| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - text-classification |
| language: |
| - en |
| tags: |
| - code |
| - synthetic |
| - code-review |
| - static-analysis |
| pretty_name: Free Synthetic Code Diffs (100M) |
| size_categories: |
| - 10M<n<100M |
| --- |
| |
| # Free Synthetic Code Diffs (100M) |
|
|
| A 100-million-row synthetic dataset of code diffs labeled for destructive-change detection — the kind of change that silently drops data, tables, or columns in a migration or deploy. Every diff in this dataset is fabricated; none of it comes from real repositories, so there's no copyright or licensing entanglement. |
|
|
| Detecting a truly destructive change is harder than it looks. A plain regex for `DROP TABLE` or `DELETE FROM` catches the obvious cases and misses (or wrongly flags) a long tail of edge cases: destructive intent expressed through an ORM instead of raw SQL, casing or whitespace tricks that dodge a literal pattern match, a dangerous string sitting harmlessly inside a comment or log line, or a `DROP` that's actually just test-suite cleanup. This dataset is built specifically to stress-test detectors against that edge-case distribution, not just reward pattern recall. |
|
|
| ## Schema |
|
|
| | Column | Type | Description | |
| |---|---|---| |
| | diff_id | string | Unique identifier for the diff | |
| | change_category | string | One of 7 categories (see below) | |
| | language | string | Source language of the changed file | |
| | file_path | string | Fabricated file path for the change | |
| | commit_message | string | Synthetic commit message | |
| | diff_text | string | The unified diff text | |
| | sql_pattern | string | SQL pattern present in the diff, if any | |
| | is_destructive_ground_truth | bool | Ground-truth label — whether the change is actually destructive | |
| |
| ### Change categories |
| |
| - `raw_sql_destructive` (15%) — literal destructive SQL (DROP/DELETE/TRUNCATE) |
| - `raw_sql_safe` (15%) — literal SQL that looks risky but isn't destructive |
| - `orm_schema_change` (15%) — destructive change made through an ORM migration, no raw SQL to match on |
| - `obfuscated_destructive` (10%) — destructive SQL disguised via casing/whitespace/newline variation |
| - `mentioned_in_comment` (10%) — destructive-looking SQL sitting in a comment, docstring, or log string — not executed |
| - `test_suite_cleanup` (10%) — a DROP/DELETE inside test setup/teardown — not a production risk |
| - `general_code_change` (25%) — unrelated code changes, for class balance |
|
|
| `is_destructive_ground_truth` is set independently of whether a literal SQL keyword is present, so the dataset actually tests classification quality rather than keyword matching. |
|
|
| ## Format |
|
|
| Single Parquet file, Snappy compression, ~2.9 GB, 100,000,000 rows. |
|
|
| ## Quick start |
|
|
| ```python |
| import pandas as pd |
| df = pd.read_parquet("synthetic_code_diffs_100M.parquet") |
| ``` |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("ziadatalabs/FreeSyntheticCodeDiffs100M") |
| ``` |
|
|
| ```python |
| import duckdb |
| con = duckdb.connect() |
| con.sql("SELECT * FROM 'synthetic_code_diffs_100M.parquet' LIMIT 10").show() |
| ``` |
|
|
| ## Notes |
|
|
| - All diffs, file paths, and commit messages are fabricated — no real repository content. |
| - Categories are stratified as listed above; use `change_category` to filter or rebalance for your task. |
| - `is_destructive_ground_truth` is the label to train/evaluate against — don't infer it purely from `sql_pattern`. |
|
|
| ## License & Usage |
|
|
| Released under CC BY-NC 4.0 — free for personal, research, and educational use, with attribution. Not licensed for commercial use. |
|
|
| No real people, repositories, or organizations are represented in this data. It is entirely synthetic. |
|
|
| --- |
|
|
| Created by Zia Data Labs. Questions or feedback: zia.data.team@protonmail.com |
|
|
