Code Quality Monitoring Dashboards
Status: Active
Version: 1.0.0
Last Updated: 2026-01-05
Epic: Epic 7 - Codebase Maintenance and Review
Story: Story 3 - Code Quality Metrics and Monitoring
Task: E7:S03:T02 - Create code quality monitoring dashboards
Related: Code Quality Metrics Framework, Framework Health Dashboard Guide
Executive Summary
This document defines code quality monitoring dashboards for the AI Dev Kit project. It provides dashboard templates, examples, and usage guidance for visualizing and monitoring code quality metrics across the codebase.
Key Features:
- Visual Quality Overview: At-a-glance quality status
- Dimension Breakdowns: Detailed metrics by quality dimension
- Trend Analysis: Historical quality trends
- Module-Level Views: Quality metrics by module/package
- Actionable Insights: Prioritized improvement recommendations
Dashboard Overview
Dashboard Types
- Overall Quality Dashboard - Project-wide quality overview
- Dimension Dashboards - Quality metrics by dimension
- Module Dashboards - Quality metrics by module/package
- Trend Dashboards - Historical quality trends
- Alert Dashboards - Quality alerts and thresholds
Dashboard 1: Overall Quality Dashboard
Purpose
Provide a high-level overview of code quality across the entire project.
Components
Quality Score Summary:
- Overall quality score (composite)
- Quality status (Excellent/Good/Fair/Poor)
- Quality trend (improving/stable/declining)
Dimension Scores:
- Complexity score
- Coverage score
- Duplication score
- Maintainability score
- Security score
- Performance score
- Technical debt score
Key Metrics:
- Total lines of code
- Test coverage percentage
- Number of issues
- Technical debt hours
Quality Alerts:
- Critical issues count
- Warning issues count
- Recent quality changes
Dashboard 2: Dimension Dashboards
Complexity Dashboard
Metrics:
- Average cyclomatic complexity
- Maximum complexity
- Functions exceeding threshold
- Complexity distribution
Visualizations:
- Complexity histogram
- Top complex functions
- Complexity trends
Coverage Dashboard
Metrics:
- Overall test coverage
- Branch coverage
- Function coverage
- Coverage by module
Visualizations:
- Coverage heatmap
- Coverage trends
- Uncovered code highlights
Duplication Dashboard
Metrics:
- Duplication percentage
- Number of duplication blocks
- Largest duplications
- Duplication trends
Visualizations:
- Duplication map
- Duplication trends
- Refactoring opportunities
Dashboard 3: Module Dashboards
Module Quality Overview
Per Module:
- Quality score
- Dimension scores
- Issue count
- Technical debt
Module Comparison:
- Quality ranking
- Improvement opportunities
- Best practices identification
Dashboard 4: Trend Dashboards
Quality Trends
Time Series:
- Quality score over time
- Dimension scores over time
- Issue count over time
- Technical debt over time
Trend Analysis:
- Improving trends
- Declining trends
- Stable trends
- Seasonal patterns
Dashboard 5: Alert Dashboards
Quality Alerts
Alert Types:
- Critical issues
- Warning issues
- Threshold violations
- Recent degradations
Alert Details:
- Alert description
- Affected modules
- Severity
- Recommended actions
Dashboard Templates
Markdown Dashboard Template
# Code Quality Dashboard
**Last Updated:** [DATE]
**Overall Quality Score:** [SCORE]
**Status:** [STATUS]
## Quality Overview
| Dimension | Score | Status |
|-----------|-------|--------|
| Complexity | [SCORE] | [STATUS] |
| Coverage | [SCORE] | [STATUS] |
| Duplication | [SCORE] | [STATUS] |
| Maintainability | [SCORE] | [STATUS] |
| Security | [SCORE] | [STATUS] |
| Performance | [SCORE] | [STATUS] |
| Technical Debt | [SCORE] | [STATUS] |
## Key Metrics
- **Total Lines of Code:** [COUNT]
- **Test Coverage:** [PERCENTAGE]%
- **Issues:** [COUNT]
- **Technical Debt:** [HOURS] hours
## Quality Alerts
[ALERT LIST]
Dashboard Generation
Automated Generation
Tools:
- Custom scripts
- CI/CD integration
- Scheduled jobs
Process:
- Collect metrics from tools
- Aggregate metrics by dimension
- Calculate composite scores
- Generate dashboard markdown
- Update dashboard files
Manual Generation
When Needed:
- Initial setup
- Custom dashboards
- Validation
Process:
- Collect metric data
- Calculate scores
- Create dashboard markdown
- Review and validate
- Commit dashboard
Dashboard Usage
Regular Reviews
Frequency:
- Daily: Quick status check
- Weekly: Detailed review
- Monthly: Comprehensive analysis
Review Process:
- Check overall quality score
- Review dimension scores
- Identify areas needing attention
- Plan improvements
- Track progress
Quality Improvement
Using Dashboards:
- Identify low-scoring dimensions
- Drill down to specific issues
- Prioritize improvements
- Track improvement progress
- Validate improvements
Integration
Tool Integration
Static Analysis Tools:
- SonarQube dashboards
- CodeClimate dashboards
- Custom tool dashboards
CI/CD Integration:
- Automated dashboard updates
- Quality gate visualization
- Build quality reports
Workflow Integration
Release Workflow:
- Quality checks in RW
- Quality metrics in changelog
- Quality gates
Kanban Integration:
- Quality metrics in Kanban
- Quality-based task prioritization
- Quality tracking
Best Practices
Dashboard Design
Guidelines:
- Keep dashboards focused and actionable
- Use clear visualizations
- Provide context for metrics
- Enable drill-down capabilities
Dashboard Maintenance
Guidelines:
- Update dashboards regularly
- Validate dashboard accuracy
- Review dashboard effectiveness
- Improve dashboards based on feedback
References
- Code Quality Metrics Framework:
docs/architecture/standards-and-adrs/code-quality-metrics-framework.md - Framework Health Dashboard Guide:
docs/architecture/standards-and-adrs/framework-health-dashboard-guide.md - Epic 7:
docs/project-management/kanban/epics/Epic-7/Epic-7.md - Story 3:
docs/project-management/kanban/epics/Epic-7/Story-003-code-quality-metrics-and-monitoring.md
Last updated: 2026-01-05 (v0.7.3.2+0 – Code quality monitoring dashboards created)