AI Test Generation
Quick Reference
What & Why
Definition
>= 60% of new functions have AI-generated unit tests with edge cases, covering >= 80% of branches.
Business Value
Catches 40% more code issues than human-only review and reduces code review time by 60% while maintaining quality through AI-augmented reviews Achieving >= 60% functions have AI tests is a key milestone toward this goal.
Context
This capability is part of the Optimization milestone's focus on ai enablement, predictive ops, self-healing. Essential for teams targeting LT, CFR improvements.
Success Criteria
Target
>= 60% functions have AI tests
Measurement
AI test generation coverage
Evidence
- AI-generated test code
- Coverage improvement metrics
- Test quality validation
In Practice
Real-World Implementation
Developer writes function, AI generates tests: happy path, edge cases (null, empty, boundary values), error conditions. Developer reviews and adjusts.
Concrete Example
Implementation Guide
Prerequisites
Implementation Steps
Follow the measurement approach: AI test generation coverage
For detailed step-by-step guidance, refer to the AI-Enabled Code & Review Automation Implementation Kit.
Resources
Implementation Kit
AI-Enabled Code & Review Automation KitTemplates
Browse all templatesRelated Resources
View learning pathsRelated Capabilities
Prerequisites
Implement these first
Complementary
Often adopted together, from the AI-Enabled Code & Review Automation epic
Troubleshooting & FAQs
Common Issues
Issue: Target metric not improving
Solution: Verify measurement is accurate, check if prerequisites are fully implemented, review evidence artifacts for completeness
Issue: Team resistance to adoption
Solution: Start with pilot team, demonstrate value with metrics, provide training and support during transition
Issue: Inconsistent implementation across teams
Solution: Create shared templates and guidelines, establish regular sync meetings, use automation to enforce standards
Frequently Asked Questions
Can we implement this before completing prerequisites?
While possible, it's not recommended. Prerequisites ensure foundational practices are in place, making this capability more effective and easier to adopt.
How long does implementation typically take?
Most capabilities can be implemented within 185 days when tackled as part of the Optimization milestone. Individual timelines vary based on team size and existing practices.