embeddedverificationCI/CD

Integrating RocqStat with VectorCAST: A Practical Guide for Embedded Timing Analysis

wwebscraper

2026-02-04

10 min read

Shift WCET left: practical steps to integrate RocqStat into VectorCAST and gate timing in CI for real-time embedded systems.

Hook: Stop late-stage timing surprises — bring WCET into CI

Timing regressions and unpredictable worst-case execution times (WCET) are a top cause of late-stage rework in embedded projects. If your team is still running WCET analysis as an occasional offline activity, you risk missing regressions introduced by micro-optimizations, scheduler tweaks, or compiler updates. Integrating RocqStat into your VectorCAST toolchain lets you shift timing analysis left: automated, repeatable, and actionable within CI/CD pipelines so timing becomes a first-class gate in your release process.

Why this matters in 2026

In late 2025 and early 2026 we've seen two reinforcing trends: increased regulatory scrutiny for timing in safety-critical domains (automotive ADAS, industrial control and aerospace), and consolidation in tooling — most notably Vector Informatik's January 2026 acquisition of StatInf's RocqStat technology. Vector has signaled a medium-term plan to embed RocqStat into the VectorCAST environment to create a unified testing and timing analysis flow. That means tighter integration points and richer automation options for teams building real-time systems.

What this unified stack delivers

Measurement-driven WCET inside test runs — produce pWCET estimates from the same tests that validate functionality.
Trace and metric continuity— functional failures and timing violations reported together.
CI gating for timing— fail builds on regressions in worst-case estimates, not just unit test failures.

High-level integration strategy

There are three logical layers you must integrate: test orchestration (VectorCAST), instrumentation and trace capture, and statistical WCET analysis (RocqStat). The practical goal is to automate: run tests → capture traces → run RocqStat → compare to requirements → gate CI.

Step 1 — Define timing requirements and acceptance criteria

Before automating, codify the acceptance rules you'll enforce in CI. Examples:

Task X pWCET95 (probabilistic bound at 1e-9 violation probability) must be < 1.5 ms.
End-to-end latency for control loop Y must be < 10 ms with 99.999% confidence.
No more than a 5% increase in pWCET compared to baseline across major compiler/toolchain updates.

Step 2 — Instrument tests in VectorCAST

VectorCAST already automates unit, integration and system tests. To collect timing you will:

Enable high-resolution timers or tracing on the target (ETM/ETR for ARM, hardware cycle counters, or OS trace points).
Create a VectorCAST test configuration that runs the timing-sensitive test vectors repeatedly and deterministically.
Capture events with a lightweight measurement agent that exports standardized trace files (CSV or JSON time-stamped events).

Key practices:

Isolate the core where possible (pin threads/affinities, disable unused interrupts) to reduce noise.
Control power management (disable DVFS, set fixed clock frequencies) to avoid variance from frequency scaling.
Run cache warm-up sequences before measurement and collect warm-up logs as part of the trace package.

Step 3 — Export traces to RocqStat

VectorCAST should be configured to export timing artifacts at the end of each test run. With Vector’s announced roadmap, expect native exporters from VectorCAST to RocqStat, but you can start now with an adapter that:

Collects VectorCAST test run identifiers and artifact paths via the VectorCAST API or file output.
Converts target-specific trace formats to the RocqStat-compatible CSV/JSON format (timestamp, event-id, call-stack-id).
Uploads the artifact bundle to your analysis host (local server, dedicated analysis VM, or cloud storage).

Step 4 — Run RocqStat and capture pWCET

RocqStat is a measurement-based, statistical timing analysis tool that estimates pWCET from real execution traces and controlled stress testing. In CI you’ll automate a command-line invocation. An illustrative (adaptable) example:

# Example (illustrative) wrapper to run RocqStat on trace bundle
ro cqstat analyze --input traces/run_12345 --function task_x --confidence 1e-9 --output reports/run_12345_pwcet.json

Notes:

Set the target confidence (violation probability) per your standards — automotive teams often target 1e-9 or similar for safety-critical paths.
Include test metadata (compiler version, CPU model, OS kernel) in output to support reproducibility.

Step 5 — Enforce gates in CI

After RocqStat produces pWCET estimates, compare the results against your acceptance criteria and implement gating logic. Typical CI integrations:

Convert pWCET output to JUnit or SARIF and upload to your CI server to make failures visible in the pipeline.
Post summary messages to Slack/MS Teams with build status and links to detailed reports.
Store artifacts to object storage (S3) for audit and traceability.

Example: GitHub Actions workflow

The following YAML is a concrete starting point. It assumes you have a measurement agent that can run tests on a hardware rack and stream artifacts back to the runner. Adapt for GitLab or Jenkins.

name: CI-Timing
on: [push, pull_request]

jobs:
  vectorcast-rocqstat:
    runs-on: ubuntu-22.04
    steps:
      - name: Checkout
        uses: actions/checkout@v4

      - name: Build and run VectorCAST tests on target
        run: |
          ./scripts/deploy_and_run_vectorcast.sh --target rack1 --suite TimingSuite --out artifacts/run_12345

      - name: Retrieve traces
        run: |
          ./scripts/pull_traces.sh --target rack1 --output traces/run_12345

      - name: Run RocqStat
        run: |
          docker run --rm -v ${{ github.workspace }}/traces:/data rocqstat:latest \
            rocqstat analyze --input /data/run_12345 --function task_x --confidence 1e-9 --output /data/report.json

      - name: Evaluate thresholds
        run: |
          python3 ./scripts/check_pwcet.py traces/run_12345/report.json --threshold 1.5

That final script would exit non-zero to fail the job if pWCET exceeds threshold — turning timing analysis into a hard CI gate.

Handling common embedded complexities

Embedded systems introduce special challenges for timing analysis. Here’s how to address them when combining VectorCAST and RocqStat:

Multicore interference

Multicore timing interference is one of the hardest problems in WCET. Practical approaches:

Prefer isolation for critical tasks: pin high-criticality threads to dedicated cores during measurement.
When co-scheduling is unavoidable, create representative background workloads and include them as part of the measurement profile so RocqStat can quantify interference effects.
Use platform-level QoS (cache partitioning, memory bandwidth throttling) to reduce non-determinism and repeatability variance.

Interrupts and asynchronous events

Interrupts create long tails in timing distributions. Mitigate by:

Logging interrupt activity and correlating interrupts with timing spikes in the trace.
Using targeted stress tests that inject interrupts at controlled rates to quantify their impact.
Separating hard real-time paths from soft real-time ones in your analysis scope.

Toolchain and compiler changes

Compiler optimizations, link-time code generation and microcode updates can change timing characteristics. Make sure your CI does:

Record toolchain versions and hardware microcode as build artifacts.
Run a focused timing test garden when a compiler or toolchain change is detected.
Automate regression thresholds — allow small variation but flag systemic increases for triage.

Practical recipes and scripts

Below are short example scripts to standardize the collection and analysis flow. Use these as templates.

Minimal trace exporter (Python)

#!/usr/bin/env python3
# run_exporter.py - collect vectorcast artifacts and normalize for RocqStat
import json, shutil, sys

run_dir = sys.argv[1]
out_file = sys.argv[2]

# Example: copy VectorCAST timing logs to a single normalized file
with open(f"{run_dir}/vc_timing.log") as f:
    events = []
    for line in f:
        ts, evt = line.strip().split(' ', 1)
        events.append({'timestamp': float(ts), 'event': evt})

with open(out_file, 'w') as o:
    json.dump({'events': events}, o)

Check pWCET and fail CI (Bash)

#!/usr/bin/env bash
# check_pwcet.sh report.json threshold
REPORT=$1
THRESHOLD=$2
pwcet=$(jq .task_x.pwcet_ms $REPORT)

awk -v val=$pwcet -v thr=$THRESHOLD 'BEGIN { if (val>thr) exit 1; else exit 0 }'

Reporting, traceability and audit

To satisfy auditors and safety cases, integrate reporting:

Attach RocqStat outputs to VectorCAST test cases; link trace IDs to failing tests for root-cause analysis.
Produce human-readable summaries (PDF) and machine-readable artifacts (JSON, JUnit).
Retain raw traces and analysis parameters for the lifetime required by your compliance domain (automotive supply chains typically require multi-year retention). Consider an operational playbook for retention and governance of those artifacts.

Benchmarks & expectations

From pilot projects in 2025–2026 integrating measurement-based WCET into CI, teams typically observe:

First 3 months: setup and stabilization — building test harnesses, instrumenting hardware and normalizing trace formats.
Ongoing: CI runtime impact of timing analysis varies by test duration; a 30–60 minute hardware test can be scheduled to run nightly while a fast subset runs on every push.
ROI: reduced late-stage performance debugging, fewer regressions in release branches, and earlier detection of compiler or platform-induced timing changes.

Example numbers (illustrative): teams that gate pWCET on nightly runs saw a 40–60% reduction in mid-to-late-stage timing escalations over 6 months.

Dealing with scale: parallelization & cloud

As your test matrix grows (targets, configurations, compiler versions), scale the analysis pipeline:

Parallelize physical test racks and measurement agents; use a work queue to distribute test runs. If you need orchestration guidance for edge-hosted racks, see examples from edge testbed orchestration.
Run RocqStat in containerized or cloud-hosted compute for heavy statistical analysis jobs.
Store results in a central database and use dashboards (Grafana) for trend analysis and regression detection. For offline and retention tooling, consider an offline-first tooling strategy for preserving artifacts.

Future predictions and what to watch in 2026

Expect these trends to accelerate through 2026:

Deeper toolchain integration: Vector’s acquisition of RocqStat will accelerate native VectorCAST–RocqStat connectors, reducing the adapter burden teams face today.
Regulatory alignment: Timing analysis practices will converge around acceptance criteria for ISO 26262 and similar standards; statutory guidance will increasingly reference pWCET techniques.
ML-assisted test selection: smarter sampling for measurement-based WCET — fewer runs needed to reach statistical confidence, driven by anomaly detection and intelligent sampling.
Cloud-based distributed analysis: offer burst compute for pWCET computations with secure trace uploads and controlled retention.

Common pitfalls—and how to avoid them

Pitfall: Treating timing like functional tests. Fix: Design separate timing-oriented test vectors and include warm-up and stress phases.
Pitfall: Not recording environment metadata. Fix: Always capture hardware, firmware, compiler and config versions with each trace.
Pitfall: Over-reliance on single-run measurements. Fix: Use repeated runs and randomized inputs to build representative distributions for RocqStat.
Pitfall: Blocking CI on long hardware runs. Fix: Implement fast timing checks on PRs and full pWCET regression gates on nightly builds.

Case study (composite, representative)

A European Tier-1 supplier piloted VectorCAST + RocqStat integration in Q4 2025. Key outcomes after three months:

Automated nightly pWCET analysis for 25 critical tasks across 3 ECUs.
Early detection of a compiler micro-optimization that increased WCET by ~12% for a tight ISR — avoided late-stage firmware rollback.
Reduction in manual WCET runs from 100s per release to 20 automated nightly analyses, freeing engineers for root-cause work.

Actionable checklist to get started this week

Identify 3 high-criticality tasks and define pWCET acceptance thresholds.
Validate you can extract high-resolution timing traces from your target hardware.
Create a VectorCAST test configuration that executes timing vectors with deterministic seed inputs.
Build a simple extractor to convert your VectorCAST trace into RocqStat-compatible format (see example templates for small automation scripts).
Add a CI job that runs the extractor, calls RocqStat, and fails on threshold violation.

Final notes on governance and trust

Measurement-based WCET (pWCET) and tools like RocqStat are complementary to static WCET techniques. For safety cases, use a combination: measurement-based for operational evidence and static analysis for absolute worst-case proof where needed. With Vector’s acquisition and roadmap, teams should expect tighter first-party integrations, but start today by establishing repeatable instrumentation, artifact retention, and CI gates — those practices will transfer smoothly when native connectors arrive.

Vector's acquisition of RocqStat in January 2026 signals a new era of unified timing and functional verification inside toolchains like VectorCAST.

Call to action

Ready to shift WCET left? Start by running a small pilot: select one critical task, implement the VectorCAST test harness, and wire a RocqStat analysis step into your CI. If you want a jumpstart, download our example repo with VectorCAST adapters, trace converters and CI templates — or contact our engineering team for a technical walkthrough and pilot plan tailored to your hardware matrix.

Take the first step: clone the example integration repo, run the included demo on a single target, and add a timing gate to your next feature branch. If you need help mapping acceptance criteria to regulatory requirements, our engineers can help you design thresholds and evidence packages for ISO 26262 and related standards.

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