Data and State Model¶
Purpose¶
Explain how lifecycle state moves through governance, engineering, evidence, release, and readiness domains.
State Transition Layers¶
flowchart TD
Governance["Governance State"] --> Engineering["Engineering State"]
Engineering --> Evidence["Verification and Assurance State"]
Evidence --> Release["Release and Impact State"]
Release --> Operations["Operational Readiness State"]Ownership by State Layer¶
| State Layer | Owning Modules | Typical Records |
|---|---|---|
| governance | portfolio_mgmt, scope_mgmt | project/phase/scope allocations |
| engineering | sysdef_mgmt, sysarch_mgmt, interface_mgmt, requirements_mgmt | system entities, interfaces, requirement baselines |
| evidence | verification_validation_mgmt, safety_assurance | results, defects, assurance evidence |
| release | baseline_mgmt, impact_assessment | release packs, impact findings |
| readiness | ops_mgmt | readiness actions, milestones, dependencies |
State Consistency Rules¶
- upstream state changes require downstream re-validation
- release decisions should reference current evidence state
- trace link completeness is required for confident governance decisions
Practical Validation¶
docker compose run --rm app sh -c "pytest requirements_mgmt/tests verification_validation_mgmt/tests baseline_mgmt/tests impact_assessment/tests ops_mgmt/tests -v"
Data discipline
Update trace links as part of normal workflow rather than late-cycle cleanup.