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Requirements Traceability Matrix (RTM): Template and an In-Code Alternative
A requirements traceability matrix (RTM) is a table that maps each requirement to the test cases that verify it, along with their latest result and any open defects, so you can prove every requirement is covered before a release. Most teams keep it in a spreadsheet, which works for a few dozen requirements and goes stale quickly beyond that.
RTM template
Copy this into a spreadsheet or a Markdown file. One row per requirement; add a column per release if you need history.
| Req ID | Requirement | Priority | Test case IDs | Last result | Open defects | Owner |
|---|---|---|---|---|---|---|
| REQ-101 | User can reset password by email | High | TC-12, TC-13 | Pass | None | QA |
| REQ-102 | Checkout supports 3D Secure cards | High | TC-40 | Fail | BUG-311 | Payments |
| REQ-103 | Admin can export audit log as CSV | Medium | (none yet) | Not covered | None | Platform |
The rows that matter most are the ones like REQ-103: a requirement with no linked test. The rest of this page covers why keeping this table accurate by hand breaks down, and how linking scenarios to tests in code keeps the same matrix live.
In brief: Traditional traceability lives in external tools disconnected from tests; TestChimp embeds links in Playwright code and markdown plans agents and reviewers see every PR.
Traditional requirement traceability is usually an integration project:
- user stories in an issue tracker
- test cases in a test management tool (or spreadsheets)
- mappings maintained manually
- execution results in CI dashboards
The team then tries to stitch everything together into a single view of “coverage”.
TestChimp flips the model: traceability is designed to be native, in-code, and folder-aware.
The traditional approach (and why it fails over time)
Multiple sources of truth
When different tools own different parts of the truth, people spend time reconciling:
- what the product is supposed to do
- what tests exist
- what’s covered
- what’s currently passing
Manual mapping (spreadsheets don’t survive reality)
Even when teams start with good intentions, manual mapping inevitably goes stale:
- new stories appear
- scenarios change
- tests refactor
- ownership shifts
Flat structures block rollups
Without hierarchical organization, answering simple questions becomes hard:
- “what’s the coverage for checkout?”
- “which team owns the biggest coverage gaps?”
TestChimp’s approach: scenario linking in code + structured planning folders
Link tests to scenarios where tests live (in code)
Instead of maintaining a separate mapping system, you link from the test using a comment (example shown in docs):
Keep user stories and scenarios in folders (so rollups are automatic)
When planning artifacts are organized by folders (feature/journey/team), insights can roll up at any level—without spreadsheets.
UX bug traceability is a first-class concept (not an afterthought)
Most traditional traceability stacks don’t handle “UX bug traceability” well at all. Exploratory findings become a detached list of issues with weak context.
TestChimp tags exploratory findings to screen + screen-state and links them through SmartTests to the underlying scenarios and user stories:
Side-by-side comparison
| Question you want answered | Traditional stitched approach | TestChimp |
|---|---|---|
| “What’s our coverage for checkout?” | Requires manual mapping + fragile rollups | Folder rollups + linked scenarios |
| “Which scenarios are high priority and uncovered?” | Spreadsheet/workflow-heavy | Filters + built-in insights |
| “Which UX bugs affect onboarding?” | Usually not traceable | Findings → screen-state → scenario/story rollups |
| “What changed in our test plan last week?” | Vendor audit logs | Git diffs/PR review (if using planning-as-code) |
Common questions teams ask (when coverage reporting is a mess)
How do we know what’s actually covered before a release?
It’s worth it when you need to make release decisions based on:
- what’s covered
- what’s currently passing
- what’s missing at a level of granularity that matches how your product is organized.
How do we link tests to requirements without maintaining spreadsheets?
Because the link lives next to the thing that changes most often: test code. Refactors don’t require a second system to stay in sync.
How do we connect UX bugs back to user journeys?
By tagging findings at screen-state level and inheriting the traceability chain through SmartTests:
Related QA guides
- Playwright alternatives compared
- Cypress vs Playwright
- Smoke vs regression testing
- Stripe test cards for Playwright E2E
- Test plan template in Markdown
Citations and further reading
FAQ
Does this satisfy audit needs?
Linked scenarios with execution history in QA Intel provide evidence; export as needed for compliance programs.
Multiple scenarios per test?
Yes—multiple scenario annotations are supported; insights roll up per linked scenario.
How do explorations extend traceability?
UX bugs on SmartTest journeys attach to the same scenarios and screen-states functional tests cover.