Test Suite Optimization

Test Suite Optimization

Qualflare's AI can analyze your test suite and surface Insights — recommendations that flag test cases worth revisiting, so suites stay lean and trustworthy as they grow instead of accumulating dead weight over time.

Recommendation Types

Each recommendation carries a confidence score and comes in one of three types:

• Flaky — the case has an inconsistent pass/fail history that looks like a flakiness problem rather than a real regression signal.
• Low Value — the case rarely catches anything (e.g. it hasn't failed in a way that indicated a real bug) and may not be worth the maintenance cost.
• Redundant — the case appears to duplicate coverage already provided by another case. Redundant recommendations additionally carry a similarity score and a pointer to the similar case, so you can compare before acting.

Recommendation Lifecycle

A recommendation starts active and moves to one of:

• Accepted — you agreed with the recommendation and took the suggested action (e.g. removed or merged the case).
• Declined — you reviewed it and chose to keep the case as-is.
• Stale — the underlying data changed enough that the recommendation no longer applies (e.g. the case's execution history shifted).

Insights never change or delete a test case automatically — every recommendation requires an explicit Accept or Decline from a user.

Where to Find Insights

Once enabled for your workspace, AI Insights appears in the project sidebar under the Analysis section, alongside Defects and Failure Clusters. Each recommendation in the list shows its type, confidence score, and a short reasoning summary; click a row to open the detail dialog with the full reasoning and, for Redundant recommendations, a side-by-side comparison with the similar case.

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See Also

• AI Features — overview of all AI capabilities in Qualflare