canvas-heal 0.2.0

Semantic intent-based self-healing test locators for QE and test automation

CANVAS

Context-Aware Navigation and Visual Anchoring System for Selectors

An open source research prototype for semantic intent-based self-healing test locators, built for the QE and test automation community.

Why CANVAS

Existing self-healing tools use attribute-based matching — CSS selectors, XPath, element IDs, class names. These break whenever a UI undergoes structural redesign, even when the element's function is unchanged.

CANVAS takes a different approach: semantic intent anchoring. At record time it encodes what an element does — its role, accessible label, workflow position, and surrounding context — into a dense vector using a local sentence-transformers model. At runtime it embeds live DOM candidates and finds the nearest semantic match, then gates the decision:

• Auto-heal if confidence is high enough
• Request human confirmation if confidence is in a grey zone
• Fail explicitly if no confident match exists

This means a "Submit Order" button that moves from a sidebar to a modal, or gets its ID changed from #btn-submit to #cta-primary, can still be found — because its intent is preserved even when its address is not.

Status

All 4 phases complete. The core pipeline (descriptor, embedder, confidence-gated resolver) is implemented and tested, and the adversarial test suite covering DOM restructuring, attribute churn, semantic paraphrase, and false-positive detection is in place — all tests passing.

Roadmap

Phase	Name	Status
1	Semantic Element Descriptor	Complete
2	Intent Embedding	Complete
3	Confidence-Gated Resolver	Complete
4	Adversarial Testing	Complete

Structure

canvas/         — core source code
  descriptor.py — DOM element descriptor extraction
  embedder.py   — sentence-transformers embedding pipeline
  resolver.py   — confidence-gated semantic resolver + SQLite intent store
tests/          — unit tests and adversarial test scenarios
docs/           — technical documentation

Quick Start

pip install -r requirements.txt
python -m playwright install chromium
python -m pytest tests/ -v

Contributing

CANVAS is in early prototype stage. Community feedback, issues, and pull requests are welcome once Phase 4 (adversarial testing) is complete. Watch the repo or open a discussion if you want to get involved earlier.

License

MIT — see LICENSE