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| license: openmdw-1.1 |
| language: |
| - en |
| pretty_name: S |
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| |
| # Code Syntax Dataset (S) |
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| A large-scale, high‑quality dataset for teaching large language models to identify and correct common syntax errors across **30+ programming languages**. |
| Contains **500,000+ unique examples** (≈110 MB) with English explanations – no artificial padding. |
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| ## 📊 Dataset Format |
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| The dataset is provided as a **single CSV file** with the following columns: |
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| | Column | Type | Description | |
| |--------|------|-------------| |
| | `wrong_code` | string | Code snippet containing a syntax error | |
| | `correct_code` | string | The corrected version of the same snippet | |
| | `explanation` | string | Concise, plain‑English explanation of the mistake and fix | |
| | `language` | string | Programming language (e.g., `Python`, `JavaScript`, `Rust`) | |
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| ## 🧠 Languages Covered |
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| The dataset includes examples from **30+ languages** and technologies: |
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| | Category | Languages | |
| |----------|-----------| |
| | **General‑purpose** | Python, JavaScript, TypeScript, Java, C#, C++, Rust, Go, Ruby, PHP, Perl, Swift, Kotlin, R, MATLAB | |
| | **Web** | HTML, CSS | |
| | **Database** | SQL (MySQL/PostgreSQL‑style) | |
| | **Shell / Scripting** | Bash, PowerShell | |
| | **Markup / Config** | YAML, JSON, XML, Markdown | |
| | **Backend / Node.js** | Express, fs, JWT, bcrypt, Mongoose | |
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| ## 💡 Example Entries |
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| Here are a few sample rows to illustrate the dataset content: |
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| | wrong_code | correct_code | explanation | language | |
| |------------|--------------|-------------|----------| |
| | `if x > 5\n print('hello')` | `if x > 5:\n print('hello')` | Colon missing after if. | Python | |
| | `console.log('world'` | `console.log('world')` | Close parenthesis. | JavaScript | |
| | `let mut x=5; let r1=&mut x; let r2=&mut x;` | `let mut x=5; { let r1=&mut x; } let r2=&mut x;` | Only one mutable borrow allowed. | Rust | |
| | `SELECT name age FROM users;` | `SELECT name, age FROM users;` | Missing comma between columns. | SQL | |
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| Each example is **unique** – variable names, numbers, and string values are randomised, ensuring a wide variety of patterns for robust model training. |
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| ## 🎯 Use Cases |
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| - **Fine‑tuning LLMs** – train models to correct erroneous code or to generate correct code from buggy input. |
| - **Building code‑review assistants** – create tools that automatically detect and suggest fixes for common syntax mistakes. |
| - **Educational materials** – use the dataset as a large, searchable bank of common programming pitfalls. |
| - **Benchmarking** – evaluate how well models understand language‑specific syntax rules. |
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| ## 📈 Dataset Statistics |
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| | Metric | Value | |
| |--------|-------| |
| | Total rows | ~500,000 – 550,000 | |
| | File size | ≈110 MB (uncompressed CSV) | |
| | Languages | 30+ | |
| | Unique templates | 130+ error patterns, each parameterised with random values | |
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| ## 📄 License |
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| This dataset is released under the **Open Metadata License (OpenMDW v1.1)** – you are free to use, modify, and distribute it for any purpose, subject to the terms of that license. |
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| ## 🙋 Contributions & Feedback |
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| If you have suggestions for additional languages, error patterns, or improvements, feel free to reach out or open an issue. We welcome contributions to make this dataset even more comprehensive. |
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| **Happy training!** 🚀 |
