/code_search_net (python, train split)"
  },
  "license": {
    "spdx": "BSD-3-Clause",
    "file": "LICENSE", "blob_sha": "3d9cc0c2...",
    "resolved_at_commit": "1b38e7cd...",
    "resolved_via": "GitHub GET /repos/{repo}/license?ref={sha}"
  },
  "n_instr": 49, "has_annotation": false
}
```

Paths are relative, so the set works from any checkout location. Nothing points at `/tmp`.

## How rows were selected

Source: `code-search-net/code_search_net`, python train split, read in file order from a local
parquet copy (`tools/fetch_csn.sh`; sha256
`ad9e3a4ab10c2c1d8926d2b26ca2bfcc3aadda1477ba29a933391f93806b9fed`).

3,138 rows were read to keep 600. In order:

| Gate | Effect |
|---|---|
| Repo cap (6) | 1,838 rows skipped — the mechanism that spreads the set across 117 repos |
| Repo blacklisted on licence | 668 rows skipped, from the 25 repos rejected below |
| **Licence not permissive / not resolvable** | **25 repos rejected** |
| Train-contamination (identifier-blind fingerprint) | 3 rows dropped |
| Unparseable | 4 rows dropped |

Repos rejected on licence: GPL-3.0 ×8, no licence file at that commit ×7, AGPL-3.0 ×3,
LGPL-3.0 ×2, GPL-2.0 ×2, `NOASSERTION` ×2, LGPL-2.1 ×1.

**A licence is resolved, never guessed.** `GET /repos/{owner}/{repo}/license?ref={sha}` must
return a concrete SPDX identifier on the allowlist (`tools/resolve_licenses.py:ALLOWED_SPDX`).
`NOASSERTION` and `Other` count as unresolved and the row is dropped. We never infer a licence
from a README, a `setup.py` classifier, or a package index.

## Normalisation

Each function is reduced to a normal form before compiling: every docstring is replaced by the
literal `'pass'`, then the tree is re-emitted with `ast.unparse`. Idempotence is checked per row
and a row that is not a fixed point is dropped.

This build uses `tools/normalize.py`, a stdlib-only implementation. **The GPL-3.0 tool that built
the previous benchmark is not in this pipeline.** The two agree byte-for-byte on 400/400 rows of
the previous benchmark (`tools/verify_equivalence.py`); the reasoning is in
`../../LICENSING-DETERMINATION.md` §1.

Because docstrings are normalised away, **this benchmark measures nothing about docstring
recovery** — `samples_with_real_docstring` is 0 by construction. Use the held-out set for that.

## Compilation

`py_compile` at `optimize=0` for the reference `.pyc`, and `compile(..., dont_inherit=True,
optimize=0)` for the model's input. `dont_inherit` is deliberate: the training corpus was
compiled with PEP-563 stringised annotations inherited, and real `.pyc` files are not. Handing
the model its training-time distribution would flatter it, so we do not. See
`../../DATA-CARD-training-corpus.md` §7.

## Harness soundness on this set

`grade.py --self-test-only`: pre-flight **600/600 = 100%**, mutation kill rate **116/116 = 100%**,
0 survivors. Both are prerequisites for quoting any score — but note that **pre-flight is trivial
by construction and proves nothing about soundness** (it compares `compile(x)` with `compile(x)`).
See `../../ORACLE-LIMITS.md` §1.

## Unit size — read this before comparing scores against another benchmark

An aggregate on this set is largely a statement about **small units**, so the size distribution is
part of the result rather than a footnote to it. Size is measured in **representation lines** —
the number of lines in the `input` field, i.e. the disassembly text a model is actually given.

| min | p25 | median | p75 | p90 | p99 | max |
|---|---|---|---|---|---|---|
| 19 | 39 | **59** | 101 | 167 | 478 | 1,622 |

Certification falls off sharply with size (v3 greedy, this set; intervals omitted below 30 rows /
10 repositories rather than printed at a misleading width):

| rep lines | rows | v3 greedy | 95% CI | v3 best-of-32 | 95% CI |
|---|---|---|---|---|---|
| 0–49 | 224 | 95.98% | [93.01, 98.51] | 98.21% | [96.31, 99.58] |
| 50–99 | 224 | 89.73% | [85.17, 93.93] | 98.21% | [96.26, 99.57] |
| 100–199 | 112 | 65.18% | [55.36, 74.14] | 85.71% | [77.57, 92.98] |
| 200–299 | 27 | 51.85% | — | 77.78% | — |
| 300–399 | 5 | 60.00% | — | 100.00% | — |
| 400–599 | 5 | 0.00% | — | 0.00% | — |
| 600+ | 3 | 0.00% | — | 0.00% | — |

**96.64%** of v3's greedy certifications on this set (95.37% at best-of-32) come from units under
200 rep lines, and above ~400 rep lines nothing certified even at 32 samples. The
300–399 bucket reading above the one below it is n=5 noise, not a recovery. Recompute all of it
with `harness/size_curve.py`; the stored output is `../../results/size_curve_csn600.json`.

## Limitations

- **Measured scores (2026-08-04, L1 strict oracle):** PyBytecode v3 greedy
  **506/600 = 84.33%**, repo-clustered 95% CI [80.48, 87.94]; verified best-of-32
  **562/600 = 93.67%**, CI [90.86, 96.08]. Untuned `Qwen2.5-Coder-1.5B-Instruct` control:
  **4/600 = 0.67%**, CI [0.16, 1.35]. Per-row verdicts: `../../results/rows_with_base.jsonl`.
- GitHub's licence detection is repository-level. A repository can vendor third-party files under
  other terms; we do not detect that, and no automated tool reliably does.
- A licence resolved at a commit is the licence *of that repository snapshot*. It does not prove
  the specific file was contributed under it.
- CodeSearchNet is a 2019-era snapshot, so the code skews toward pre-3.7 idiom. It contains no
  `match` statements, no walrus operators, and few modern typing constructs.
- Rows are capped, not sampled uniformly at random: the set is the first 6 admissible functions
  per repository in dataset order. That is reproducible and unbiased with respect to difficulty,
  but it is not a random sample of Python.
- 117 repositories is enough to defeat single-repo dominance; it is not a representative sample
  of the language ecosystem.

## Provenance and licence of this benchmark

Derived from CodeSearchNet (`code-search-net/code_search_net`). The underlying functions remain
under their original licences and copyright, listed per row and reproduced in full in
`NOTICES.md` (117 repositories, 272 KB of licence text). The assembly, normalisation and
disassembly are ours.