Comparison View Helps Teams Pinpoint Mobile Performance Regressions

SAN FRANCISCO and NOIDA, Sept. 23, 2026 /CourierPR/ -- TestMu AI, the world's first Agentic AI-powered Quality Engineering platform, has introduced a new feature in its App Profiling Insights, allowing teams to trace mobile performance regressions to their actual source in minutes. The new Comparison view in App Profiling Insights lets teams select multiple runs of the same mobile test and overlay them run by run, rather than averaging sessions into a single trend line. Instead, the view plots individual runs against one another, filtered and grouped by device, OS version, and app build, enabling teams to pinpoint the exact source of a regression.

Mobile performance regressions are often difficult to identify, as a jump in CPU or a slower cold start could be attributed to a new build, a newer OS version, or one device model that behaves differently from the rest. Aggregate dashboards typically show that a metric has moved, but they cannot reveal which run caused the change or why. Teams often resort to re-running tests, exporting logs, and comparing screenshots manually, a process that can be time-consuming and error-prone.

The Comparison view, now available in App Profiling Insights, addresses this issue by plotting each selected run at 0:00 on a shared elapsed-time axis, so sessions of different lengths and start times line up and can be read against each other. One run is set as the baseline, and every other run's numbers show a color-coded delta against it, green where the run is better, red where it is worse. Because the same run keeps the same color across every chart, a spike in memory can be followed straight down the page to see what frame rate and startup time were doing at the same moment.

Key capabilities of the Comparison view include overlaying up to five runs at once, across CPU, memory, frame rate, disk, network, and startup time, with organization-level Service Level Agreement (SLA) bands drawn on every chart. Users can filter and group by device, OS version, app build, and pass/fail status, allowing comparisons to be narrowed to exactly the runs that isolate one variable. The view also includes Baseline and Baseline Diff, with per-metric deltas against any run chosen as the reference. Side by side, the Avg, Min, Max, and P90 metrics for every selected run allow teams to catch a build that looks healthy on average but breaches on its worst runs immediately.

The Comparison view is available now alongside the existing Trends view and its Average/p90 toggle for Appium tests on iOS and Android. For more details, visit the App Profiling Comparison documentation.