Update README.md

README.md

@@ -9,4 +9,126 @@ tags:
 - Ruby
 size_categories:
 - 100K<n<1M
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+---
+
+# Ruby-Code-Large
+
+**Ruby-Code-Large** is a large-scale corpus of Ruby programming language source code comprising **331,743 code samples** stored in `.jsonl` format. The dataset is designed to support research and development in large language model (LLM) pretraining, static analysis, web application development, and software engineering automation within the Ruby ecosystem.
+
+By offering a substantial, language-focused dataset, Ruby-Code-Large enables targeted experimentation in dynamic programming, object-oriented design, and rapid application development—areas where Ruby is widely used, particularly in web frameworks and scripting.
+
+Ruby-Code-Large addresses the lack of large, curated, Ruby-specific datasets, enabling focused research on expressive syntax, metaprogramming, and high-level abstractions.
+
+
+
+## 1. Dataset Composition
+
+### Programming Language
+
+Ruby
+
+### Total Size
+
+331,743 code samples
+
+### File Format
+
+`.jsonl` (JSON Lines)
+
+
+
+## 2. Content Overview
+
+The dataset captures a wide spectrum of Ruby programming constructs, ranging from foundational syntax to advanced metaprogramming and framework-oriented patterns.
+
+
+
+### 2.1 Core Language Features
+
+* Methods and blocks
+* Classes and modules
+* Mixins and inheritance
+* Symbols and hashes
+* Iterators and enumerables
+* Exception handling (`begin`, `rescue`, `ensure`)
+* Dynamic typing and duck typing
+* Constants and global variables
+
+
+
+### 2.2 Object-Oriented and Functional Paradigms
+
+* Class-based design
+* Encapsulation and polymorphism
+* Functional constructs using blocks, procs, and lambdas
+* Method chaining
+* DSL-style coding patterns
+* Code reuse via modules and mixins
+
+
+
+### 2.3 Memory and Execution Model
+
+* Garbage-collected memory management
+* Object allocation patterns
+* Symbol vs string memory usage
+* Lazy evaluation patterns
+* Performance considerations in Ruby
+
+
+
+### 2.4 Data Structures
+
+* Arrays and hashes
+* Sets and ranges
+* Custom data structures
+* Nested collections
+* Enumerable transformations (`map`, `select`, `reduce`)
+
+
+### 2.5 Web and Application Development
+
+* MVC patterns (commonly used in Ruby frameworks)
+* Routing and controllers
+* Background job patterns
+* Database interaction patterns (ORM-style)
+* RESTful API implementations
+* Templating and view logic
+
+
+## 3. Intended Research Applications
+
+### 3.1 Fine-Tuning and Adaptation
+
+* Code completion systems for Ruby
+* Intelligent IDE assistants
+* Automated refactoring tools
+* Conversational programming agents
+* Framework-aware coding assistants
+
+
+
+### 3.2 Code Intelligence Tasks
+
+* Code summarization
+* Code-to-text generation
+* Documentation generation
+* Bug detection (e.g., nil errors, undefined methods)
+* Security vulnerability detection
+* Clone detection
+* Code similarity analysis
+* Dead code detection
+* Complexity estimation
+* Dynamic behavior analysis
+
+
+
+## 4. Key Advantages
+
+* **Language-specific**: Focused purely on Ruby (no cross-language noise)
+* **Dynamic paradigm coverage**: Includes idiomatic Ruby and metaprogramming patterns
+* **Web-focused**: Reflects real-world Ruby usage in application development
+* **Diverse**: Covers multiple coding styles and abstraction levels
+* **Research-ready**: Suitable for ML pipelines and static/dynamic analysis tools
+
+