Integration checkpoint for epic-bufdir-reporting-export-core-logic
epic-bufdir-reporting-export-core-logic-integration-task — Integration Task
Integration Purpose
Verify integration with dependent epics: epic-bufdir-reporting-export-foundation, epic-bufdir-reporting-export-processing-services
This integration checkpoint ensures proper coordination and compatibility between different epics. It verifies that all interfaces, data flows, and dependencies are correctly implemented before proceeding.
Integrates With Epics
Execution Context
Tier 5 - 253 tasks
Can start after Tier 4 completes
Handles integration between different epics or system components. Requires coordination across multiple development streams.
| Status | pending |
| Type | Integration |
| Estimated | 4h |
| Tier | 5 |
Bufdir's column schema may have per-field business rules (conditional required fields, cross-field validation, organisation-specific category taxonomies) that cannot be expressed in a simple key-value mapping configuration. If the configuration model is too simple, supporting NHF's specific requirements will require hardcoded organisation logic, undermining the configuration-driven design.
Mitigation & Contingency
Mitigation: Design the column configuration schema as a full JSON document supporting field-level transformation rules, conditional expressions, and org-specific value enumerations. Validate the design against a real NHF Bufdir Excel template before implementation begins.
Contingency: If the configuration model cannot express all required rules, implement a thin transformation plugin interface where org-specific logic can be added as a named Dart class registered against the organisation ID, with the JSON config covering only the common cases.
For large organisations like NHF with potentially tens of thousands of activity records, the full export pipeline (query + map + generate + bundle + upload) may exceed Supabase Edge Function execution time limits (typically 150s), causing silent timeouts that leave audit records in a pending state indefinitely.
Mitigation & Contingency
Mitigation: Implement the orchestrator as a background Dart isolate with progress streaming rather than a synchronous Edge Function call. Use chunked processing for the query and mapping phases to reduce peak memory usage. Profile against realistic NHF data volumes in a staging environment.
Contingency: If processing time cannot be reduced below the timeout threshold, implement an asynchronous job model where the export is queued, processed in the background, and the user is notified via push notification when the download is ready — treating it as an eventual rather than synchronous operation.