Transparent Self-Healing

Self-healing that shows its work

Most brittle suites fail on harmless UI movement. Zerocheck uses semantic resolution, accessibility data, cached selectors, and confidence checks, then fails with evidence when it cannot act confidently.

Who this is for

Role
Senior engineer or QA lead
Company
Teams evaluating or already using AI testing tools (Mabl, Testim, Momentic)
Trigger
AI tool healed a test that silently masked a real bug. Or: team disabled self-healing because they couldn't trust it.

The pain is real

“The same pattern kept repeating itself: a harmless-looking UI change, a merge, and then a failing test in CI.”

monday.com Engineeringsource

“We completely lost trust in our build, and red builds no longer meant anything.”

ThoughtWorks Engineeringsource

46% of developers distrust AI testing accuracy

30% of GenAI projects abandoned after POC due to trust issues

Testim users report 'tests do not heal themselves under any circumstance'

Why this stays unsolved

Selector-based healing (Mabl, Testim, Katalon) guesses alternative selectors when the original breaks. The guess can latch onto the wrong element, creating false passes that mask real bugs.

Intent-based tools (Momentic, testRigor) are more resilient but opaque. Engineers describe them as a 'black box' when they cannot inspect why the tool chose a specific action.

Engineers need evidence for passes and failures. Low-confidence behavior should fail with context rather than silently pass.

The workflow today vs. with Zerocheck

Without Zerocheck

UI redesign ships. Mabl 'heals' 12 tests by finding alternative selectors. 10 heal correctly. 2 latch onto the wrong element and now validate a different flow entirely. Tests pass. Bug ships to production. Team discovers it from a customer report 3 days later.

With Zerocheck

Same redesign. Zerocheck uses semantic resolution, accessibility data, cached selectors, and confidence checks. High-confidence interactions continue; low-confidence interactions fail with screenshots and step traces instead of silently passing.

How it works

1

Tests describe browser intent instead of selectors

2

Visual interaction uses the rendered UI

3

Low-confidence interactions fail with screenshots and step traces

4

Low-confidence changes fail-closed instead of silently passing

Self-healing that shows its work

Resilience engineers can inspect. Low-confidence actions fail with evidence instead of silently passing.

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