Integrating WCET Timing Analysis into CI/CD for Safety-Critical Messaging Systems

Stop shipping uncertain timing: embed WCET checks in CI/CD for real-time messaging

Safety-critical messaging systems in automotive and industrial domains are under pressure: faster release cadences, more complex integrations, and stricter timing budgets. Teams tell us the same pain: "We have functional tests in CI, but timing regressions slip into releases." The result is costly rework, delayed certifications, and safety risk. The good news in 2026: acquisitions like Vector's integration of StatInf's RocqStat into the VectorCAST toolchain make it practical to run WCET and timing analysis as first-class stages inside CI/CD pipelines for real-time messaging apps.

Why this matters in 2026

By late 2025 and entering 2026, three trends converged to make automated timing verification essential:

• Software-defined vehicles and industrial control systems increasingly push logic into software layers, increasing the volume and impact of timing-sensitive messaging.
• Regulatory and standards pressure (ISO 26262, IEC 61508) emphasizes not only functional correctness but demonstrable timing safety for ASIL/ SIL-rated components.
• Toolchain consolidation by vendors like Vector—bringing RocqStat's WCET expertise into VectorCAST—creates a unified path from code verification to timing proof, enabling automation in CI/CD.

"Timing safety is becoming a critical ..." — Vector statement on integrating RocqStat into VectorCAST (Jan 2026)

What VectorCAST + RocqStat enables for real-time messaging

Vector's acquisition of RocqStat (StatInf) focuses on embedding advanced timing analysis directly into developers' verification flows. Practically, this means you can:

• Run static WCET analysis against compiled binaries as part of a CI job.
• Combine measurement-based and model-based timing checks to reduce false positives while preserving safety margins.
• Gate builds on timing budgets for real-time messaging tasks (publish/subscribe, CAN/TSN messaging handlers, middleware callbacks).
• Produce artifacts and traceable evidence for safety audits and certification.

WCET fundamentals and why automation is hard

Worst-case execution time (WCET) estimation determines the maximum time a routine, task, or message handler could consume. For messaging stacks—protocol parsing, serialization, encryption, and dispatch—timing budgets are tight and depend on hardware behavior (caches, buses, multicore interference).

Automation is hard because:

• WCET requires platform-specific models (instruction timing, cache models, bus arbitration).
• Multicore and shared resources make conservative static analysis expensive or imprecise.
• Measurement-based methods need repeatable execution on representative hardware or trace collection during HIL tests.

Integrated tools like RocqStat plus VectorCAST reduce the friction by coupling code-level verification with timing models and measurement workflows that can be executed in CI/CD.

How to embed WCET timing analysis into CI/CD — a pragmatic, step-by-step guide

This section gives an actionable pipeline you can adopt. Objectives: fail fast on timing regressions, produce audit artifacts, and keep CI time manageable.

Step 1 — Define timing contracts and budgets

• List messaging paths and handlers: e.g., CAN message parse -> validate -> enqueue -> dispatch handler.
• Assign a deadline or budget for each path (ms or microseconds). Use system architects to derive budgets from end-to-end latency requirements.
• Define safety margins: for safety-critical components target a margin (e.g., required WCET <= 70% of period) or a percent-based delta allowed from baseline (e.g., ±5%).

Step 2 — Prepare the toolchain and CI environment

• Install VectorCAST and RocqStat on a secure build agent or container image. Coordinate license access (license servers or license files) and authenticate using CI secrets or SSO/OAuth tokens.
• Encapsulate tool invocations in scripted wrappers to simplify CI jobs and enforce consistent parameters.
• Ensure cross-compilation artifacts (ELF, MAP files) and compiler optimization flags are reproducible across CI runs—WCET depends on compiler output.

Step 3 — Add a WCET analysis stage to CI

Design the CI stage to run only when relevant code changes occur (message handling files, middleware, scheduler). For example, trigger the stage on changes to src/messaging/**.

Typical stage flow:

1. Build artifact for target (cross-compile).
2. Run static WCET analysis (RocqStat) on selected binaries or functions.
3. Optionally run measurement-based timing on a hardware runner or emulator and merge results.
4. Compare measured/estimated WCET against budgets. Fail the job on violations or regressions beyond thresholds.
5. Publish artifacts: WCET reports, trace files, and diagnostic maps for developers and auditors.

Step 4 — Fail fast, but be pragmatic

Not every CI run needs the heaviest analysis. Use tiers:

• Quick stage (every push): run conservative static checks for the most critical functions.
• Full analysis (merge request or nightly): run full WCET and measurement-based combination for broader coverage.
• HIL validation (release or daily): run full hardware-in-the-loop scenarios for final verification.

CI examples: GitLab CI, GitHub Actions, and Jenkins

Below are compact examples showing how to insert a WCET stage. Replace tool commands with your VectorCAST/RocqStat CLI wrappers.

GitLab CI (snippet)

stages:
  - build
  - test
  - wcet

build-target:
  stage: build
  script:
    - ./scripts/ci/build-target.sh
  artifacts:
    paths: [build/artifact.elf, build/artifact.map]

wcet-analysis:
  stage: wcet
  needs: [build-target]
  script:
    - ./scripts/ci/run_rocqstat.sh build/artifact.elf build/artifact.map --functions messaging_* --out reports/wcet.xml
    - ./scripts/ci/check_wcet_thresholds.py reports/wcet.xml thresholds.json
  artifacts:
    paths: [reports/wcet.xml]
  rules:
    - changes: [src/messaging/**]

GitHub Actions (snippet)

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Build
        run: ./scripts/ci/build-target.sh
      - name: WCET Analysis
        if: contains(github.event.head_commit.message, 'messaging')
        run: |
          ./scripts/ci/run_rocqstat.sh build/artifact.elf build/artifact.map --functions messaging_* --out reports/wcet.xml
          python3 ./scripts/ci/check_wcet_thresholds.py reports/wcet.xml thresholds.json

Jenkins (Declarative stage)

pipeline {
  agent any
  stages {
    stage('Build') { steps { sh './scripts/ci/build-target.sh' } }
    stage('WCET') {
      when { changeset '**/src/messaging/**' }
      steps {
        sh './scripts/ci/run_rocqstat.sh build/artifact.elf build/artifact.map --functions messaging_* --out reports/wcet.xml'
        sh 'python3 ./scripts/ci/check_wcet_thresholds.py reports/wcet.xml thresholds.json'
      }
    }
  }
}

Handling hardware, traces, and measurement-based techniques

Static WCET is conservative but sometimes overly pessimistic—combine it with measurements for realistic bounds:

• Use dedicated hardware runners or HIL benches for measurement-based runs. Collect traces (ETM, traceroute) and feed them to RocqStat/VectorCAST for trace-informed analysis.
• Automate trace capture: run scripted test vectors that exercise messaging handlers and upload traces as CI artifacts.
• Use statistical methods (e.g., Extreme Value Theory) where appropriate to estimate tails from measurement data; retain conservative safety factors for certification.

Best practices: gating, thresholds, and developer workflow

• Gate on functional deadline, not raw WCET: convert WCET to utilization or slack metrics (WCET / period, or deadline margin).
• Establish baseline runs: store baseline WCET values per function per target in your repository and use them for regression detection.
• Fail CI on meaningful regressions: e.g., fail when WCET increases by more than 5% or when WCET crosses the absolute deadline.
• Annotate code with timing budgets: inline comments and metadata help reviewers and tie WCET reports to code changes.
• Automate triage: when CI fails on timing, auto-assign the failure to the author of the MR and include the diff and hotspot report in the ticket.

Metrics and dashboards to track timing health

Make timing visible like unit test coverage:

• WCET margin per function (current vs baseline).
• Trend lines for regressions (weekly/monthly).
• Top N hotspots in messaging stacks.
• Counts of CI failures and time-to-fix for timing regressions.

Push WCET reports to your observability stack or a dedicated dashboard. Use artifacts produced by VectorCAST/RocqStat and parse them into Prometheus/Grafana or your internal dashboards.

Practical case: Real-time messaging in an ADAS message broker (concise)

Scenario: A team maintains an in-vehicle messaging broker that handles sensor messages, applies filters, serializes payloads to CAN and Ethernet TSN, and dispatches callbacks. After integrating RocqStat into VectorCAST and automating WCET in CI:

• They defined budgets per path (e.g., sensor parse + filter + serialize <= 800 µs).
• CI runs static analysis for changed handlers on MR; nightly runs combine static WCET with HIL traces from a bench.
• When a serialization optimization increased WCET by 12%, CI failed immediately; engineers rolled back and fixed the implementation in <24 hours, preventing a late-stage regression.
• Artifacts produced in CI were used in a safety audit, reducing manual evidence collection by 40%.

Common challenges and mitigation strategies

• Licensing and CI scale: Commercial tools require license seats. Mitigate by creating license pools, scheduling heavy runs on dedicated runners, and using lightweight static checks for everyday pushes.
• False positives: Combine static and measurement-based analysis to reduce conservatism and produce actionable results.
• Multicore interference: Use partitioning strategies (time-partitioning or resource reservation) and model shared resources in WCET tools.
• Long CI runtimes: Use tiered analysis, selective function targeting, and cache persisted build artifacts to speed repeated runs.

Advanced strategies for messaging-heavy systems

• Incremental WCET: run full WCET only on modified modules and run delta analysis for callers.
• Function-level budgets: decompose end-to-end timing into per-function allowances and enforce locally in CI.
• Automated remediation suggestions: use static profiling to point developers to hot code paths—e.g., expensive parsing or dynamic allocations inside handlers.
• Integrate with safety case artifacts: attach WCET reports to work items and verification matrices for certification traceability.

Trends and predictions for timing analysis (2026 and beyond)

Expect to see:

• Deeper toolchain consolidation similar to Vector + RocqStat, making timing analysis accessible earlier in the lifecycle.
• Better support for multicore and mixed-criticality systems, with hybrid static/measurement workflows becoming standard in CI.
• Increased use of AI-assisted hotspot detection and suggestion engines to find likely timing regressions during code review.
• More regulatory emphasis on demonstrable, automated timing evidence in CI for automotive and industrial certifications.

Actionable checklist to get started this sprint

1. Identify the top 10 messaging handlers with the tightest latency budgets.
2. Bootstrap a CI runner with VectorCAST/RocqStat or vendor tooling wrappers; secure licenses and secrets today.
3. Define baseline WCET values and safety margins; commit a thresholds.json file to repo.
4. Implement a lightweight WCET CI job triggered on messaging code changes.
5. Set failure policies for regressions and configure dashboards to visualize trends.

Final thoughts

Embedding WCET checks into CI/CD is no longer optional for teams delivering safety-critical, real-time messaging systems. The Vector + RocqStat integration marks a turning point: it makes timing analysis more accessible and automatable, enabling teams to catch regressions early and produce evidence for certification without blocking development velocity.

Call to action

Start enforcing timing safety in your pipelines today. Download our CI example repo (VectorCAST/RocqStat wrappers, threshold checkers, and dashboard parsers) or contact QuickConnect for a guided integration session tailored to your messaging stack and certification needs. Reduce integration time, secure your releases, and make timing regressions visible — before they reach the vehicle or plant floor.

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