Evidence and public accountability
Build the system right. Confirm it addresses the right need.
Verification checks the approved requirements; validation evaluates whether the integrated result is suitable for its intended users and context.
- System
- Evidence
- Public state
- Active governance system
- Purpose
- Define verification and validation controls
- Evidence boundary
- Evidence before claim
Orientation
One precise job inside the wider Continuum.
Passing a component test does not validate the whole application. Integration, usability, environment and failure behavior require their own evidence.
Parent domain: Research & Verification ↗
Evidence and limits
Ambition remains bounded by proof.
Public evidence pages distinguish established facts, current work, proposed programs, exploratory questions and future hypotheses. Missing evidence remains visible.
What must support advancement
Named source, method, owner, version and review date.
Acceptance criteria tied to the exact intended claim.
A recorded decision to advance, revise, hold or retire.
What this page does not claim
No architecture diagram substitutes for validation.
No planned study is described as a completed result.
No unsupported traction, partnership or performance statement.
Working model
The relationships that govern this domain.
Requirement
A measurable need with source and acceptance criteria.
Verification
Objective evidence that the implementation meets it.
Validation
Evidence that the integrated use is suitable and meaningful.
Release
A bounded decision with monitoring and rollback.
What the work contains
The working structure behind the public explanation.
Test levels
Unit, integration, system and use-context evidence remain distinct.
Failure testing
Degraded, missing, conflicting and adversarial conditions are included.
Regression
New capability must not silently weaken existing controls.
Evidence path
A controlled path from need to learning.
Connect each requirement to a method and owner.
Collect objective evidence against acceptance criteria.
Evaluate with representative users and environments.
Approve scope, monitor performance and retain rollback.
Continuum return
Useful learning strengthens more than one layer.
Evidence changes what Heartstone may claim, build, prioritize and carry into the next governed development cycle.