embeddedverificationCI/CD

Embedded Software Verification for Small Teams: Practical Steps to Add RocqStat Checks

UUnknown

2026-02-15

10 min read

A practical, non-academic guide for small embedded teams to add RocqStat-based timing verification: what to measure, when to run checks, and simple gates.

Hook: Bring timing verification into your small embedded team without a PhD

Slow, unpredictable task timing and mystery regressions in the field are common pain points for small embedded teams. You don’t need a full formal methods lab to add trustworthy timing checks. With lightweight tooling like RocqStat and simple CI gates, a compact team can catch worst-case execution time (WCET) regressions early and keep releases predictable.

Why timing verification matters in 2026

Through late 2025 and into 2026, the industry shifted toward integrated toolchains that combine testing and timing analysis. In January 2026, Vector Informatik acquired RocqStat, signaling that timing checks and WCET estimation are becoming first-class concerns in mainstream toolchains. Timing verification is no longer an optional quality add-on for safety-critical domains—it’s a lifecycle requirement for any product where missed deadlines cost money, user trust, or lives.

"Vector will integrate RocqStat into its VectorCAST toolchain to unify timing analysis and software verification." — Automotive World, January 16, 2026

What small teams should measure (practical list)

Focus on a compact metric set that gives high signal with low effort. Measure these every run or periodically:

WCET per critical task: The estimated maximum execution time for each real-time task or ISR.
Typical execution time (median/95th percentile): For trends and regression detection.
Execution path coverage: Which code paths were exercised during timing runs.
Measurement variance (jitter): Standard deviation or interquartile range across runs.
Input-trigger distribution: Inputs that exercise worst-case behavior (identify scenarios).
Resource interference: Cache/pipeline impacts if running with co-runners or interrupts.

Quick glossary

Keep these concepts handy when you add checks:

WCET: Worst-case execution time estimate for a code fragment on target hardware.
RocqStat: Tool for statistical timing analysis and WCET estimation (recently acquired by Vector).
Verification cadence: How often timing checks run in CI and on hardware.
Pass/fail gate: A rule that decides whether a build is acceptable based on timing metrics.

Practical integration plan for small teams

Follow these four phases. Each phase is tailored to lean teams with limited hardware and staff.

Phase 1 — Baseline and fast wins (1–2 weeks)

Identify up to 5 critical tasks (scheduling, control loops, comm stacks).
Run initial measurements on a dev board or emulator to collect median, 95th percentile, and a single WCET estimate.
Use RocqStat in sample mode or the built-in CLI to generate a timing report and save artifacts in CI.
Establish an initial threshold for each task: baseline WCET plus 15% headroom.

Phase 2 — CI automation and lightweight gates (2–4 weeks)

Add a quick timing check to PRs using an emulator or instrumented unit tests that exercise hot paths.
Run full timing analysis nightly on a single hardware target or on-demand on a shared bench.
Implement two simple gates: immediate PR warning (soft) and nightly hard fail if WCET exceeds threshold.

Phase 3 — Hardening and statistical checks (4–8 weeks)

Introduce regression detection using rolling baselines and simple statistical tests (e.g., change > mean + 3 sigma).
Automate path coverage reports so you know if worst-case paths are exercised — part of building a solid developer experience that scales.
Run a full RocqStat exploration on release candidates and save signed artifacts.

Phase 4 — Operationalization (ongoing)

Integrate timing reports into release notes and RTCs for traceability.
Store historical WCET values and create simple dashboards (Grafana or static HTML) for trend spotting.
Plan scheduled re-runs when toolchain or compiler changes are made.

How often to run timing checks: a suggested verification cadence

Small teams need to balance CI cost with signal. Use this practical cadence matrix:

On every PR: Fast, instrumented micro-benchmarks on emulator or host. Goal: catch obvious regressions quickly. Run time < 5 minutes.
Nightly: Full software timing suite on target hardware or representative emulator. Goal: detect regressions and path changes. Run time 30–90 minutes.
Weekly: Full RocqStat WCET exploration on hardware-in-the-loop (HIL) or the most representative board. Goal: confirm WCET and stress edge cases. Run time several hours.
Pre-release: End-to-end WCET verification with production build, release config, and stress inputs. Goal: final sign-off. Run time variable; plan for 1–2 days if needed.

Example CI snippet: quick PR check

Below is a minimal CI job that runs a fast timing check and fails the PR if a simple regression is detected. This example assumes RocqStat CLI is available in the CI image or a Docker container.

jobs:
  quick-timing-check:
    runs-on: ubuntu-latest
    steps:
      - run: checkout
      - run: setup-cross-compiler
      - run: build-target --profile=instrumented
      - run: docker run --rm -v $PWD:/work rocqstat-image bash -lc '
          cd /work && ./run_instrumented_tests.sh --output timing.json && \
          rocqstat analyze --input timing.json --format json --output report.json'
      - run: |
          python tools/check_timing_gate.py report.json --max-rel-reg 0.05

The check_timing_gate.py script should implement the simple gating rules below. Keep it under 200 lines so the rules are auditable.

Simple pass/fail gating rules you can implement today

Start with deterministic, easy-to-understand rules. Avoid opaque statistical black boxes at first.

Absolute threshold: Fail if WCET > known-safe threshold. Example: task_x WCET must be < 8 ms.
Relative regression: Fail if WCET increases by more than X% relative to baseline (recommend 5–10% for PRs).
Statistical regression: Fail if new median or 95th percentile exceeds baseline mean + 3 sigma (after you have enough samples).
Coverage fail: Fail if worst-case path coverage drops below a set fraction (e.g., < 80% of identified worst-case paths exercised).
Soft warnings: For non-critical tasks, mark as warning in PR but fail on nightly runs to reduce developer friction.

Implementing a robust baseline (calibration)

Baseline calibration is where most teams get it wrong. Do this carefully:

Collect an initial dataset of 50–200 samples per task on target hardware where possible.
Use representative inputs, including worst-case sequences and stress combinations.
Record toolchain, compiler flags, power mode, and hardware revision—baseline is tied to configuration.
Set thresholds with engineering margin, then tighten over time as confidence grows.

Hardware constraints and cost-saving tactics

Small teams often have limited benches. Here are practical trade-offs:

Use fast emulators or hardware simulators for PR-level checks; reserve real hardware for nightly/weekly runs. Many teams pair this with compact dev benches and cloud-assisted analysis (cloud-PC hybrids and remote benches).
Containerize RocqStat and reuse a single shared bench with scheduled jobs to avoid hardware duplication — combine containerized analysis with message-driven job scheduling for better utilization (edge message brokers).
Cache instrumentation artifacts to avoid rebuilding everything on each run.
Parallelize different task suites across time windows rather than machines—this smooths utilization.

Interpreting RocqStat outputs: what to look for

RocqStat provides distributions, path sets, and WCET estimates. For small teams, focus on these signals:

Sharp increases in WCET: Immediate investigation—likely a code-path or compiler change.
Rising variance: Indicates input diversity or interference; look for new interrupt sources or timing sources in the code.
New uncovered paths: Might indicate test harness gaps or unintended control flow changes.
Convergence behavior: If WCET estimates are unstable between runs, increase sample size or review measurement isolation.

Case study (compact): How a small IoT team avoided a field recall

Team size: 6 engineers. Product: battery-powered sensor node with 10 ms control loop. Problem: occasional missed sensor deadlines in the field after a compiler upgrade.

Action: Added RocqStat-based nightly WCET runs and a PR-level instrumented check.
Finding: Median times did not change, but 99th percentile increased by 20% after the compiler upgrade.
Resolution: Reverted a specific optimization flag and added a micro-benchmark that gates future compiler changes.
Outcome: No recall needed, releases regained scheduling margin, and confidence improved for the small team.

This example illustrates that timing checks often catch regressions that unit tests and CI performance tests miss.

When a check should be a soft warning vs hard fail

Not all timing anomalies require blocking development. Use role-based enforcement:

Soft warning (PR): Minor relative regressions < 10% or non-critical task timing variance. Developer gets a notification and link to report.
Hard fail (nightly / merge): Absolute threshold violations, regressions > 20%, or reduction in worst-case path coverage for critical tasks.
Escalation: If the release candidate fails WCET on hardware, escalate to on-call and pause release until mitigated.

Toolchain and automation best practices

Make the timing checks reliable and low-friction with these patterns:

Immutable artifacts: Save timing reports tied to commit hashes and build IDs for traceability — treat these artifacts like any other telemetry asset to be audited and secured (trust and telemetry scoring).
Auditable scripts: Keep gating logic in small, reviewed scripts in the repo.
Containerized analysis: Package RocqStat and its dependencies in a container to avoid environment drift; this pairs well with cloud/edge runtimes (cloud-native hosting and edge workflows).
Fail-fast vs fail-safe: Fail fast on absolute breaches; fail safe with warnings for ambiguous signals.
Traceability: Link timing reports to test case IDs and requirements for compliance purposes.

2026 trends and what to prepare for

Expect the following industry shifts through 2026 and plan accordingly:

Integrated verification stacks: Vendors will bundle timing analysis into testing toolchains, reducing setup friction (e.g., Vector integrating RocqStat).
Higher expectations: Safety standards and customers increasingly expect evidence of timing verification even for non-critical products.
Automation-first: Teams that automate timing checks early see dramatically fewer late-stage surprises.
Cloud + edge workflows: Expect more hybrid workflows where heavy analysis runs in the cloud while final verification runs on physical benches — similar to emerging edge+cloud telemetry patterns.

Common pitfalls and how to avoid them

Avoid treating WCET as a single number. Always retain distributional context.
Don’t gate everything immediately. Start soft, then harden gates to reduce developer resistance.
Don’t rely solely on emulators for final sign-off. Emulators are great for PRs; hardware is essential for WCET confidence.
Avoid opaque statistical models early on—favor simple thresholds and clear documentation that stakeholders can review.

Minimal scripts and artifacts to create now

Create these five artifacts as part of onboarding a timing verification workflow:

Baseline collection script that runs N samples per task and stores JSON output.
Gate checker that reads RocqStat JSON and evaluates the simple rules described above.
CI job definitions for PR, nightly, and weekly runs (example provided earlier).
Signed release timing report template for compliance and customer audits — treat signing like any secure release artifact and consider bug-bounty style audits for critical repos (bug-bounty lessons).
Dashboard or static trend page plotting median, 95th, and WCET over time.

Actionable takeaways

Start small: Add a PR-level instrumented check and a nightly hardware run—don’t try to formalize everything at once.
Measure distributions: WCET is important, but track median and percentile trends to spot regressions early.
Use clear gates: Implement absolute thresholds for critical tasks and soft warnings for less-critical ones.
Containerize and automate: Package RocqStat in your CI to avoid environment drift and to make runs reproducible — combine containerized analysis with caching and smart job scheduling (caching strategies).
Document baselines: Record config, compiler flags, hardware revision, and test inputs with every baseline.

Next steps (4-week pilot plan)

For teams ready to pilot, here is a simple 4-week plan:

Week 1: Pick 3 critical tasks, collect baseline samples on target hardware, and define thresholds.
Week 2: Add PR-level instrumented tests and a quick RocqStat analysis in CI.
Week 3: Add nightly full timing suite on hardware and implement hard-fail gating for serious breaches.
Week 4: Create a release timing report and review the pilot with stakeholders; plan roll-out to the rest of the codebase.

Final note

Timing verification no longer needs to be an academic exercise reserved for large teams. By adopting pragmatic baselines, a sensible verification cadence, and clear pass/fail gates, small teams can gain predictable timing behavior and reduce risky regressions. The industry is moving fast in 2026—tools like RocqStat becoming part of mainstream toolchains means now is the time to make timing checks part of your CI/CD best practices.

Call to action

If you are on a small embedded team and want a compact, repeatable plan to add timing verification with minimal overhead, start a 4-week pilot. Contact us to get a starter repo with Dockerized RocqStat examples, CI jobs, and gating scripts you can use today.

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