Traceability Made Simple
A lightweight trace chain that stays practical—plus how AI drafting can help without weakening reviewability or evidence expectations.
Key takeaways
Designed to be practical, reviewable, and easy to share across teams.
A common aerospace trace structure
A common aerospace pattern is not just Requirement → Test. It is a layered trace that connects system intent down to implementation-level verification artifacts.
- System Requirement: captures the system-level intent or behavior.
- HLR: translates that intent into software or subsystem behavior.
- LLR: adds implementation-level detail that can be verified directly.
- Verification: links each requirement level to cases, procedures, and measurable expected results.
- Evidence: logs, reports, measurements, or execution records that prove the result.
Keeping traceability intact with AI drafting
AI can help draft the structure consistently, but the workflow still needs explicit links and engineering review.
Tiny Example
A small structured draft is often easier to review than a blank page.
Typical aerospace trace SYS-001 → HLR-014 → LLR-014.3 LLR-014.3 → TC-22 / PROC-22 PROC-22 → Expected Results Expected Results → Execution Record / Evidence
Traceable draft System Req: SYS-001 HLR: HLR-014 LLR: LLR-014.3 Case: Verify SAFE mode entry on fault F Procedure: Inject fault, record timestamps Evidence: execution log + mode transition record
FAQ
What’s the hardest part of traceability?
Keeping requirement links and evidence expectations explicit and consistent across layers.
How do you handle one requirement to many tests?
Treat the higher-level requirement as a parent and list the cases and procedures that collectively satisfy it.
Can AI generate trace links automatically?
It can draft them, but enforcement and review are still needed to keep links accurate.
Follow along as we build
We share practical AI examples for test cases, procedures, coverage, and traceability—built for aerospace and regulated teams.