01
Functional correctness
The system handles expected rules, states, permissions, exceptions, and outcomes.
Quality assurance
Quality evaluated across the whole service.
A risk-based assurance model for product behaviour, accessibility, security, data, integration, performance, resilience, maintainability, and operation.
What this means
Testing is essential, but quality is broader.
Quality begins with whether the right problem and acceptance conditions are understood. Assurance then combines prevention, automated and exploratory testing, review, observation, and operational learning.
- Risk drives depth and priority
- Automation supports repeatability
- Humans explore ambiguity and use
- Production evidence informs improvement
Quality dimensions
02
User experience and accessibility
Critical journeys are understandable, usable, responsive, keyboard operable, and compatible with assistive technology expectations.
03
Integration and data
Contracts, mappings, validation, ordering, duplication, reconciliation, failure, lineage, and recovery are exercised.
04
Security and privacy
Access, abuse cases, sensitive information, dependencies, configuration, logging, and relevant verification requirements are assessed.
05
Performance and resilience
Important loads, limits, timeouts, failure modes, degradation, recovery, and capacity assumptions are examined.
06
Maintainability and operability
Code clarity, modularity, tests, documentation, diagnostics, deployment, support, and change safety are reviewed.
Assurance gates
01
Ready to build
Critical ambiguity, acceptance, dependencies, data, architecture, and risk are understood enough to proceed.
02
Ready to integrate
Interfaces, environments, test data, ownership, compatibility, and failure handling are prepared.
03
Ready to release
Acceptance evidence, unresolved risk, deployment, rollback, support, security, and operational readiness are reviewed.
04
Ready to close
Ownership, documentation, remaining work, known limits, support, and learning are explicit.
Evidence standard
No finite test set proves that software is defect-free or secure. Algoza uses proportionate assurance to reduce uncertainty, make residual risk visible, and support an informed release decision.
Related assurance
Inspect the connected practices
Engineering overview
Return to the public engineering principles.
View detailsTechnology approach
How technologies are selected for the workload and long-term owner.
View detailsDevelopment standards
Source, review, testing, documentation, and release expectations.
View detailsArchitecture standards
How boundaries, trade-offs, integration, data, and operations are decided.
View detailsBring the requirement and its constraints.
Algoza will clarify the evidence, controls, decisions, and delivery route appropriate to the engagement.