| --- |
| license: cc-by-4.0 |
| size_categories: |
| - 10K<n<100K |
| tags: |
| - code |
| - source-code |
| - data-structures |
| - algorithms |
| - competitive-programming |
| - software-engineering |
| - computer-science |
| - code-generation |
| - code-completion |
| - code-understanding |
| - program-synthesis |
| - llm |
| - reasoning |
| - problem-solving |
| - coding-interviews |
| - leetcode |
| - sft |
| - rlhf |
| - self-supervised-learning |
| task_categories: |
| - text-generation |
| language: |
| - en |
| pretty_name: DSA coding Dataset |
| --- |
| |
| # Dataset Description |
|
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|
|
|
|
| This dataset is a large-scale collection of **Data Structures and Algorithms (DSA) code**, containing **12,384 code files** with **3.86 million lines of code** and **25.01 million lexical tokens**, designed to support the development of advanced code generation models, programming assistants, software engineering AI systems, and code intelligence applications. |
|
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| It consists of real-world DSA implementations covering a wide range of algorithms, data structures, problem-solving techniques, and programming paradigms. The dataset captures coding patterns, algorithmic reasoning, optimization strategies, computational logic, and software development practices commonly used in technical interviews, competitive programming, computer science education, and production software systems. |
|
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| This makes it highly valuable for building accurate, scalable, and production-ready AI systems for code generation, code completion, program synthesis, code understanding, bug detection, algorithmic reasoning, and software engineering research. Additionally, this dataset can be utilized in pipelines for **Supervised Fine-Tuning (SFT), Self-Supervised Learning (SSL), Reinforcement Learning with Human Feedback (RLHF), and code-focused AI workflows.** |
|
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| # Dataset Specification |
|
|
|
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| ``` |
| |
| Code Files: 12,384 |
| |
| Total Lines of Code: 3.86 Million |
| |
| Total Lexical Tokens: 25.01 Million |
| |
| Domain: Data Structures and Algorithms |
| |
| Data Type: Source Code |
| |
| Nature: Real-world and curated programming data |
| |
| ``` |
|
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| # Key Use Cases |
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| ``` |
| |
| Code generation and completion |
| |
| Algorithm understanding and reasoning |
| |
| Competitive programming model training |
| |
| Programming assistant development |
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| Code search and retrieval |
| |
| Program synthesis |
| |
| Software engineering AI systems |
| |
| Bug detection and code analysis |
| |
| Technical interview preparation systems |
| |
| Code model benchmarking and evaluation |
| |
| ``` |
|
|
| --- |
|
|
| # Value of This Dataset |
|
|
| ``` |
| |
| Enables development of advanced coding AI systems |
| |
| Supports large-scale code model training |
| |
| Improves algorithmic reasoning capabilities |
| |
| Facilitates code understanding and generation |
| |
| Helps build AI-powered programming assistants |
| |
| Strengthens software engineering and developer productivity tools |
| |
| ``` |
| **Basic JSON Schema** |
|
|
| ```json |
| { |
| "problem_sno": "int64", |
| "problem_slug": "string", |
| "title": "string", |
| "problem_statement": "string", |
| "sample_sno": "int64", |
| "input": "string", |
| "output": "string", |
| "solution_sno": "int64", |
| "solution_name": "string", |
| "language": "string", |
| "code": "string", |
| "source_json_file": "string" |
| } |
| ``` |
|
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| **Data Creation** |
|
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| -Procured through formal agreements and generated in the ordinary course of business. |
| |
| **Considerations** |
|
|
| This dataset is provided for research and educational purposes only. It contains only sample data. For access to the full dataset and enterprise licensing options, please visit our website [InfoBay.AI](https://infobay.ai/) or contact us directly. |
| |
| -Ph: (91) 8303174762 |
| -Email: datareq@infobay.ai |
