Interactive WCET Demos: Turn Vector’s RocqStat Outputs into Shareable HTML Explainers
Turn RocqStat WCET outputs into interactive, shareable HTML explainers for engineering reviews and certification in 2026.
Turn WCET outputs from RocqStat into interactive, shareable HTML explainers — fast
Pain point: your WCET reports are dense XML/JSON logs or static PDFs that engineers and certification stakeholders won't read. You need a zero-friction way to convert timing analysis outputs into interactive explainers that communicate safety margins, evidence links, and actionable conclusions.
In 2026 the demand for auditable, explainable timing artifacts has never been higher. With Vector's acquisition of RocqStat in January 2026 and the push to integrate timing analysis into end-to-end verification workflows, teams must deliver clear, shareable artifacts that non‑experts can inspect and auditors can rely on. This article shows how to convert RocqStat / VectorCAST WCET outputs into single-file HTML demos and embeddable widgets that are secure, CDN-ready, and easy to automate from CI.
Why interactive explainers matter in 2026
- Regulatory expectations (ISO 26262, DO-178C) increasingly require traceable evidence and clear artifacts for timing analysis.
- Toolchain convergence: Vector's integration of RocqStat into VectorCAST and other trends mean timing data will be generated continuously; static PDFs won't keep up.
- Cross‑discipline collaboration: hardware, software and systems engineers — plus product managers and safety auditors — need concise, interactive views that highlight risks and assumptions.
- CI-driven audits: automated generation of shareable artifacts (with links to source code and analysis version) is now a standard practice for safety-critical pipelines. Make sure these feeds connect into your broader operational systems and dashboards — see playbooks for resilient operational dashboards that ingest CI artifacts.
What you'll get from this guide
- Practical, step-by-step patterns to turn RocqStat WCET outputs into an interactive single-file HTML demo.
- Three templates: a single-file demo, a multi-page landing page, and an embeddable widget you can drop into docs or Confluence.
- CI/CD automation patterns (GitHub Actions example) to generate and publish artifacts to static hosting/CDN. If you need edge-aware hosting strategies, consult edge caching guidance like the Edge Caching Playbook.
- Security and certification tips: sanitizing outputs, signing artifacts, and access controls.
Overview: from RocqStat output to a shareable HTML explainer
At a high level the pipeline looks like this:
- Run RocqStat and export WCET data (JSON/XML/HTML).
- Normalize the output into a small JSON schema for the viewer (paths, WCET per path, confidence, evidence links).
- Embed the data into a standalone HTML file with interactive visualizations and annotations.
- Host the file on a static hosting service or CDN and share the link (or embed via iframe/script).
- Automate via CI so every commit or release generates a fresh, versioned explainer.
Why single-file HTML?
Single-file static HTML (all CSS/JS inlined or referenced from a CDN) is the fastest way to produce a shareable, audit-friendly artifact. It avoids complex hosting configuration, works offline for audits, and is easy to sign or archive with the rest of the release artifacts.
Template 1: Single-file interactive WCET demo
Use case: quick hub for an engineering review or safety meeting. One file you can email or host publicly for demonstration.
Key UX elements to include
- Summary card with WCET, P95, average, analysis timestamp, tool and version.
- Interactive timeline or bar chart showing WCET per path and per function.
- Threshold toggles that overlay safe/unsafe zones (e.g., MCU deadline).
- Evidence links that open the exact RocqStat trace, source file, or VectorCAST test case.
- Annotations for risky paths and mitigations (developer comments).
Minimal file structure (single HTML)
<!-- wcet-demo.html -->
<!doctype html>
<html lang='en'>
<head>
<meta charset='utf-8'>
<meta name='viewport' content='width=device-width,initial-scale=1'>
<title>WCET Demo</title>
<link rel='stylesheet' href='https://unpkg.com/spectre.css/dist/spectre.min.css'>
<script src='https://cdn.jsdelivr.net/npm/vega-lite@5'></script>
</head>
<body>
<div id='app'></div>
<script>/* Inline data and viewer logic here */</script>
</body>
</html>
Example: embed RocqStat data and a Vega-Lite chart
Below is a condensed example pattern. It keeps everything in one file and uses Vega-Lite for compact, performant visualizations.
<script>
// 1) RocqStat-normalized data (example)
const wcetData = {
meta: {
tool: 'RocqStat',
toolVersion: '2026.1',
timestamp: '2026-01-08T12:34:56Z',
analysisId: 'rcq-2026-001'
},
paths: [
{ id: 'P1', wcet_us: 1200, mean_us: 850, confidence: 0.995, evidence: 'trace://...#P1' },
{ id: 'P2', wcet_us: 950, mean_us: 600, confidence: 0.990, evidence: 'trace://...#P2' }
]
};
// 2) Vega-Lite spec for a simple bar chart
const spec = {
'width': 700,
'height': 240,
'data': { 'values': wcetData.paths },
'mark': 'bar',
'encoding': {
'x': { 'field': 'id', 'type': 'ordinal', 'axis': { 'title': 'Path' } },
'y': { 'field': 'wcet_us', 'type': 'quantitative', 'axis': { 'title': 'WCET (μs)' } },
'color': { 'field': 'wcet_us', 'type': 'quantitative' }
}
};
vlEmbed('#app', spec); // assumes a tiny wrapper to mount the chart
</script>
Actionable tip: normalize RocqStat outputs to a compact JSON with only the fields your explainer needs: id, wcet, mean/jitter, confidence, evidenceURL. That makes the viewer code tiny and easy to audit. If you’re formalizing this normalization at scale, hiring or training data engineering skills focused on efficient schemas helps.
Template 2: Multi-page landing for stakeholder reviews
Use case: deliver a branded landing page for certification evidence that aggregates multiple component analyses, change history and links to raw artifacts.
Core pages
- Overview — executive summary and pass/fail indicators.
- Component pages — per-component WCET interactive explainer.
- Trace viewer — links to raw RocqStat traces (hosted securely).
- History & Versions — build IDs, tool versions, and change logs.
Hosting and archival considerations
- Archive every artifact with the release (signed ZIP or artifact repository) so auditors can reproduce the analysis run that produced the explainer. If you need cloud sovereignty or compliance-aware hosting, review migration playbooks such as FedRAMP and compliance guides to understand enterprise constraints.
- Version your explainers — include analysisId, commit hash, and RocqStat/VectorCAST versions on every page.
- Provide a printable PDF snapshot for regulators who prefer traditional documents; generate PDFs from the rendered HTML during CI.
Template 3: Embeddable widget (for docs and reporting)
Use case: embed a concise WCET widget into Confluence pages, Jira tickets, or internal dashboards so non‑engineers can see top-line results without leaving context.
Widget form factors
- Inline iframe (simple, isolated CSS/JS).
- Script tag that mounts a shadow DOM widget (smaller footprint, SEO neutral) — a pattern common in composable UX pipelines.
- API-backed widget that fetches normalized JSON from a versioned endpoint and renders client-side.
Iframe example (drop-in)
<iframe src='https://example.cdn/static/wcet-widget/rcq-2026-001.html' width='480' height='220' title='WCET Summary' style='border:0'></iframe>
Security note
For private projects, do not expose raw traces inside public widgets. Use short‑lived signed URLs or host the widget behind authentication. Consider a CDN that supports signed tokens and edge authentication. For advanced edge-auth strategies and caching, consult the edge caching playbook and integrate per-request auth into the CDN layer.
CI/CD pattern: auto-generate explainers with GitHub Actions
Automate the entire flow so every merge or release produces a fresh, versioned explainer that you can link to from release notes.
High-level steps
- Run unit and integration tests (VectorCAST).
- Run RocqStat WCET analysis as part of the pipeline; export machine-readable JSON.
- Run a small script that normalizes the RocqStat output into your viewer schema. Adopt ethical and secure data practices when building normalization pipelines — see guidance on ethical data pipelines.
- Inject the data into your single-file template (or produce a minified bundle).
- Publish the artifact to static hosting (GitHub Pages, Netlify, Vercel, or a CDN-backed file host). When you need edge previews and tokenized short links for auditors, combine CDN hosting with edge auth described in the Edge Caching Playbook.
- Post a short link into the PR or release notes (and optionally create a preview comment for stakeholders).
Example GitHub Actions snippet (conceptual)
name: Generate WCET Explainer
on: [push]
jobs:
wcet:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Run VectorCAST + RocqStat
run: ./run_vectorcast_and_rocqstat.sh --output out/rocq.json
- name: Normalize RocqStat
run: node tools/normalize-rocq.js out/rocq.json out/explainer/data.json
- name: Build single-file explainer
run: node tools/build-explainer.js out/explainer --out out/wcet-demo.html
- name: Publish to Pages
uses: peaceiris/actions-gh-pages@v3
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
publish_dir: out/
Actionable tip: include the analysisId and commit hash in the filename or path (eg. wcet-rcq-2026-001-
Visualization patterns tailored for WCET explainers
Design visualizations to communicate uncertainty, sources of evidence, and operational impact. Here are patterns that work well:
- Bar charts for per-path WCET with color-coded safety zones.
- Strip plots or violin plots to show distribution across runs (jitter).
- Timeline traces for path execution order and hotspots.
- Drill-down tables where each path links to source lines and RocqStat trace snippets.
- Confidence badges (e.g., 99.5%) and toolchain provenance so auditors understand the evidence's strength.
Practical considerations: security, IP, and certification
Interactive explainers are useful, but you must guard sensitive details:
- Mask or strip IP-sensitive code snippets before publishing public demos.
- Use signed URLs or short-lived tokens for anything that reveals internal traces. For defensive techniques to detect and mitigate automated attacks on identity systems, refer to work on predictive AI for identity.
- Embed provenance data (tool versions, config) in the explainer — auditors want it.
- Understand archival rules in your domain; store artifacts with release bundles so you can reproduce the analysis later. For broader migration considerations, see enterprise migration playbooks such as Gmail exit strategy guidance which covers CI/CD and alert continuity.
2026 trends and the future of timing explainers
Late 2025 and early 2026 saw clear momentum: vendors are embedding timing analysis into automated verification pipelines and prioritizing explainability. Vector's acquisition of RocqStat is a signal that timing tools will be first-class citizens in verification suites.
"Timing safety is becoming a critical capability" — Vector (acquisition statement, Jan 2026)
Expect these trends to accelerate:
- Standardized WCET JSON schemas: an industry push toward common schemas to enable the same viewers to consume outputs from different tools.
- Edge-powered previews: CDN-backed short links with per-request authentication for auditors. If you’re integrating previews with low-latency media or live analysis feeds, see patterns from hybrid studio ops work on edge encoding and monitoring.
- AI-assisted annotation: tools that suggest root causes or highlight risky paths automatically from timing traces.
- Deeper toolchain ties: built-in links from timing explainers back into VectorCAST test cases and source control for immediate remediation workflows. For realtime integration ideas, examine WebRTC + Firebase lessons in run realtime workrooms without Meta.
Checklist before you share a WCET explainer
- Include tool name, exact version, and analysis timestamp (provenance).
- Normalize and minimize the dataset to the fields needed for the explainer.
- Sanitize traces — remove any secrets or proprietary APIs.
- Sign or version the artifact; store alongside release artifacts.
- Provide direct evidence links so reviewers can validate claims.
- Add an audit trail: who ran the analysis and which configuration was used.
Real-world example (concise case study)
Context: a Tier-1 supplier integrated RocqStat outputs into a release pipeline in Q4 2025. They automated extraction of per-path WCET, mean jitter and evidence links, and produced single-file explainers for every release. Results:
- Engineering review cycles shortened by 30% because stakeholders could interactively explore failing paths.
- Certification meeting time reduced because auditors were given immutable, traceable artifacts rather than ad-hoc reports.
- Faster remediation — each widget linked to the exact test case and source file so developers reproduced and fixed the worst paths immediately.
Advanced strategies
1) Live analysis previews in PRs
Run RocqStat on the branch, generate the explainer and post a preview link in the PR. Stakeholders and CI gates can see timing regressions before merging. Combine previews with edge-powered short links and preview infra described in the Edge Caching Playbook.
2) Comparison mode
Produce a diff explainer that overlays baseline and current WCET per path, highlighting regressions with heatmap colors.
3) Evidence-first views
Make the default view show the evidence for the worst path (trace snippet, call tree), because that is what auditors and reviewers ask for first.
Actionable takeaways
- Normalize outputs: transform RocqStat data into a compact JSON schema for the viewer.
- Keep explainers single-file for demos: simplifies hosting, archiving, and auditing.
- Automate via CI: generate, version and publish explainers automatically on each build or PR. Use resilient CI-to-dashboard integrations described in operational dashboard playbooks.
- Protect IP: sanitize outputs and use signed URLs for private artifacts. For enterprise-scale identity protections, consult guidance like using predictive AI to detect automated attacks.
- Show provenance: tool versions, analysisId and commit hashes are mandatory for certification evidence.
Next steps & call to action
Start small: take one RocqStat output JSON and build a single-file HTML demo with a bar chart and evidence links. Automate it into your CI and add a preview link to your next PR.
Want a jumpstart? Clone the template repo with three ready-to-use explainer templates (single-file demo, landing page, and embeddable widget), plus a sample GitHub Actions workflow and normalization script. Host the generated file on your static host or try a CDN-backed single-file host to share preview links with stakeholders instantly.
Make your WCET results visible, explainable, and auditable — not just another file on disk.
Ready to convert your RocqStat outputs into shareable explainers? Download the template repo, or contact our team for a hands-on workshop that integrates explainers into your VectorCAST/RocqStat pipeline. If you need help designing the edge-hosted preview or low-latency embeds for demos, see resources on hybrid studio ops and mobile studio essentials.
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