1. Conduct thorough scenario-based self-testing. Enumerate test cases covering edge, failure, and nominal business flows—annotating execution outcomes and tracking unresolved issues to closure.

2. Implement targeted unit tests with meaningful coverage metrics—not just line count, but logical branches, exception paths, and state transitions.

3. Apply defensive design: explicitly model failure modes (e.g., network timeouts, null dependencies, constraint violations) and contain their blast radius via fallbacks, circuit breakers, or idempotent retries.

4. Institutionalize post-incident reflection. Document root causes, mitigation steps, and preventive guardrails—then integrate those learnings into code reviews, checklists, or automated validation.

5. Account for environment-specific behaviors: SQL query plans may differ under scale; disk I/O latency varies across staging vs. production; permission models or third-party service endpoints often diverge.

6. Before implementation, decompose requirements into clear acceptance criteria, data flow diagrams, failure-handling strategies, and verification points—including integration boundaries and concurrency assumptions.

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Reward Distribution Workflow Review

• Verify resolution of known issues before deployment—not just detection.
• Shared infrastructure components (e.g., WeChat notification services) require cross-environment validation: success in production does not guarantee correctness in staging. Coordinate final sign-off with the responsible engineer (e.g., Wang Nan) on environment-specific constraints.
• Scale disparities matter: production databases may hold 50–100× more records than staging. Queries that perform well locally can degrade significantly under real load—profile with representative data volumes.
• Peak-time operations (e.g., midday coupon issuance) must account for concurrent database access pressure—simulate load patterns during integration testing.

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Image Upload System Observations

• Incomplete requirement interpretation led to incorrect assumptions about upload eligibility. Specifically:
  • Photo upload was permitted even when account opening failed (no e-subaccount created), violating business rules. The loop termination condition omitted the isAccountOpened && hasESubaccount predicate.
  • Binding-card failures for existing users were overlooked: such users possess asset accounts but lack e-subaccounts—triggering null dereferences.
• Pagination misuse stemmed from cognitive bias: an HQL filter based on status (status = 'PROCESSED') inherently excludes previously handled items, making pagination redundant—and dangerous—since it skips unprocessed entries that don’t match the current filter.
• Optimistic locking conflicts arose when shared domain objects were passed as method parameters. Concurrent updates from other services invalidated version stamps, causing silent update failures.
• Unbounded retry loops occurred during repeated authentication-state updates. Introduce exponential backoff and maximum attempt limits to prevent resource exhaustion.
• Infrastructure coordination is essential: confirm storage quotas, filesystem permissions, and network ACLs with operations teams before rollout—do not assume parity across environments.