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README.md
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@@ -53,4 +53,87 @@ The dataset includes a wide variety of JavaScript constructs and paradigms, such
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- Error handling patterns
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- Modern ES6+ features
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- Error handling patterns
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- Modern ES6+ features
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**2. Intended Research Applications**
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2.1 Pretraining
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- Training JavaScript code foundation models from scratch
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- Continued pretraining of existing LLMs
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- JavaScript-specialized language modeling
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- Tokenizer training for JS ecosystems
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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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- JavaScript-specific copilots
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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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- Vulnerability detection
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- Clone detection
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- Code similarity modeling
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- Minified-to-readable code transformation
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- Static and structural analysis
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2.4 Software Engineering Research
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- Empirical studies of JavaScript coding patterns
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- Analysis of async and event-driven architectures
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- Framework usage studies
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- Dependency modeling
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- AST-based experiments
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- Cross-version JavaScript evolution analysis
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3. Relationship to **Java-Code-Large**(ajibawa-2023/Java-Code-Large)
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JavaScript-Code-Large complements **Java-Code-Large**, enabling comparative research between:
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- Statically typed vs dynamically typed languages
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- Class-based vs prototype-based paradigms
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- Backend vs frontend dominant ecosystems
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- JVM vs Node.js environments
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Together, these datasets support cross-language transfer learning and controlled specialization studies.
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