Semantic Explorer: See Your QA Knowledge by Meaning
TL;DR: Existing QA tooling lets you follow explicit links only—story → ticket → test case → run, if someone remembered to wire them. Anything related by meaning but not linked stays invisible. TestChimp consolidates stories, scenarios, SmartTests, issues, and TrueCoverage events into a single embedding space. Semantic Explorer (in QA Brain) projects that space onto a 2D map so you can navigate neighborhoods, identify clusters, and surface related entities by conceptual similarity—then link near-misses, mark lookalikes distinct, or raise cleanup work from the sidebar.
Explicit links aren’t enough
Last week we shipped InfiniTrace—walk the structural edges of your QA graph board by board.
That answers:
“What is linked to this story / test / event?”
Most of the industry stops there. Jira, TestRail, CI folders, coverage tools: if the edge wasn’t created, the relationship doesn’t exist. Keyword search helps only when titles share tokens. Paraphrases, cross-type near-misses, and quiet duplicates fall through the cracks—especially when agents author plans and tests at speed.
The sibling question traditional tools never answer:
“What looks like this—even if nobody linked it yet?”
Or:
“Which entities belong to the same conceptual neighborhood?”
Those need meaning, not another list sorted by updated-at.
TestChimp already maps every QA entity into a shared embedding space—beyond explicit links, into semantic proximity. Semantic Explorer is the surface that lets you see and navigate that space, next to InfiniTrace in QA Brain.
Introducing Semantic Explorer
Semantic Explorer is a spatial map of your project’s QA knowledge—laid out by conceptual similarity.
Open QA Brain → Semantic Explorer tab (/brain?tab=semantic-explorer).
- Add the entity types you care about—Stories, Scenarios, Tests, Issues, Events
- Nodes land on a UMAP canvas: high-dimensional embeddings projected so local neighborhoods reflect cosine similarity
- Pan, zoom, filter, search (
#US-12, titles, …) - Click a node → the detail sidebar fills with cosine-ranked peers
- Link, mark distinct, create a duplicate-cleanup issue, or open details—in place
Deep links encode types, filters, border modes, and selection in ?locator= (with tab=semantic-explorer). “Look at this cluster” is a URL, not a screenshot.
Docs: Semantic Explorer.
What you can actually do with it
A few use cases that show why a meaning map beats link-chasing alone:
Plan neighborhoods with live automation health
Load Stories + Scenarios + Tests, paint test borders with latest execution status, and scan the map: requirement clusters with failing automation sitting right next to the plans they should cover—without walking each story’s link tree.
Duplicate / lookalike issue clusters
Load Issues alone with severity borders. Twin bugs filed weeks apart with different titles collapse into neighborhoods. Open the sidebar, mark distinct where needed, or file cleanup when it’s a true duplicate.
Close semantic coverage gaps
Put Scenarios + Tests (or Events + Tests) on one canvas. Select an unlinked scenario or hot TrueCoverage event → Close by tests ranks peers by cosine similarity → Link the near-miss that should have been wired months ago.
Requirement overlap before you plan more
Plot Stories + Scenarios. Dense blobs often mean one idea wearing three titles—or a story that needs a scenario split—before you (or an agent) author more surface area.
TrueCoverage hotspots vs automation islands
Add Events with has test coverage borders. Uncovered events that sit next to well-covered automation clusters are high-ROI gaps: instrumentation, missing emits, or a test that almost covers the behaviour.
We already open-sourced the suite-side cousin—Semantic Graph for Playwright folders. Semantic Explorer brings the same instinct into the product graph: not just tests vs tests, but cross-type meaning across your QA entities.
| Surface | Primary question |
|---|---|
| InfiniTrace | What is structurally linked—and what’s a semantic near-miss on the next board? |
| Semantic Explorer | What clusters by meaning—and what should I link or dedupe right here? |
Same underlying entities. Same link rules. Two complementary ways to see the graph.
The sidebar is where the work happens
The canvas orients you. The detail sidebar decides.
Select a node and you get accordion lists ranked by cosine similarity—not by how close the dots look after UMAP squashed the space into 2D (those can disagree; trust the scores for linking).
| Section | Job |
|---|---|
| Similar <same type> | Spot duplicates and over-similar peers |
| Close by <other type> | Cross-type near-misses among types on the canvas |
Tune a cosine cutoff per source→target pair. Raise it when you’re hunting true duplicates; lower it when you’re fishing for coverage gaps.
Then act:
- Link — same model as InfiniTrace (including story↔scenario mappings and
// @Scenarioinjection for scenario↔test) - Mark as distinct — teach the system “similar ≠ duplicate”
- Create issue for duplicate — turn a lookalike pair into cleanup work
- View details — read-only modal, then jump to the full page when you need to edit
If a card that looks nearby on the map falls below your cutoff, that’s not a bug—that’s the difference between a 2D sketch and embedding space. The sidebar keeps you honest.
Borders that mean something
Pretty clusters aren’t enough. You need health overlays.
Per type, paint node borders with operational signal:
- Latest execution status on tests / scenarios
- Priority / severity and due status on stories, scenarios, issues
- Has linked test on scenarios
- Has test coverage on TrueCoverage events
Drop Stories + Scenarios + Tests with execution status on the tests, and the map stops being art: requirement neighborhoods with live automation health.
Or load Issues alone with severity borders—and watch lookalike bugs collapse into clusters you can actually triage.
Combine that with folder filters and status chips for sharper triage: failing tests next to the stories they should cover, severity islands of duplicate bugs, uncovered hot events next to automation islands.
From links to neighborhoods
Dashboards tell you what’s trending.
Atlas tells you where in the product structure something lives.
TrueCoverage tells you what real users do versus what tests cover.
InfiniTrace tells you how the pieces connect via explicit edges.
Semantic Explorer tells you what belongs together by meaning—even when the link was never created—and where quiet duplicates and near-misses still hide.
That’s the difference between knowing coverage is “82%” and seeing the blob of scenarios that are really one idea wearing three costumes.
Go open QA Brain → Semantic Explorer. Load Stories, Scenarios, and Tests with execution status—or Issues with severity—and click something you think is unique. If the sidebar shows a 90% twin you forgot existed… good. That’s the product working.
Full walkthrough: Semantic Explorer docs.
Pair it with: InfiniTrace.