Upload structurally-vacuous-filtered methods2test_small (train split cleaned, val/test unchanged)

README.md

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+---
+language:
+- en
+license: mit
+task_categories:
+- text-generation
+tags:
+- code
+- java
+- unit-testing
+- methods2test
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
+  - split: test
+    path: data/test-*
+---
+
+# methods2test_small_cleaned
+
+A **structurally-vacuous-filtered** copy of the `train` split of
+[`andstor/methods2test_small`](https://huggingface.co/datasets/andstor/methods2test_small)
+(context config `fm+fc+c+m+f+t+tc`, the one actually used to fine-tune models in
+[andstor/peft-unit-test-generation-replication-package](https://github.com/andstor/peft-unit-test-generation-replication-package)).
+Produced for the investigation in
+[lhnam/PEFT — FINDINGS.md](https://github.com) (`FINDINGS.md` §1.2, §4 item 2),
+which found that **17.8% of the real fine-tuning targets are structurally
+vacuous** (no assertion, empty, or tautological) and hypothesized this is a
+driver of the "convergence attractor" collapse seen when fine-tuning code LLMs
+for JUnit test generation.
+
+## What changed vs. the original
+
+| Split | Original rows | This dataset | Vacuous rate |
+|---|---|---|---|
+| `train` | 7,440 | **6,124** (vacuous rows dropped) | 17.7% removed |
+| `validation` | 953 | 953 (**unchanged**) | 15.2% (left in, for fair eval_loss) |
+| `test` | 1,017 | 1,017 (**unchanged**) | 16.9% (left in) |
+
+Only `train` is filtered. `validation` and `test` are byte-identical to the
+source dataset's `fm+fc+c+m+f+t+tc` config — the point of this dataset is to
+isolate the effect of *training on* cleaner targets while still measuring
+`eval_loss` / benchmark success against the real, unfiltered data distribution.
+Filtering only the split a model actually learns from, and leaving evaluation
+untouched, is what makes a before/after comparison causally meaningful.
+
+## Filtering method
+
+Each `target` (the reference JUnit test) is classified as vacuous if it does
+**not** contain a real, non-tautological `assert*`/`fail`/`verify` call:
+
+```python
+ASSERT_RE = re.compile(r"\b(assert\w*|fail|verify\w*)\s*\(", re.IGNORECASE)
+TAUTOLOGY_RE = re.compile(
+    r"assert(true)\s*\(\s*true\s*[,)]|assert(false)\s*\(\s*false\s*[,)]|"
+    r'assertequals\s*\(\s*([A-Za-z0-9_."\']+)\s*,\s*\3\s*[,)]',
+    re.IGNORECASE,
+)
+```
+
+Targets under 15 characters are also treated as vacuous ("empty"). This is the
+exact classifier used throughout the source investigation (see
+`scripts/filter_vacuous_training_data.py` in the repo above), applied here with
+`--mode drop`.
+
+Breakdown of the original `train` split before filtering:
+
+| Label | Count | % |
+|---|---|---|
+| `has_real_assert` (kept) | 6,124 | 82.3% |
+| `no_assert` | 1,278 | 17.2% |
+| `tautological_assert` | 25 | 0.3% |
+| `empty` | 13 | 0.2% |
+| **vacuous total (dropped)** | **1,316** | **17.7%** |
+
+(Matches `FINDINGS.md`'s independently-reported 17.8% to within rounding —
+recomputed directly from this dataset's own source parquet.)
+
+## Columns
+
+- `id` (string) — original row id from `andstor/methods2test_small`.
+- `source` (string) — the prompt/context (unchanged).
+- `target` (string) — the reference JUnit test (the fine-tuning label).
+
+No `weight` column — this is the `drop` variant, not `downweight`. See the
+source script if you want a down-weighted variant instead.
+
+## Intended use
+
+Point a fine-tuning run's `TRAIN_DATASET` at this repo (config `default`) in
+place of `andstor/methods2test_small` (`fm+fc+c+m+f+t+tc`), keeping everything
+else — model, LoRA config, epochs, learning rate, validation split — identical,
+to test whether removing the training-time shortcut narrows or removes the
+post-fine-tuning "convergence attractor" documented in the source repo's
+`FINDINGS.md`. This is one experiment in an ongoing, self-correcting
+investigation — see that document for the full methodology, caveats, and
+history of revisions before citing any number from this dataset card in a
+paper.
+
+## Provenance
+
+- Source dataset: [`andstor/methods2test_small`](https://huggingface.co/datasets/andstor/methods2test_small), config `fm+fc+c+m+f+t+tc`, revision confirmed via that dataset's own commit history.
+- Source paper / replication package: [andstor/peft-unit-test-generation-replication-package](https://github.com/andstor/peft-unit-test-generation-replication-package).
+- License inherited as MIT from the source dataset.

data/test-00000-of-00001.parquet

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data/validation-00000-of-00001.parquet

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filter_stats.json

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+{
+  "validation": {
+    "n": 953,
+    "counts": {
+      "has_real_assert": 808,
+      "no_assert": 140,
+      "empty": 1,
+      "tautological_assert": 4
+    },
+    "vacuous_pct": 15.2
+  },
+  "test": {
+    "n": 1017,
+    "counts": {
+      "has_real_assert": 845,
+      "no_assert": 168,
+      "tautological_assert": 3,
+      "empty": 1
+    },
+    "vacuous_pct": 16.9
+  },
+  "train_original": {
+    "n": 7440,
+    "counts": {
+      "has_real_assert": 6124,
+      "no_assert": 1278,
+      "tautological_assert": 25,
+      "empty": 13
+    },
+    "vacuous_pct": 17.7
+  },
+  "train_cleaned": {
+    "n": 6124
+  }
+}