testing-workflow

To analyze test results, you can parse standard JSON reports to surface failures, pass rates, and performance insights. This eliminates manual log sifting by reading test result files and identifying passed, failed, or skipped statuses.

Getting test health metrics from JSON reports involves computing pass rates, total test duration, and highlighting slow tests. This provides a concise summary of test health and performance without requiring manual log analysis.

Yes, you can filter test results by module or suite for targeted debugging. This module-focused view reads standard test result formats and computes summaries to help isolate failures within specific parts of your project.

The best way to identify slow tests in CI workflows is by analyzing test result data to highlight performance insights. It computes total duration and flags slow tests, returning concise guidance and commands for next steps.

You need test results saved as a standard format like JSON, XML, or logs in your project root. The analysis reads these files to compute summaries and return recommended test commands and actions for CI and local development.

Parsing test logs manually fails to provide actionable CI insights because it lacks automated health metric computation. Automated parsing computes pass rates and identifies slow tests, returning concise guidance and commands for immediate next steps.