The Enterprise Reporting Automation Engine includes automated validation testing designed to verify data quality validation logic and ensure expected outcomes are produced during pipeline execution.
Testing focuses on validating common data quality scenarios frequently encountered within enterprise reporting environments.
The testing framework was designed to verify:
- Duplicate record detection
- Missing value detection
- Invalid Control ID detection
- Invalid Application ID detection
- Validation logic accuracy
- Expected pass/fail outcomes
Validation tests are executed using:
tests/run_validation_tests.py
The script generates an automated validation report containing:
- Test Name
- Expected Result
- Actual Result
- Pass/Fail Status
Generated output:
data/output/Validation_Test_Results.xlsx
| Test Scenario | Expected Result |
|---|---|
| Duplicate Row Detection | 1 Duplicate Found |
| No Duplicate Rows | 0 Duplicates Found |
| Missing Value Detection | 1 Missing Value Found |
| No Missing Values | 0 Missing Values Found |
| Invalid Control ID Detection | 1 Invalid Control ID Found |
| No Invalid Control IDs | 0 Invalid Control IDs Found |
| Invalid Application ID Detection | 1 Invalid Application ID Found |
| No Invalid Application IDs | 0 Invalid Application IDs Found |
| Metric | Result |
|---|---|
| Total Tests Executed | 8 |
| Tests Passed | 8 |
| Tests Failed | 0 |
| Success Rate | 100% |
The automated validation report is generated during testing and stored within:
data/output/Validation_Test_Results.xlsx
Sample Results:
| Test Name | Status |
|---|---|
| Duplicate Row Detection | PASS |
| No Duplicate Rows | PASS |
| Missing Value Detection | PASS |
| No Missing Values | PASS |
| Invalid Control ID Detection | PASS |
| No Invalid Control IDs | PASS |
| Invalid Application ID Detection | PASS |
| No Invalid Application IDs | PASS |
Planned testing enhancements include:
- PyTest integration
- Automated unit testing
- Integration testing
- Regression testing
- CI/CD pipeline testing
- Code coverage reporting
All current validation tests executed successfully and produced expected results.
The testing framework provides evidence that core validation logic functions as designed and supports the overall reliability of the reporting pipeline.