What the Data for This Category Looks Like
The data sources for this category include four types: requirement specification documents, test environment configurations, customer business samples, and defect management systems. Daily produced documents include UAT test cases, acceptance issue tickets, acceptance reports, and signature confirmation sheets. These documents are jointly maintained by implementation consultants, test managers, and customer business representatives. Data is updated once per phase or per version. All documents have a fixed field structure, including core content such as business scenarios, defect severity, and acceptance conclusions.
How These Characteristics Impose Constraints on Workflow Orchestration
Multi-source data sources require workflows to be configured with cross-data-source pull nodes. This ensures simultaneous acquisition of different types of information such as requirement specifications and test environments. Fixed document structures require workflow nodes to map to standard fields for UAT test cases and acceptance issue tickets. This avoids field mismatch issues. Update frequency per phase or per version requires workflows to bind version trigger rules. This ensures timely data synchronization. The most time-consuming links include test case preparation, issue reproduction classification, and acceptance confirmation. These links require workflows to include automated transfer logic. This reduces manual operation time and avoids acceptance delay risks.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind UAT test case ID, acceptance issue ticket number, customer business sample version | Match core identification fields of category data to enable associated transfer across documents |
nodeId | Assign fixed IDs to three nodes: test case review, issue reproduction, acceptance confirmation | Clarify node boundaries for workflow transfer, adapt to fixed business links of the category |
| Trigger Timing | Within 72 hours after each version release | Match the update frequency of the category per phase or per version to ensure timely data synchronization |
| Text Extraction Scope | Extract preconditions of UAT test cases, defect severity of acceptance issue tickets | Align with standard field structures of category documents, reduce manual entry costs |
| Exception Alert Threshold | Trigger alert when issue reproduction exceeds 600 seconds | Cover the most time-consuming issue reproduction link of the category, avoid acceptance delays |
| Single Data Pull Limit | Top 10 acceptance issue ticket records | Adapt to the document volume scale of a single phase for the category, avoid overloading system resources |
Three Common Misconfigurations
- Empty knowledge base information is extracted after workflow runs: No customer business sample data source exclusive to user acceptance testing support is bound. Only a general dataset is called, which cannot match the business field structure of the category.
- Node transfer errors occur during debugging: Node identifiers are not assigned according to the
nodeIdnaming rule, causing the FastGPT v4.17.0 workflow engine to fail to recognize node paths. - Workflow processing performance does not meet expectations: The binding range of
variablesis not limited, causing nodes to repeatedly pull historical data from multiple phases and occupy excessive system resources.
How to Verify Proper Configuration
- Check if the workflow’s
variablesare bound to category-specific document fields such as UAT test cases and acceptance issue tickets. - Verify that each node’s
nodeIdcorresponds one-to-one with the business links of test case review, issue reproduction, and acceptance confirmation, with no duplicates or omissions. - Trigger a workflow after a version update, confirm that data can be normally pulled from specified sources such as requirement specifications and test environments.
- Simulate an overtime scenario in the issue reproduction link, confirm that the exception alert rule triggers normally.
The values provided are common starting points and should be evaluated against relevant samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.