Backend Contract Guard

3. Business Logic Enforcement

• Validate two-role access model with ownership/capability permissions
• Check model lifecycle workflows
• Verify approval process implementation
• Confirm edge deployment capabilities
• Test multi-step process state management

4. File Handling Systems

• Validate secure file upload and storage
• Check proper status tracking for uploads
• Verify file attachment integration with conversations
• Test file cleanup and retention policies
• Confirm virus scanning and security measures

API Implementation Standards

Endpoint Consistency

• Follow RESTful design principles where applicable
• Use consistent URL patterns and naming conventions
• Implement proper HTTP method usage
• Apply appropriate response caching strategies
• Support proper pagination and filtering

Request/Response Handling

• Validate input parameters according to specification
• Sanitize all user inputs to prevent injection attacks
• Format responses according to documented structure
• Implement proper content negotiation
• Handle large payloads appropriately

Authentication & Authorization

• Implement JWT-based authentication correctly
• Enforce role-based access control (RBAC)
• Apply principle of least privilege
• Implement proper session management
• Support API key authentication where specified

Data Layer Standards

Database Design

• Follow the documented data model precisely
• Implement proper normalization to reduce redundancy
• Use appropriate data types for each field
• Create indexes for frequently queried fields
• Implement proper constraints and validation

Data Integrity

• Use transactions for operations that span multiple tables
• Implement proper error handling and rollback mechanisms
• Validate data consistency across related entities
• Handle concurrent access appropriately
• Implement proper backup and recovery procedures

Performance Considerations

• Optimize queries for expected load patterns
• Use connection pooling appropriately
• Implement proper pagination for large datasets
• Cache frequently accessed data appropriately
• Monitor and optimize slow queries

Service Architecture Standards

Microservice Patterns

• Implement proper service boundaries
• Use asynchronous communication where appropriate
• Implement circuit breaker patterns
• Design for graceful degradation
• Support distributed tracing

Event-Driven Architecture

• Use message queues for asynchronous processing
• Implement proper error handling and retry mechanisms
• Support dead letter queues for failed messages
• Ensure event ordering where required
• Implement idempotency for event handlers

Caching Strategy

• Use appropriate caching layers (application, database, CDN)
• Implement cache invalidation strategies
• Support cache warming for critical data
• Monitor cache hit/miss ratios
• Implement cache fallback mechanisms

Security Standards

Input Validation & Sanitization

• Validate all incoming request parameters
• Sanitize user inputs to prevent injection attacks
• Implement proper file type and size validation
• Use parameterized queries to prevent SQL injection
• Apply content security policies

Authentication & Authorization

• Implement secure password hashing (bcrypt/scrypt)
• Use proper JWT signing and validation
• Implement rate limiting for authentication endpoints
• Support multi-factor authentication
• Implement proper session management

Data Protection

• Encrypt sensitive data at rest and in transit
• Implement proper key management
• Support data anonymization where required
• Implement proper audit logging
• Ensure compliance with privacy regulations

Performance Requirements

Response Time Benchmarks

• Authentication endpoints: < 200ms (95th percentile)
• CRUD operations: < 100ms (95th percentile)
• Complex queries: < 500ms (95th percentile)
• File uploads: Progress updates every 100ms
• Model inference: Within acceptable latency bounds

Scalability Targets

• Support 10,000+ concurrent users
• Handle 1000+ requests per second
• Process 1TB+ file uploads per month
• Maintain 99.9% uptime SLA
• Scale horizontally with load

Resource Utilization

• CPU usage under 70% under peak load
• Memory usage within allocated limits
• Database connection usage optimized
• Network bandwidth utilization efficient
• Storage growth within projected limits

Review Checklist

API Endpoints

• All documented endpoints implemented
• Request/response formats match specification
• HTTP status codes used correctly
• Authentication/authorization enforced properly
• Rate limiting implemented where required
• Error responses follow standard format

Data Models

• Database schema matches documentation
• Foreign key relationships implemented
• Proper indexing for performance
• Data validation implemented
• Audit logging configured
• Constraints and uniqueness enforced

Business Logic

• Two-role access model with ownership/capability permissions implemented
• Model lifecycle workflows functional
• Approval processes working correctly
• Multi-step processes maintain state
• File attachment system integrated
• Edge deployment capabilities available

Security Implementation

• Input validation and sanitization applied
• Authentication works as specified
• Authorization enforces proper access
• Data encryption implemented
• Rate limiting prevents abuse
• Audit logging captures required events

Performance & Reliability

• Response times meet benchmarks
• Error handling is robust
• Service recovery procedures implemented
• Monitoring and alerting configured
• Backup and recovery tested
• Load testing performed

Common Issues to Identify

API Issues

• Endpoints returning incorrect status codes
• Response formats not matching specification
• Missing authentication on protected endpoints
• Improper error handling
• Inconsistent parameter validation
• Incorrect pagination implementation

Data Issues

• Schema not matching documentation
• Missing foreign key constraints
• Inadequate indexing causing slow queries
• Improper data validation
• Missing audit trails
• Data consistency issues

Performance Issues

• Slow endpoint response times
• Database queries without proper indexing
• Inefficient memory usage
• Poor handling of large file uploads
• Inadequate caching strategies
• Blocking operations in request handling

Security Issues

• Insufficient input validation
• Weak authentication implementation
• Improper access control
• Unencrypted sensitive data
• Missing rate limiting
• Vulnerable dependencies

Testing Requirements

Unit Testing

• All business logic functions tested
• Data access layer thoroughly tested
• Authentication/authorization logic verified
• Error handling paths tested
• API endpoint controllers tested
• Utility functions covered

Integration Testing

• End-to-end API flows tested
• Database transaction scenarios tested
• File upload/download workflows tested
• Authentication and authorization tested
• External service integrations tested
• Error condition workflows tested

Load Testing

• Stress test API endpoints
• Database performance under load
• File upload throughput testing
• Concurrent user scenarios
• Memory and CPU usage monitoring
• Response time under load

Verification Methods

Static Analysis

• Code linting and formatting checks
• Dependency vulnerability scanning
• Security vulnerability assessment
• Type checking for typed languages
• Code complexity analysis
• Documentation completeness check

Dynamic Testing

• Functional testing of all features
• Performance benchmarking
• Security penetration testing
• Load and stress testing
• Chaos engineering for resilience
• Real-world usage scenario testing

Compliance Verification

• Privacy regulation compliance
• Industry security standards adherence
• API specification compliance
• Data retention policy enforcement
• Audit trail completeness
• Access control effectiveness

Acceptance Criteria

Backend implementation passes review when it:

• Implements all API endpoints according to specification
• Maintains data integrity as defined in data models
• Enforces all business logic requirements
• Meets security standards and recommendations
• Achieves stated performance benchmarks
• Supports scalability requirements
• Provides adequate monitoring and logging
• Includes comprehensive error handling
• Passes all automated and manual tests
• Documents all implemented functionality

Recommended Tools

Development Tools

• OpenAPI/Swagger for API documentation
• Postman/Newman for API testing
• Docker for consistent environments
• Git hooks for code quality enforcement
• CI/CD pipeline for automated testing

Monitoring Tools

• Application performance monitoring (APM)
• Infrastructure monitoring
• Database performance monitoring
• Error tracking and alerting
• Log aggregation and analysis
• Security monitoring and alerting

Security Tools

• Static application security testing (SAST)
• Dynamic application security testing (DAST)
• Interactive application security testing (IAST)
• Dependency vulnerability scanners
• Security configuration auditors
• Penetration testing tools