app-baseline

Automated baseline verification compares your current app state against an approved baseline using deterministic Python-based checks to surface drift, ensuring only reviewed changes are promoted. It requires a review ledger and explicit approval signature to finalize updates.

A signed baseline workflow enforces human signature approval before promoting a new baseline, ensuring only reviewed changes pass. You need it for CI verification, release verification, and QA closeout to detect drift and control the baseline lifecycle in large codebases.

You lock an app baseline by running a deterministic comparison against the approved state, logging decisions in a review ledger, and finalizing the update with an explicit approval signature. This prevents unauthorized baseline promotion and flags drift.

Yes, baseline drift review applies to QA closeout workflows by comparing the current app state to an approved baseline, flagging drift, and requiring a human signature before finalizing. This ensures large applications remain consistent and only approved changes are promoted.

Yes, baseline verification requires a review ledger to track model decisions and structure the approval workflow before updating the baseline. This ledger ensures explicit human signatures are recorded to finalize and promote new approved states.

The best way to prevent unapproved promotions is applying deterministic baseline verification to flag drift, logging decisions in a review ledger, and mandating an explicit human signature before updating the baseline. This locks the CI-CD pipeline to only approved changes.