| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - text-generation |
| language: |
| - en |
| tags: |
| - code-generation |
| - benchmark |
| - classeval |
| pretty_name: ClassEval (modernised) |
| size_categories: |
| - n<1K |
| --- |
| |
| # ClassEval (modernised) |
|
|
| A lightly patched fork of [FudanSELab/ClassEval](https://huggingface.co/datasets/FudanSELab/ClassEval), |
| the 100-task class-level Python code generation benchmark, fixed so that it |
| still runs correctly on a current Python and a current NumPy. |
|
|
| **The benchmark itself is unchanged.** Every patch either repairs a test that no |
| implementation could pass, or repairs the reference solution. No task was made |
| easier, no prompt (`skeleton`) was touched, and nothing about what a model is |
| asked to write has changed. |
|
|
| | | upstream | this fork | |
| |---|---:|---:| |
| | classes whose reference solution passes all its tests | 96 / 100 | **100 / 100** | |
| | test methods passed by the reference solutions | 2182 / 2196 | **2196 / 2196** | |
|
|
| Measured on CPython 3.13 and 3.14, NumPy 2.x, in a network-isolated sandbox. |
|
|
| ## What was changed |
|
|
| Six edits across five tasks. Schema, task ids and field names are identical to |
| upstream. |
|
|
| ### Tests that no implementation could pass |
|
|
| - **ClassEval_17** (`CalendarUtil`) — a time bomb. `get_upcoming_events()` |
| filters on `event['start_time'] >= datetime.now()`, but the test hard-codes a |
| 2024-01-02 event as the "upcoming" one, so the task became unpassable once the |
| wall clock passed that date. The event now sits at `datetime.now().year + 1`; |
| the companion 2023 event, which must stay in the past, is untouched. |
| - **ClassEval_31** (`DataStatistics4`) — `assertEqual` on a Pearson correlation |
| coefficient. NumPy 2.x returns `0.9819805060619655` against a recorded |
| `0.9819805060619659`: a 4-ULP difference, the same number to 15 significant |
| figures. Now `assertAlmostEqual`. |
| - **ClassEval_48** (`IpUtil`) — asserted that a reverse DNS lookup of `0.0.0.0` |
| returns `'LAPTOP-2CS86KUM'`, the dataset author's own machine name. This could |
| never pass on any other computer. The assertion now expects `None`, which is |
| what the lookup yields when it fails. This is the one patch that genuinely |
| weakens a test: no portable replacement asserting a *successful* reverse |
| lookup exists. |
| |
| ### Reference solutions only (models are unaffected) |
| |
| - **ClassEval_51** (`KappaCalculator`) — two independent NumPy 2.0 breakages: |
| `np.mat` was removed (now `np.asmatrix`, at both call sites), and |
| `float()` on a 1×1 matrix is no longer allowed (now indexes `[0, 0]` |
| explicitly). The second only surfaces once the first is fixed. |
| - **ClassEval_58** (`MinesweeperGame`) — the reference `generate_mine_sweeper_map` |
| drew mine coordinates without checking for collisions, so two mines could land |
| on the same cell and the board would contain fewer than `k` mines. It failed |
| its own test about 30% of the time (measured: 21/30 passes across 30 runs). |
| Now retries on collision, with a guard against looping on a full board. |
|
|
| ## Known remaining quirks |
|
|
| Not patched, because fixing them would change what the model is shown or is |
| metadata rather than content: |
|
|
| - **ClassEval_69**'s `methods_info` maps `merge_pdfs` to `TestPDFHandler`, a |
| fixture-only class with zero test methods. This caps upstream's method-level |
| metric at 409/410 for any submission, including ground truth. |
| - **ClassEval_22 / _43 / _46** have malformed skeletons. That is prompt text — |
| patching it would change the task. |
| - **ClassEval_44** selects its parser by string (`BeautifulSoup(html, 'lxml')`), |
| so `lxml` is a hard dependency that appears in no import statement and is |
| absent from upstream's `requirements.txt`. Install it or that task drops from |
| 23/23 to 7/23. |
| - **ClassEval_69**'s test imports `PdfFileReader` from `PyPDF2`, a name the |
| successor package `pypdf` removed. `PyPDF2` cannot be substituted. |
|
|
| ## Running it |
|
|
| Reproduced by `llama-eval` in llama.cpp, which executes generated classes in a |
| sandboxed venv (no Docker) and reports class-level and method-level scores: |
|
|
| ```bash |
| python3 llama-eval.py --server http://localhost:8033 --model my-model \ |
| --dataset classeval --n_predict 4096 --temperature 0 |
| ``` |
|
|
| Notes for anyone building their own runner: |
|
|
| - **Do not execute as uid 0.** ClassEval_50 asserts that writing to a `chmod |
| 0444` file fails; root bypasses permission bits, so it silently scores 14/16. |
| - Give each task its own working directory — 15 tasks write files, all |
| cwd-relative, and the names collide. |
| - Seed the global RNG before each test if you want reproducible verdicts. |
| - `gensim` publishes no wheel past cp313. Only two pure-Python APIs are used |
| (`utils.decode_htmlentities`, `matutils.unitvec`), so a small shim covers 3.14. |
| - NLTK needs exactly `punkt_tab`, `averaged_perceptron_tagger_eng` and |
| `wordnet` (~33 MB). These are the modern names; the dataset asks for the |
| renamed `punkt` / `averaged_perceptron_tagger`. |
|
|
| ## Licence and attribution |
|
|
| Original work: [FudanSELab/ClassEval](https://github.com/FudanSELab/ClassEval), |
| from *"ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on |
| Class-level Code Generation"* ([arXiv:2308.01861](https://arxiv.org/abs/2308.01861)). |
| Upstream distributes the code under MIT and **the data under |
| [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/)**; this modified |
| dataset is redistributed under the same CC BY-NC 4.0 terms. |
|
|
| This is a **modified** version. For the unmodified benchmark, use |
| [FudanSELab/ClassEval](https://huggingface.co/datasets/FudanSELab/ClassEval). |
|
|
