| --- |
| license: mit |
| task_categories: |
| - text-generation |
| language: |
| - zh |
| - en |
| tags: |
| - ARP |
| - RL |
| - verl |
| - LLM |
| pretty_name: DeCoMo |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| --- |
|
|
| ## 📁 Dataset Variants |
| ### 1. `preprocess-CodeContests-perturbation-none` |
|
|
| * No perturbation applied |
| * Pure clean programs |
| * Used as baseline reference |
|
|
| ### 2. `preprocess-CodeContests-perturbation-syntax` |
| * Only syntax-level perturbations |
| * Bug types: token deletion, indentation errors, malformed expressions |
| * Focus: **syntax recovery ability** |
|
|
| ### 3. `preprocess-CodeContests-perturbation-structure` |
|
|
| * Only structure-level perturbations |
| * Bug types: line swap, line deletion, statement reordering |
| * Focus: **program structure repair** |
|
|
| ### 4. `preprocess-CodeContests-perturbation-semantic` |
|
|
| * Only semantic-level perturbations |
| * Bug types: logic errors, wrong operators, boundary mistakes |
| * Focus: **semantic reasoning repair** |
|
|
| ### 5. `preprocess-CodeContests-perturbation-mix` |
|
|
| * Mixed perturbation dataset |
| * Combines syntax + structure + semantic corruption |
| * Used for general robustness training |
|
|
| ### 6. `preprocess-CodeContests-perturbation-mixed-task-*` |
| |
| These are **controlled mixture ratio subsets** used for ablation and scaling. |
| |
| Format: |
| |
| ``` |
| 00100 → 0 : 10 : 0 : 0 |
| 01000 → 0 : 0 : 10 : 0 |
| 10000 → 10 : 0 : 0 : 0 |
| 2242 → 2 : 2 : 4 : 2 |
| ``` |
| |
| Where the order is: |
| |
| ``` |
| [syntax : structure : semantic : mixed] |
| ``` |
| |
| Examples: |
| |
| * `00100` → only structure perturbation (100%) |
| * `01000` → only semantic perturbation (100%) |
| * `10000` → only syntax perturbation (100%) |
| * `2242` → balanced mixture (2:2:4:2) |
|
|
| --- |
|
|
| ## 📦 Data Format |
|
|
| Each sample contains: |
|
|
| ```json id="m4kqv2" |
| { |
| "id": "problem_id", |
| "clean_code": "correct reference solution", |
| "buggy_code": "perturbed program", |
| "perturbation_type": "syntax | structure | semantic | mixed", |
| "language": "python", |
| "task_prompt": "problem statement (optional)", |
| "test_cases": { |
| "input": "...", |
| "output": "..." |
| } |
| } |
| ``` |
|
|
| ## 🎯 Purpose |
| These variants are designed for: |
| * perturbation-driven program repair |
| * RL-based trajectory learning |
| * ablation over bug types |
| * robustness evaluation under different corruption distributions |
