Quality Assurance (QA)
The Quality Assurance (QA) role in Engineering AI Agent focuses on verifying features and ensuring software quality through various testing methods.
Version Support
The QA role is planned but not supported in v0.1.0.
Planned Capabilities
Feature Verification
The QA agent will verify implemented features:
- Challenge and test requirements to uncover edge cases
- Perform end-to-end testing through automated procedures
- Verify user stories against acceptance criteria
- Document test results and findings
Task Management
The QA agent will manage QA task tickets in JIRA or ClickUp:
- State transitions:
- Open → In progress: When verification begins
- In progress → In review: When verification completes with bugs/issues found
- In review → Complete: When the agent approves bug fixes
- Complete → Close: When reviewers confirm QA checks are satisfactory
Bug Reporting
The QA agent will create detailed bug reports:
- Description of the issue with steps to reproduce
- Environment details and context
- Severity and priority assessment
- Screenshots or logs as needed
- Link to relevant requirements or user stories
Future Features
In upcoming releases, the QA role will expand to include:
- Automated Test Generation: Creating test scripts and scenarios automatically
- Load and Performance Testing: Assessing system behavior under stress
- Security Testing: Identifying potential security vulnerabilities
- Regression Testing: Ensuring new changes don't break existing functionality
Integration Points
The QA role will integrate with:
- Slack: For communication about quality issues
- GitHub: For reporting issues directly on repositories
- JIRA/ClickUp: For bug tracking and QA task management
- Testing Frameworks: For automated test execution