Integration with Expression Parsers

Oct 13, 2025 by thesweetdesigns.com 115 views

Problem Statement

The KAIREI DSL has grown in complexity, leading to challenges in maintaining consistent and up-to-date documentation. Current approaches involve:

Manual documentation that becomes outdated as the parser implementation evolves
AI-based validation that lacks complete understanding of the DSL's syntax
No single source of truth for the DSL specification

This creates friction for both developers and users, as syntax errors can be difficult to diagnose, and the correct syntax is not clearly documented directly from the implementation.

Proposed Solution

Implement a lightweight documentation generator that integrates directly with the existing parser combinators, making the parser itself the source of truth for DSL documentation.

Implementation Approach

1. Parser Extension Trait

Add a documentation extension trait to annotate parser combinators with syntax descriptions, examples, and explanations:

/// Documentation metadata extension for parsers
pub trait DocParserExt<I, O, E>: Parser<I, O, E> {
    fn with_doc(self, name: &str) -> DocParser<Self, O>
    where
        Self: Sized;
        
    fn with_description(self, description: &str) -> DocParser<Self, O>
    where
        Self: Sized + Into<DocParser<Self, O>>;
        
    fn with_syntax(self, syntax: &str) -> DocParser<Self, O>
    where
        Self: Sized + Into<DocParser<Self, O>>;
        
    fn with_example(self, example: &str) -> DocParser<Self, O>
    where
        Self: Sized + Into<DocParser<Self, O>>;
}

2. Integration with Expression Parsers

Apply the extension to detailed expression parsers to capture syntax rules:

pub fn parse_binary_expression(input: &str) -> IResult<&str, Expr> {
    // Original parser logic
    (
        parse_primary_expression,
        many0(
            tuple((
                alt((
                    tag("+").with_doc("Addition").with_syntax("expr + expr"),
                    tag("-").with_doc("Subtraction").with_syntax("expr - expr"),
                    tag("*").with_doc("Multiplication").with_syntax("expr * expr"),
                    tag("/").with_doc("Division").with_syntax("expr / expr"),
                    // Other operators...
                )),
                parse_primary_expression
            ))
        )
    )
    .map(|(first, operations)| {
        // Transformation logic...
    })
    .with_doc("BinaryExpression")
    .with_description("Binary expressions represent arithmetic, logical, or comparison operations between two expressions.")
    .with_syntax("left_expr operator right_expr")
    .with_example("count + 1")
    .parse(input)
}

3. Documentation Collection System

Create a documentation collector that harvests metadata from parsers:

pub struct DocCollector {
    docs: HashMap<String, DocInfo>,
}

impl DocCollector {
    pub fn new() -> Self { /* ... */ }
    
    pub fn collect_from_parser<I, O, E, P>(&mut self, parser: &DocParser<P, O>)
    where
        P: Parser<I, O, E>;
        
    pub fn generate_markdown(&self) -> String;
    pub fn generate_html(&self) -> String;
}

4. API Integration

Add HTTP endpoints to expose the documentation:

async fn get_markdown_docs(app_state: web::Data<AppState>) -> impl Responder {
    let doc_collector = &app_state.doc_collector;
    let markdown = doc_collector.generate_markdown();
    
    HttpResponse::Ok()
        .content_type("text/markdown")
        .body(markdown)
}

5. Static File Generation

Generate static documentation during the build process:

fn generate_documentation() -> std::io::Result<()> {
    let mut collector = DocCollector::new();
    initialize_parsers(&mut collector);
    
    std::fs::create_dir_all("./static/docs")?;
    std::fs::write("./static/docs/kairei_dsl_reference.md", collector.generate_markdown())?;
    std::fs::write("./static/docs/index.html", collector.generate_html())?;
    
    Ok(())
}

Expected Benefits

Single Source of Truth: The parser implementation becomes the authoritative source for syntax documentation
Consistency: Documentation automatically reflects the latest syntax changes
Accuracy: Syntax examples and descriptions come directly from the implementation
Developer Experience: Clear, accurate documentation makes the DSL easier to use
Reduced Maintenance: No need to manually update documentation when syntax changes

Implementation Plan

Phase 1: Core Infrastructure (1-2 weeks)

Implement DocParser wrapper and extension trait
Create basic DocCollector with Markdown and HTML output
Test with a small subset of parsers

Phase 2: Parser Integration (2-3 weeks)

Apply documentation metadata to all expression parsers
Add documentation to block-level parsers
Implement static file generation in build process

Phase 3: API Integration (1-2 weeks)

Add documentation endpoints to HTTP API
Create basic web UI for browsing documentation
Integrate with CI/CD pipeline

Future Extensions

Interactive Documentation: Add an interactive playground for testing DSL snippets
Search Functionality: Add search capabilities to the documentation
Contextual Docs: Integrate with IDE extensions for context-aware documentation
AI Training Data: Use generated documentation to improve AI validation capabilities

Resources Required

1 developer for implementation
Review time from team members familiar with the parser implementation
CI/CD integration for automated documentation generation

Conclusion

By integrating documentation generation directly with the parser combinators, we can create a robust, accurate, and maintainable documentation system for the KAIREI DSL. This approach ensures that documentation remains in sync with the implementation, reducing friction for both developers and users of the DSL.

Frequently Asked Questions

Q: What is the current state of documentation for the KAIREI DSL?

A: The current documentation for the KAIREI DSL is manual and outdated, leading to inconsistencies and difficulties in maintaining accurate documentation.

Q: How does the proposed solution address the current documentation issues?

A: The proposed solution integrates documentation generation directly with the parser combinators, making the parser itself the source of truth for DSL documentation. This ensures that documentation remains in sync with the implementation, reducing friction for both developers and users of the DSL.

Q: What are the expected benefits of implementing the proposed solution?

A: The expected benefits include:

Single Source of Truth: The parser implementation becomes the authoritative source for syntax documentation
Consistency: Documentation automatically reflects the latest syntax changes
Accuracy: Syntax examples and descriptions come directly from the implementation
Developer Experience: Clear, accurate documentation makes the DSL easier to use
Reduced Maintenance: No need to manually update documentation when syntax changes

Q: What is the implementation plan for the proposed solution?

A: The implementation plan consists of three phases:

Phase 1: Core Infrastructure (1-2 weeks)
- Implement DocParser wrapper and extension trait
- Create basic DocCollector with Markdown and HTML output
- Test with a small subset of parsers
Phase 2: Parser Integration (2-3 weeks)
- Apply documentation metadata to all expression parsers
- Add documentation to block-level parsers
- Implement static file generation in build process
Phase 3: API Integration (1-2 weeks)
- Add documentation endpoints to HTTP API
- Create basic web UI for browsing documentation
- Integrate with CI/CD pipeline

Q: What are the future extensions for the proposed solution?

A: The future extensions include:

Interactive Documentation: Add an interactive playground for testing DSL snippets
Search Functionality: Add search capabilities to the documentation
Contextual Docs: Integrate with IDE extensions for context-aware documentation
AI Training Data: Use generated documentation to improve AI validation capabilities

Q: What resources are required for implementing the proposed solution?

A: The resources required include:

1 developer for implementation
Review time from team members familiar with the parser implementation
CI/CD integration for automated documentation generation

Q: What is the expected timeline for implementing the proposed solution?

A: The expected timeline is approximately 6-8 weeks, depending on the complexity of the implementation and the availability of resources.

Q: How will the proposed solution be maintained and updated?

A: The proposed solution will be maintained and updated through regular reviews and updates to the parser implementation, as well as through the integration of new features and functionality.

Conclusion

The proposed solution for integrating documentation generation with the parser combinators offers a robust, accurate, and maintainable documentation system for the KAIREI DSL. By addressing the current documentation issues and providing a clear implementation plan, the proposed solution is well-positioned to improve the developer experience and reduce maintenance efforts for the DSL.