Architecture Communication Canvas: AsciiDoc Linter

Value Proposition

  • Automated quality assurance for AsciiDoc documentation

  • Consistent documentation style across projects

  • Early detection of documentation issues

  • Reduced review effort

  • Integration with CI/CD pipelines

Core Functions

  • Lint AsciiDoc files for common issues

  • Check heading structure and format

  • Validate document consistency

  • Generate detailed reports

  • Configurable rule sets

  • Multiple output formats (console, JSON, HTML)

  • Git pre-commit hook integration

Core Decisions - Good or Bad

Good:

  • Python as implementation language (wide adoption, great libraries)

  • Modular rule system for easy extension

  • Clear separation of concerns (rules, parser, reporter)

  • Test-driven development approach

  • AsciiDoc for documentation

Bad:

  • Limited to AsciiDoc format

  • No real-time linting

  • No IDE integration yet

Strategic:

  • Focus on documentation quality

  • Extensible architecture

  • Community-driven rule development

Technologies

  • Python 3.8+

  • unittest framework

  • AsciiDoc parser

  • YAML/JSON for configuration

  • Git integration

  • CI/CD tools

  • HTML report generation

Key Stakeholder

  • Documentation writers

  • Technical authors

  • Development teams

  • Documentation maintainers

  • Open source projects

  • Technical documentation teams

  • Quality assurance teams

Quality Requirements

  • Performance: Fast processing for CI/CD

  • Extensibility: Easy to add new rules

  • Reliability: No false positives

  • Usability: Clear error messages

  • Configurability: Flexible rule settings

  • Maintainability: Well-documented code

  • Testability: Comprehensive test suite

Business Context

External Systems:

  • Version Control Systems (Git)

  • CI/CD Pipelines

  • Documentation Build Tools

  • IDE Plugins (planned)

  • Issue Tracking Systems

Data Flow:

  • AsciiDoc files as input

  • Configuration files (YAML/JSON)

  • Lint reports as output

  • Integration webhooks

Components / Modules

Diagram

Core Risks and Missing Information

Risks:

  • Performance impact on large documentation sets

  • False positives affecting user acceptance

  • Complexity of rule configurations

  • Integration challenges with existing tools

  • Maintenance of rule set as AsciiDoc evolves

Missing Information:

  • Real-world usage patterns

  • Common documentation anti-patterns

  • IDE integration requirements

  • Performance benchmarks

  • User preferences for rule configuration

Software Architecture Canvas by Gernot Starke, Patrick Roos and arc42 Contributors is licensed under Attribution-ShareAlike 4.0 International