| | --- |
| | license: mit |
| | task_categories: |
| | - text-generation |
| | language: |
| | - en |
| | tags: |
| | - code |
| | - Cpp |
| | size_categories: |
| | - 1M<n<10M |
| | --- |
| | |
| |
|
| | **Cpp-Code-Large** |
| |
|
| | Cpp-Code-Large is a large-scale corpus of C++ source code comprising more than **5 million** lines of C++ code. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, software engineering automation, and static program analysis for the C++ ecosystem. |
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| | By providing a high-volume, language-specific corpus, Cpp-Code-Large enables systematic experimentation in C++-focused model training, domain adaptation, and downstream code understanding tasks. |
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| | Cpp-Code-Large addresses the need for a dedicated C++-only dataset at substantial scale, enabling focused research across systems programming, performance-critical applications, embedded systems, game engines, and large-scale native software projects. |
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|
| | **1. Dataset Composition** |
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| | Programming Language: C++ |
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| | Total Size: 5M+ lines of C++ code |
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| | File Format: .jsonl |
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| | Primary Content: C++ source and header files (.cpp, .cc, .cxx, .hpp, .h) |
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| | Content Types |
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| | The dataset includes a wide variety of C++ constructs and paradigms, such as: |
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| | - Core Language Features |
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| | - Functions and function overloading |
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| | - Templates (function and class templates) |
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| | - Lambda expressions |
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| | - Namespaces |
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| | - Macros and preprocessor directives |
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| | - Inline functions |
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| | - Header/source separation patterns |
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| | Object-Oriented Programming |
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| | - Classes and structs |
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| | - Inheritance (single and multiple) |
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| | - Polymorphism and virtual functions |
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| | - Abstract base classes |
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| | - Encapsulation patterns |
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| | - Operator overloading |
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| | Modern C++ (C++11/14/17/20) Features |
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| | - Smart pointers (unique_ptr, shared_ptr, weak_ptr) |
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| | - Move semantics and rvalue references |
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| | - Auto keyword and type inference |
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| | - constexpr and consteval usage |
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| | - Structured bindings |
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| | Memory and Resource Management |
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| | - RAII patterns |
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| | - Manual memory management (new / delete) |
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| | - Custom allocators |
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| | - Smart pointer ownership patterns |
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| | - Exception-safe resource handling |
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| | - |
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| | Standard Template Library (STL) |
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| | - Containers (vector, map, unordered_map, set, etc.) |
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| | - Iterators and algorithms |
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| | - Functional utilities |
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| | - Threading primitives (std::thread, mutex, condition_variable) |
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| | - Filesystem library |
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| | - Chrono utilities |
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| | Concurrency and Parallelism |
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| | - Multithreading patterns |
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| | - Synchronization primitives |
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| | - Lock-free patterns (where applicable) |
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| | - Async programming |
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| | - Thread pools |
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| | Systems and Low-Level Programming |
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| | - File I/O |
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| | - Socket programming |
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| | - OS-level interactions |
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| | - Embedded-style programming patterns |
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| | - Performance optimization techniques |
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| | Build and Project Structures |
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| | - CMake-based project structures |
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| | - Modular header organization |
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| | - Static and dynamic library patterns |
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| | - Cross-platform compatibility patterns |
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| | **2. Intended Research Applications** |
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| | 2.1 Pretraining |
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| | - Training C++ code foundation models from scratch |
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| | - Continued pretraining of existing LLMs |
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| | - C++-specialized language modeling |
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| | - Tokenizer training for C++ ecosystems |
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| | - Domain adaptation for systems-level models |
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| | 2.2 Fine-Tuning and Adaptation |
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| | - Code completion systems |
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| | - Intelligent IDE assistants |
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| | - Automated refactoring tools |
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| | - Conversational programming agents |
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| | - C++-specific copilots |
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| | - Static analyzer enhancement models |
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| | - Performance optimization assistants |
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| | 2.3 Code Intelligence Tasks |
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| | - Code summarization |
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| | - Code-to-text generation |
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| | - Documentation generation |
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| | - Bug detection |
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| | - Security vulnerability detection |
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| | - Clone detection |
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| | - Code similarity modeling |
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| | - Dead code detection |
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| | - Complexity estimation |
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| | - Static and structural analysis |
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| | - Legacy-to-modern C++ migration modeling (e.g., raw pointers → smart pointers) |
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| | 2.4 Software Engineering Research |
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| | - Empirical studies of C++ coding patterns |
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| | - Analysis of architectural styles in native applications |
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| | - STL and template usage studies |
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| | - Memory management strategy analysis |
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| | - Concurrency pattern modeling |
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| | - AST-based experimentation |
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| | - Cross-version C++ evolution analysis |
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| | - Security practice analysis in performance-critical systems |
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| | **3. Ecosystem Coverage** |
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| | C++-Code-Large spans a broad range of C++ application domains, including: |
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| | - Systems software |
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| | - Embedded systems |
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| | - Scientific and numerical computing |
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| | - Desktop applications |
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| | - Cross-platform libraries |
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| | - Networking applications |
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| | - CLI tools |
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| | - Microservices written in C++ |
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| | The dataset captures both legacy C++ (pre-C++11 style) and modern C++ (C++11/14/17/20) development patterns, enabling cross-era research and modernization studies. |
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| | Thanks to open source community for all the guidance & support!! |
