perflisted

# Perf — Performance Review ## Process 1. Identify performance-sensitive code paths from the diff (loops, queries, rendering, batch ops) 2. Run the Checklist below, marking each item as pass, fail, or N/A with reason 3. For each failure, cite the file and line number with a one-line fix hint 4. Report findings using the Evidence Required section ## When to Trigger - Database queries inside loops - Large data set processing - Rendering or UI update logic - API endpoint that could receive high traffic - File I/O in hot paths ## Checklist ### Database - [ ] No N+1 queries (use JOIN, eager loading, or batch) — N+1 queries cause latency to scale linearly with row count, turning a 1ms query into seconds under load. - [ ] Indexes exist for frequently queried columns — without indexes, the database performs full table scans, collapsing read throughput. - [ ] Pagination for large result sets — fetching all rows at once exhausts memory and increases response time for every consumer. - [ ] Connection pooling configured — opening a new connection per request adds network round-trip overhead and can exhaust database connection limits. ### Memory - [ ] No unbounded arrays or caches growing indefinitely — unbounded growth causes gradual memory exhaustion and eventual OOM kills with no warning. - [ ] Event listeners properly removed / unsubscribed — leaked listeners hold references to their context, preventing garbage collection of entire object graphs. - [ ] Large objects released aft