Minotaur Capabilities for Real-Time Code Operations

Core Architecture for Real-Time Operations

1. Step-by-Step Processing

Minotaur implements a step-based parsing architecture that enables real-time operations:

• StepLexer: Tokenizes input character-by-character with multiple path support
• StepParser: Processes tokens incrementally with parallel path management
• Real-time State Tracking: Maintains current position, tokens, and valid terminals

2. Multi-Path Processing for Context Management

Similar to refakts’ approach to handling ambiguities, Minotaur uses:

• Lexer Path Management: Multiple tokenization paths for ambiguous input
• Parser Path Splitting: GLR parser-like approach for handling conflicts
• Path Merging: Optimization when paths reach the same state
• Path Invalidation: Discarding invalid paths to maintain clean context

3. Rule Activation Callbacks for Real-Time Response

Minotaur’s callback system enables surgical operations:

<rule-name> ::= <expression> => { 
  function_name(match, context, position) 
}

Real-time Applications:

• Immediate Feedback: Callbacks triggered on rule matches
• Context-Aware Actions: Access to parsing context and position
• Surgical Modifications: Precise targeting of code elements
• Event-Driven Refactoring: Automatic responses to parsing events

4. Grammar Switching for Multi-Language Support

Context-based switching enables real-time language transitions:

• Context Modifiers: <rule name (context name)> for conditional rules
• Dynamic Context Control: Context(context name, on/off) commands
• Extension-Based Switching: Seamless transitions between base and extended grammars
• Multi-Language Parsing: Support for embedded languages (SQL in C#, etc.)

Comparison with RefakTS Approach

Similarities to RefakTS “Clear Path” Philosophy

RefakTS Feature	Minotaur Equivalent	Benefit
Location-based targeting	Position tracking in callbacks	Precise code element targeting
Surgical operations	Rule activation callbacks	Minimal scope changes
Context preservation	Multi-path processing	Maintains surrounding code structure
AST manipulation	Grammar-driven parsing	Reliable language-aware operations
Find-then-refactor workflow	Select-then-callback pattern	Two-step precision operations

Minotaur Advantages for Real-Time Operations

1. Language Agnostic: Works with any language defined by grammar
2. Multi-Language Support: Handles embedded languages natively
3. Real-Time Parsing: Step-by-step processing enables live feedback
4. Extensible Grammar: Can add new language features dynamically
5. Visual Debugging: Built-in visualization of parsing states

Potential Applications for Code Generation/Refactoring

1. Real-Time Syntax Validation

• Live Error Detection: Immediate feedback on syntax errors
• Context-Aware Suggestions: Based on current parsing state
• Multi-Language Validation: For embedded language scenarios

2. Incremental Code Generation

• Template-Based Generation: Using grammar rules as templates
• Context-Sensitive Completion: Based on current parsing context
• Progressive Refinement: Building code step-by-step with validation

3. Surgical Refactoring Operations

• Rule-Based Transformations: Callbacks for specific patterns
• Scope-Limited Changes: Precise targeting without full regeneration
• Multi-File Consistency: Grammar-aware cross-file operations

4. Language Extension and DSL Creation

• Custom Language Support: Define grammars for specialized languages
• Rapid Prototyping: Quick iteration on language features
• Domain-Specific Refactoring: Operations tailored to specific domains

Implementation Strategy for RefakTS-like Operations

1. Location-Based Targeting System

// Similar to refakts select command
interface CodeLocation {
  file: string;
  startLine: number;
  startColumn: number;
  endLine: number;
  endColumn: number;
}

// Grammar callback with location awareness
<variable-declaration> ::= <type> <identifier> "=" <expression> => {
  recordLocation($2, getCurrentPosition())
}

2. Surgical Operation Framework

// Refactoring operations triggered by grammar rules
<extract-variable-target> ::= <expression> => {
  if (shouldExtractVariable($1)) {
    extractVariable($1, getCurrentContext())
  }
}

<rename-target> ::= <identifier> => {
  if (isRenameTarget($1)) {
    renameAllReferences($1, getNewName())
  }
}

3. Context-Aware Selection

// Boundary-aware selection similar to refakts
<function-boundary> ::= "function" <identifier> "(" <parameters> ")" "{" <body> "}" => {
  setBoundaryContext("function", $2, $7)
}

<class-boundary> ::= "class" <identifier> "{" <members> "}" => {
  setBoundaryContext("class", $2, $4)
}

4. Multi-Language Refactoring

// Handle embedded languages like refakts handles TypeScript
<sql-in-csharp> ::= "\"" <sql-query> "\"" => {
  switchGrammar("SQL")
  validateQuery($2)
  switchGrammar("CSharp")
}

Key Advantages for AI Code Generation

1. Reduced Cognitive Load: Grammar rules handle complexity, AI focuses on logic
2. Precise Targeting: Location-aware callbacks enable surgical operations
3. Language Extensibility: Support for new languages without core changes
4. Real-Time Feedback: Immediate validation and suggestions
5. Context Preservation: Multi-path processing maintains code structure
6. Token Efficiency: Only processes what needs to change