#qa-checklist.md
Version: 1.0.0
Target Models
- DeepSeek V4
- DeepSeek V3.2
- DeepSeek R1
- DeepSeek V3 Family
- Future DeepSeek Models
#Purpose
This checklist defines the minimum Quality Assurance (QA) requirements before any software product, feature, API, AI application, or platform is approved for release or production deployment.
It applies to
- SaaS Platforms
- AI Applications
- APIs
- Backend Services
- Frontend Applications
- Mobile Applications
- Enterprise Software
- Developer Tools
- Cloud Services
- Internal Platforms
Quality Assurance is not bug finding.
Quality Assurance is the systematic process of verifying that software consistently satisfies functional requirements, business objectives, user expectations, reliability standards, security requirements, and operational readiness.
Quality is engineered.
Not inspected into a product at the end.
#Core Principle
High Quality
=
Correctness
Reliability
Consistency
Usability
Security
Performance
Business Value
Every release should increase customer confidence.
Never uncertainty.
#QA Workflow
Understand Requirements
↓
Prepare Test Plan
↓
Execute Tests
↓
Verify Results
↓
Validate Business Flows
↓
Assess Risks
↓
Approve Release
↓
Continuously Improve
#1. Requirement Validation
□ Requirements reviewed
□ Acceptance criteria defined
□ User stories validated
□ Edge cases identified
□ Business rules documented
□ Assumptions verified
□ Dependencies identified
□ Scope approved
Quality begins with correct requirements.
#2. Test Planning
□ Test strategy defined
□ Test cases prepared
□ Test data created
□ Test environment prepared
□ Automation identified
□ Risks documented
□ Exit criteria defined
□ Responsibilities assigned
Well-planned testing reduces defects.
#3. Functional Testing
□ Features work as expected
□ User workflows verified
□ Business logic validated
□ Input validation tested
□ Output verified
□ Error handling tested
□ Edge cases reviewed
□ Acceptance criteria satisfied
Every requirement should have verification.
#4. User Interface Testing
□ Layout verified
□ Responsive behavior tested
□ Navigation validated
□ Forms verified
□ Buttons functional
□ Typography consistent
□ Visual defects reviewed
□ Cross-browser testing completed
Interfaces should behave consistently.
#5. API Testing
□ Endpoints validated
□ Authentication verified
□ Authorization tested
□ Request validation verified
□ Response schema validated
□ Error responses verified
□ Rate limiting tested
□ Version compatibility reviewed
APIs are products.
Treat them accordingly.
#6. Database Testing
□ CRUD operations verified
□ Constraints validated
□ Transactions tested
□ Migrations verified
□ Data integrity confirmed
□ Rollback tested
□ Index behavior reviewed
□ Backup restoration verified
Data correctness is essential.
#7. Integration Testing
□ Service integrations verified
□ Third-party APIs tested
□ Authentication providers tested
□ Email services verified
□ Queue systems validated
□ Background jobs tested
□ Payment providers verified
□ External failures handled
Systems rarely fail in isolation.
#8. Regression Testing
□ Existing functionality verified
□ Previous bugs remain fixed
□ Shared modules tested
□ Common workflows validated
□ Critical paths executed
□ Dependencies reviewed
□ Automation completed
□ Regression report approved
Every release should preserve quality.
#9. Performance Testing
□ Response times acceptable
□ Load testing completed
□ Stress testing reviewed
□ Memory stable
□ CPU usage acceptable
□ Database performance verified
□ Scalability reviewed
□ Performance regressions absent
Performance is part of quality.
#10. Security Testing
□ Authentication tested
□ Authorization verified
□ Input validation tested
□ Session management verified
□ Sensitive data protected
□ Dependency vulnerabilities reviewed
□ API security tested
□ Security defects resolved
Secure software is quality software.
#11. Accessibility Testing
□ Keyboard navigation verified
□ Screen readers supported
□ Color contrast reviewed
□ Focus states visible
□ Alternative text available
□ Semantic structure validated
□ Accessibility guidelines followed
□ Major accessibility issues resolved
Accessibility is a quality requirement.
#12. AI Quality (If Applicable)
□ Prompt behavior verified
□ Context accuracy reviewed
□ Tool execution validated
□ Hallucination risks assessed
□ Safety filters verified
□ Output consistency reviewed
□ Failure scenarios tested
□ Fallback behavior validated
AI quality extends beyond correctness.
#13. Compatibility Testing
□ Browser compatibility verified
□ Mobile compatibility verified
□ Tablet compatibility verified
□ Operating systems tested
□ Screen sizes reviewed
□ API compatibility confirmed
□ Version compatibility maintained
□ Legacy behavior preserved
Compatibility reduces customer friction.
#14. Data Validation
□ Input data verified
□ Output data validated
□ Data migration tested
□ Import functionality verified
□ Export functionality verified
□ Duplicate handling reviewed
□ Data consistency maintained
□ Corrupted input handled safely
Incorrect data damages trust.
#15. Error Recovery
□ Failure scenarios tested
□ Retry behavior verified
□ Recovery mechanisms validated
□ Timeout handling tested
□ Offline behavior reviewed
□ User recovery supported
□ Logging verified
□ Recovery documentation updated
Good software fails gracefully.
#16. User Acceptance
□ Product owner approval
□ Stakeholder approval
□ Customer workflows validated
□ Business objectives satisfied
□ Documentation reviewed
□ Release notes approved
□ Known issues accepted
□ Final QA approval completed
Quality includes business validation.
#17. Defect Management
□ Defects classified
□ Critical defects resolved
□ High-risk defects reviewed
□ Root causes documented
□ Duplicate issues removed
□ Regression risks identified
□ Defect trends analyzed
□ Technical debt recorded
Every defect should improve the process.
#18. Documentation
□ Test plan documented
□ Test cases documented
□ Test evidence stored
□ Defect reports completed
□ Automation documented
□ Environment documented
□ QA metrics recorded
□ Lessons learned documented
Documentation preserves organizational knowledge.
#19. QA Review
Review
□ Product quality
□ Test coverage
□ Defect trends
□ Customer impact
□ Risk assessment
□ Automation effectiveness
□ Team feedback
□ Improvement opportunities
Quality continuously evolves.
#20. Continuous Improvement
Continuously improve
Test Coverage
↓
Automation
↓
Reliability
↓
Risk Detection
↓
Defect Prevention
↓
Customer Satisfaction
↓
Release Confidence
↓
QA Maturity
Great QA prevents defects before testing begins.
#QA Quality Attributes
Evaluate
Correctness
Reliability
Consistency
Coverage
Traceability
Usability
Maintainability
Release Confidence
#QA Questions
Before approval ask
Does every requirement have corresponding validation?
↓
Can critical customer workflows succeed consistently?
↓
Have regression risks been eliminated?
↓
Can the software recover gracefully from failures?
↓
Are known defects understood and accepted?
↓
Does testing provide confidence rather than assumptions?
↓
Would experienced QA Engineers confidently approve this release?
#Severity Levels
Critical
Application crashes
Data corruption
Security vulnerabilities
Broken business workflows
Release blockers
Major
Failed integrations
Regression failures
Performance degradation
Compatibility failures
Critical UI defects
Medium
Minor functional issues
Usability improvements
Documentation gaps
Automation improvements
Minor
Visual inconsistencies
Typos
Low-priority enhancements
Future optimization
#QA Checklist
✓ Requirements validated
✓ Test plan prepared
✓ Functional testing completed
✓ UI verified
✓ API tested
✓ Database validated
✓ Integrations verified
✓ Regression testing completed
✓ Performance tested
✓ Security reviewed
✓ Accessibility validated
✓ AI quality reviewed (if applicable)
✓ Compatibility verified
✓ Data validated
✓ Recovery tested
✓ User acceptance completed
✓ Defects managed
✓ Documentation complete
✓ QA review completed
✓ Continuous improvement established
#Anti-Patterns
Avoid
Testing without requirements
Testing only happy paths
Ignoring regression testing
Manual testing for repetitive tasks only
Ignoring edge cases
Skipping security validation
Ignoring accessibility
Testing in unrealistic environments
Closing defects without verification
Treating QA as the final development phase
Confusing high test coverage with high quality
Approving releases based on assumptions
#Definition of Done
QA review is complete when
- Business requirements, acceptance criteria, and customer expectations have been fully validated through comprehensive testing.
- Functional, integration, regression, security, performance, accessibility, compatibility, and AI-specific behavior have been independently verified where applicable.
- Critical customer workflows execute reliably under both normal and exceptional operating conditions.
- Defects have been classified, resolved, verified, or formally accepted based on documented business risk.
- Test coverage provides confidence that the software behaves consistently across supported platforms, devices, environments, and user scenarios.
- Automated and manual testing complement each other to maximize efficiency, repeatability, and defect detection.
- Documentation captures test strategies, execution evidence, defect history, quality metrics, and lessons learned for future releases.
- Product owners, stakeholders, engineering teams, and QA agree that residual risks are understood and acceptable.
- The release demonstrates measurable quality, operational stability, customer readiness, and business alignment.
- The QA process continuously improves through automation, feedback, root cause analysis, and proactive defect prevention.
Exceptional Quality Assurance is almost invisible.
Customers simply experience software that behaves predictably, recovers gracefully from failures, protects their data, performs consistently across environments, and inspires confidence because every important scenario has already been anticipated, validated, and verified before release.