工作流

# Code Review Workflow

## Pre-Review Checklist
- [ ] Code follows project style guide
- [ ] All tests pass locally
- [ ] No console.log or debugging code
- [ ] Comments explain "why" not "what"
- [ ] PR description is clear and complete

## Review Focus Areas
1. **Architecture**: Does this fit our existing patterns?
2. **Security**: Any potential vulnerabilities?
3. **Performance**: Any obvious bottlenecks?
4. **Testing**: Are edge cases covered?
5. **Documentation**: Is it clear how to use new features?

## Review Response
- Address all feedback within 24 hours
- Mark conversations as resolved when addressed
- Re-request review after major changes

# Bug Triage Workflow

## Information Gathering
1. Reproduce the bug in local environment
2. Identify affected versions/environments
3. Check if similar issues exist
4. Gather error logs and stack traces

## Priority Assessment
**P0 (Critical)**: Production down, data loss, security breach
**P1 (High)**: Major feature broken, significant user impact
**P2 (Medium)**: Minor feature broken, workaround available
**P3 (Low)**: Cosmetic issue, minimal impact

## Create Ticket
- Use template: "Bug Report"
- Add reproduction steps
- Include screenshots/videos if applicable
- Tag with affected component
- Assign priority label

## Next Steps
- P0/P1: Immediate fix required
- P2: Schedule for current sprint
- P3: Add to backlog

# Feature Planning Workflow

## Requirements Gathering
1. Define the user problem we're solving
2. List success criteria (measurable)
3. Identify edge cases and constraints
4. Document technical dependencies

## Design Considerations
1. How does this fit existing architecture?
2. What data models are needed?
3. What API changes are required?
4. How will this impact performance?

## Implementation Plan
1. Break into smaller, shippable pieces
2. Identify which pieces can be done in parallel
3. Note any feature flags needed
4. Plan for backwards compatibility

## Testing Strategy
1. What unit tests are needed?
2. What integration tests are needed?
3. How will we test edge cases?
4. What manual testing is required?

1. Check staging environment first
   (Catching issues in staging prevents production incidents)