File size: 3,034 Bytes
a21df21 d78dea8 e3844e4 019c80f e3844e4 4115abc e3844e4 c4d5de4 e3844e4 c4d5de4 e3844e4 c4d5de4 e3844e4 99f1ffe b9327c4 99f1ffe d78dea8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 |
---
license: mit
task_categories:
- text-generation
language:
- en
tags:
- code
- javascript
size_categories:
- 1M<n<10M
---
**JavaScript-Code-Large**
JavaScript-Code-Large is a large-scale corpus of JavaScript source code comprising around **5 million** JavaScript files. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, software engineering automation, and program analysis for the JavaScript ecosystem.
By providing a high-volume, language-specific corpus, JavaScript-Code-Large enables systematic experimentation in JavaScript-focused model training, domain adaptation, and downstream code understanding tasks.
JavaScript-Code-Large addresses the need for a dedicated JavaScript-only dataset at substantial scale, enabling focused research across frontend, backend, and full-stack JavaScript environments.
.
**1. Dataset Composition**
Programming Language: JavaScript
File Count: 5M+ JavaScript files
File Format: .jsonl
Content Types
The dataset includes a wide variety of JavaScript constructs and paradigms, such as:
- Functions (declarations, expressions, arrow functions)
- Classes and prototypes
- Modules (CommonJS and ES Modules)
- Asynchronous patterns (async/await, Promises, callbacks)
- Event-driven code
- Closures and higher-order functions
- Functional programming constructs
- DOM manipulation code
- Node.js backend logic
- Frontend framework components
- JSDoc comments
- Error handling patterns
- Modern ES6+ features
**2. Intended Research Applications**
2.1 Pretraining
- Training JavaScript code foundation models from scratch
- Continued pretraining of existing LLMs
- JavaScript-specialized language modeling
- Tokenizer training for JS ecosystems
2.2 Fine-Tuning and Adaptation
- Code completion systems
- Intelligent IDE assistants
- Automated refactoring tools
- Conversational programming agents
- JavaScript-specific copilots
2.3 Code Intelligence Tasks
- Code summarization
- Code-to-text generation
- Documentation generation
- Bug detection
- Vulnerability detection
- Clone detection
- Code similarity modeling
- Minified-to-readable code transformation
- Static and structural analysis
2.4 Software Engineering Research
- Empirical studies of JavaScript coding patterns
- Analysis of async and event-driven architectures
- Framework usage studies
- Dependency modeling
- AST-based experiments
- Cross-version JavaScript evolution analysis
**3. Relationship to [Java-Code-Large](https://huggingface.co/datasets/ajibawa-2023/Java-Code-Large)**
JavaScript-Code-Large complements **Java-Code-Large**, enabling comparative research between:
- Statically typed vs dynamically typed languages
- Class-based vs prototype-based paradigms
- Backend vs frontend dominant ecosystems
- JVM vs Node.js environments
Together, these datasets support cross-language transfer learning and controlled specialization studies.
Thanks to open source community for all the guidance & support!! |