📄️ Auto-Analysis of launches
The analysis feature of the ReportPortal makes it possible for the application to check and pass part of the routine duties by itself.
📄️ Search for the similar "To investigate" items
Let's consider below an example of ML-driven failure triage in ReportPortal.
📄️ ML Suggestions
ML suggestions functionality is based on previously analyzed results (either manually or via Auto-analysis feature) using Machine Learning. The functionality is provided by the Analyzer service in combination with ElasticSearch.
📄️ How models are retrained
In the Auto-analysis and ML suggestions processes several models take part:
📄️ Manual Analysis
Manual Analysis is presented on our test report dashboard by “Make decision” modal.
📄️ Pattern Analysis
Pattern analysis is a feature that helps you to speed up test failure analysis by finding common patterns in error logs.
📄️ Unique Error Analysis
You can look at the test failure analysis from different points of view: qualitative (passing rate – How many tests have failed?) and quantitative (Why have they failed?). For example, if 1000 test cases are failed, then