Analyze test result history

This document explains how to analyze past test result trends across your project.

Overview

Analyzing test result history is crucial for assessing testing quality and ensuring release confidence. It helps teams:

Detect abnormal spikes or shifts in failure/blocked rates early
Identify flaky or consistently failing tests to prioritize fixes. See Investigate flaky tests to learn more.
Compare manual vs. automated execution results
Trace regressions to specific intervals, releases, or branches
Provide evidence for release readiness and stakeholder communication

In TestOps, you can access the Test Results Analysis Report through multiple routes:

Via the Analytics & Trends dashboard: the Test Execution Results Trend widget can be expanded to navigate to the Test Results Analysis Report.
Via Analytics > Reports > Test Results Analysis Report.

Once you've accessed the report, follow these steps to analyze test result history.

Choose Project and Time Range. For short windows use daily grouping; for multi-week or release views use weekly grouping.
Filter by Execution Type (Manual / Automated), Release/Sprint, Tester, Platform/Configuration, or Branch to focus the analysis.

What this leads to: a focused dataset feeding the trend and distribution visuals so you can spot meaningful deviations.

Once data is scoped and filtered to address your concern, spot for patterns or signals:

Rising failure slope: a steady upward trend in Failed / Error / Skipped over several intervals (days/weeks) often indicates a regression in the product or a growing set of brittle tests.
Sudden spikes in Failed / Error / Skipped counts: one-off or burst spikes often point to a new defect, infra outage, or test environment misconfiguration.
High failure concentration by some scope: failures concentrated by Tester, Platform (OS/browser), Release/Branch, or Execution Type (Manual vs Automated) may require targeted investigations.
Automated/Manual conflicting results trend: if automated runs show a rising failure rate while manual runs remain stable (or vice versa), this signals differences in test coverage, timing, or environment parity.

Click a data point or segment to filter the detail table for that interval.
In the detail table, inspect each run's composition (counts of Passed / Failed / Skipped / Error ) and the run duration.
Use result badges and the test history link to open the Test Result or Test Run Details page for step-level logs, screenshots, and attachments.
Export filtered results to CSV or capture a report snapshot to share with stakeholders.