What this category of data looks like
This category of data primarily comes from code repositories, test framework reports, requirement specifications, and interface definitions. Update frequency is daily or after each code commit. Daily output documents include test cases, coverage reports, Mock instructions, and defect tickets. Data fields cover test case ID, execution status, duration, coverage values, defect severity, and more. There are no standardized fixed units; adjustments are made based on specific test frameworks and project requirements. The most time-consuming steps are test data construction and boundary condition completion. Locating failed test cases also consumes significant effort. Execution durations for single complex test tasks vary widely.
What constraints these characteristics impose on scheduled tasks and automation
This category of data is tied to code commit and daily update rhythms. Therefore, scheduled tasks must adapt to code commit hook triggers or fixed daily execution cycles to avoid excessive resource usage. Structured formats for documents such as test cases and coverage reports vary across frameworks. Automation tasks must adapt to the output formats of different test frameworks to accurately read and analyze data. Test data construction and failed test case localization take a long time. Scheduled tasks must split execution steps to avoid single-run timeouts. Uncovered local logic defects increase regression costs. Therefore, automation tasks must configure failure alerts and retry mechanisms to reduce the risk of defect accumulation.
How to configure settings
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
| Trigger Timing | Trigger after code commit / Trigger at 2:00 AM daily | Match data update frequency, avoid repeated execution of unchanged test tasks |
| Single Execution Timeout Threshold | 600–1200 seconds | Adapt to average test case execution duration, avoid blocking subsequent processes due to single task timeout |
| Failure Retry Count | 2–3 times | Address temporary network fluctuations or unstable test environments, avoid misjudging task failure |
| Task Execution Concurrency | 2–4 parallel tasks | Match test environment resource limits, avoid occupying excessive server resources that impact business operations |
| Alert Trigger Condition | Task fails consecutively 2 times / Coverage deviates from preset range | Notify relevant teams of anomalies promptly, avoid defect accumulation |
Three Common Misconfigurations
- Phenomenon: Single test task execution duration exceeds 1200 seconds, triggering platform timeout interception. Cause: Test case sets are not split reasonably, merging a large number of associated test tasks into a single execution, exceeding the scheduled task timeout threshold.
- Phenomenon: Test coverage report fields are empty, causing automation analysis tasks to fail. Cause: Output formats of the corresponding test framework are not adapted, making it impossible to correctly read structured data from coverage reports.
- Phenomenon: After batch uploading test cases, duplicate cases are not automatically deduplicated, leading to redundant test execution. Cause: Unique identifier verification rules for test cases are not configured, and deduplication is not associated with code repository commit hashes.
How to Verify Proper Configuration
- Manually trigger a test task in the task management page of FastGPT v4.17.0, check if task execution logs match the configured trigger timing and timeout threshold.
- Check the automation task's alert configuration, simulate a task failure, and confirm that alert notifications are triggered normally.
- Compare the unique identifier of test cases with code commit hashes, confirm that the duplicate case deduplication logic is effective.
- View scheduled task execution records, confirm that tasks start automatically after code commits or at fixed daily times.
The values provided are common starting points and should be measured against the reader's own 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.