Publish DR evaluation dataset and documentation

README.md

@@ -1,3 +1,180 @@
 ---
 license: mit
+task_categories:
+- text-classification
+tags:
+- code
+- cybersecurity
+- vulnerability-detection
+- robustness
+- c
+- java
+pretty_name: DR Evaluation Noise Pools
+size_categories:
+- 10K<n<100K
 ---
+
+# DR Evaluation Noise Pools
+
+This dataset contains the retained behavior-preserving code variants and
+realized-distance metadata used to evaluate the robustness of LLM-based
+vulnerability analyzers. The corresponding evaluation and Acc-based DR/SIR
+implementation is available in the
+[TOSEM artifact repository](https://github.com/Jackline97/TOSEM-artifact).
+
+## Files
+
+| File | Description |
+|---|---|
+| `noise_pools_all.zip` | Combined Juliet, PrimeVul, and MegaVul perturbation pools |
+
+Archive properties:
+
+- compressed size: 494,118,658 bytes (471.23 MiB);
+- uncompressed size: 7,188,405,146 bytes (approximately 6.69 GiB);
+- JSON pool files: 22,293;
+- SHA-256: `2EFC57199F3E497D48772FB322D97EA7F1393BC8C1D24EB00D2E1D224F6ED824`.
+
+## Evaluation Scope
+
+The reported evaluation uses five dataset-language subsets:
+
+| Dataset | Language | Paired base files |
+|---|---:|---:|
+| Juliet | Java | 244 |
+| Juliet | C | 363 |
+| PrimeVul | C | 196 |
+| MegaVul | Java | 335 |
+| MegaVul | C | 335 |
+
+Only these dataset-language combinations are part of the reported benchmark.
+The archive is preserved byte-for-byte for reproducibility; consumers should
+use the combinations above when reproducing the evaluation.
+
+## Perturbation Families
+
+| Directory | Family | Target levels |
+|---|---|---|
+| `comment_noise` | Contradiction Comments (CC) | 0.2, 0.4, 0.6, 0.8 |
+| `prompt_inject_noise` | Prompt-Injection Comments (PI) | 0.2, 0.4, 0.6, 0.8 |
+| `variable_noise` | Variable Replacement (VR) | 0.2, 0.4, 0.6, 0.8 |
+| `structure_noise_checked` | Structure Perturbation (SP) | 0.03, 0.10, 0.17, 0.24 |
+
+After extraction, the top-level layout is:
+
+```text
+noise_pools_juliet/
+noise_pools_megavul/
+noise_pools_primevul/
+```
+
+Within each root, records are organized as:
+
+```text
+<edit_family>/<language>/noise_<target_level>/<base_record>.json
+```
+
+## JSON Record Structure
+
+Each JSON pool record contains:
+
+- `cleaned_code`: normalized base source code;
+- `formatted_code`: formatted source representation;
+- `cwe_id`: associated CWE identifier;
+- one function-specific key containing retained `Combo_*` variants.
+
+Each retained variant contains the edited code in `code_comment_variant`, safe
+and vulnerable harnesses in `harness_command_good` and
+`harness_command_bad`, and a `meta_info` object. In `meta_info`, `score` is the
+realized normalized perturbation distance consumed by the DR estimator.
+Comment-based families also retain `code_comment_org` where applicable.
+
+## Download and Extract
+
+Download with `huggingface_hub`:
+
+```python
+from huggingface_hub import hf_hub_download
+
+archive = hf_hub_download(
+    repo_id="LLMs4CodeSecurity/DR_Evaluation",
+    filename="noise_pools_all.zip",
+    repo_type="dataset",
+)
+print(archive)
+```
+
+Extract with Python:
+
+```python
+from pathlib import Path
+from zipfile import ZipFile
+
+archive = Path("noise_pools_all.zip")
+with ZipFile(archive) as bundle:
+    bundle.extractall(archive.parent)
+```
+
+PowerShell:
+
+```powershell
+Expand-Archive -Path .\noise_pools_all.zip -DestinationPath . -Force
+```
+
+Bash:
+
+```bash
+unzip noise_pools_all.zip
+```
+
+## Evaluation Code
+
+Clone the companion code repository:
+
+```bash
+git clone https://github.com/Jackline97/TOSEM-artifact.git
+cd TOSEM-artifact
+python -m pip install -r requirements.txt
+```
+
+For example, after placing and extracting the archive in the repository root:
+
+```bash
+python evaluation_batch.py \
+  --dataset juliet \
+  --language java \
+  --noise-base noise_pools_juliet \
+  --noise-type comment_noise \
+  --models deepseek-chat \
+  --noise-scales 0.2,0.4,0.6,0.8 \
+  --max-combo 20 \
+  --num-runs 1 \
+  --out-base eval_res
+```
+
+See the [artifact README](https://github.com/Jackline97/TOSEM-artifact#readme)
+for model configuration, Ollama usage, output semantics, and DR/SIR commands.
+
+## Intended Use and Limitations
+
+The package is intended for research on vulnerability analysis, robustness,
+and behavior-preserving code transformations. It contains vulnerable code and
+should not be deployed as production software. The package provides retained
+inputs and transformation metadata; model inference outputs are generated by
+the companion evaluation code.
+
+The source samples originate from Juliet, PrimeVul, and MegaVul. Users remain
+responsible for following the applicable terms of the upstream datasets and
+projects represented in those corpora.
+
+## Citation
+
+```bibtex
+@misc{dr_evaluation_artifact_2026,
+  author       = {{LLMs4CodeSecurity}},
+  title        = {DR Evaluation Noise Pools},
+  year         = {2026},
+  howpublished = {\url{https://huggingface.co/datasets/LLMs4CodeSecurity/DR_Evaluation}},
+  note         = {Evaluation code: \url{https://github.com/Jackline97/TOSEM-artifact}}
+}
+```

noise_pools_all.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2efc57199f3e497d48772fb322d97ea7f1393bc8c1d24eb00d2e1d224f6ed824
+size 494118658