embeddedverificationci-cd

Implementing Real-Time Safety: Integrating RocqStat into Your Embedded Software Verification Pipeline

wwebdev

2026-01-29

9 min read

How Vector's acquisition of RocqStat transforms WCET workflows—practical steps to add timing checks to embedded CI pipelines.

Real-time timing failures are the silent project killer for embedded teams

Missed WCET budgets, flaky timing on the target, and late discoveries of race conditions delay releases, raise certification costs, and produce embarrassing field recalls. As vehicles and safety-critical devices become increasingly software-defined in 2026, teams can no longer treat timing analysis as a one-off activity performed manually before integration testing. The acquisition of RocqStat by Vector in early 2026 is a pivotal moment: it signals the consolidation of advanced timing analysis directly into mainstream verification toolchains and makes continuous timing verification in CI/CD practical for embedded and automotive teams.

Top-line: What Vector's acquisition of RocqStat means for your WCET workflows

Unified toolchain: Expect RocqStat's timing-analysis capabilities to be available inside VectorCAST, reducing friction between functional tests and WCET estimation. This follows broader toolchain consolidation trends.
Shift-left timing verification: Timing checks become a first-class, automated gate in embedded CI rather than a late-stage manual audit. Observability practices are critical here—see patterns for detecting regressions early (observability patterns).
Traceability for certification: Tighter integration enables artifacts and reports that map tests, code versions and timing evidence—helpful for ISO 26262 evidence packages. Treat archival and immutable artifact retention like an archival playbook (preservation & archival patterns).
Operational continuity: Vector's retention of StatInf talent means continued evolution and faster delivery of features that teams need. Operational runbooks for on-prem and edge runners help keep timing models reproducible (micro-edge operational playbook).

Vector's move integrates advanced timing analysis into an established code-testing toolchain, accelerating verification workflows for safety-critical systems.

Why timing verification must be continuous in 2026

Several trends accelerated in late 2025 and continue into 2026 that make continuous timing verification non-negotiable:

Software-defined vehicles and distributed ECUs have moved more logic into software, increasing timing interdependencies between modules.
More stringent verification expectations from OEMs and suppliers for timing budgets and traceable evidence.
Hardware complexity: modern MCUs and SoCs have deeper pipelines, caches, and heterogeneous cores that make conservative manual WCET budgeting impractical.
Toolchain consolidation: vendors are prioritizing integrated verification suites that reduce integration overhead. See the enterprise cloud and toolchain evolution discussion.

That combination turns WCET and timing analysis from an occasional engineering exercise into a continuous, automated requirement. Vector's acquisition of RocqStat creates a plausible path to embed advanced timing checks directly into verification pipelines.

Where RocqStat fits in your verification architecture

At a high level, the timing verification step belongs after build and unit/integration testing but before release gating. A practical flow:

Build – compile with consistent flags and produce symbols/map files.
Unit and integration tests – run VectorCAST test suites to exercise code paths and produce coverage data.
Timing analysis – hand the compiled artifact, map, and coverage/trace data to RocqStat (or the VectorCAST/RocqStat integrated module) to compute WCET and timing margins.
Gate – parse WCET reports and enforce budgets in CI. Create tickets or block merges for regressions.
Audit – store timing evidence, versions, and logs for certification and postmortem analysis. Use immutable archival practices from preservation playbooks (archival playbook).

This flow removes the manual handoff between functional verification and timing verification and enables automated regression detection.

Practical, step-by-step integration into your CI/CD pipeline

Below are concrete steps most embedded teams can follow to add timing verification to a CI pipeline using VectorCAST and RocqStat integration. The commands and tooling names are illustrative; adapt for your installed tool versions once Vector provides the integrated release.

Step 0 – prerequisites

Licensed VectorCAST with access to RocqStat capabilities (or a RocqStat CLI) and valid target timing models for your MCU/SoC.
Reproducible cross-compiler toolchain and deterministic build flags recorded in your repo. Consider orchestration patterns for reproducible builds (cloud-native orchestration).
Build artifacts: ELF/HEX, map files, and debug symbols where required.
Test harnesses and VectorCAST projects stored in source control or an artifact registry.
CI runners with appropriate toolchain and target models installed (on-prem runners for hardware-accurate modeling; cloud runners for fast static checks — plan hybrid flows and multi-cloud considerations with a migration playbook: multi-cloud migration).

Step 1 – make your builds timing-friendly

Consistency is the single most important requirement. Use a build matrix file that pins compiler versions and flags. Example recommendations:

Keep optimization levels consistent across CI and local reproduction.
Produce map files and symbol tables during CI builds.
Enable compile-time flags that preserve enough metadata for analysis (for example, do not strip symbols if analysis needs function-level mapping).

Step 2 – instrument and run tests with VectorCAST

Use VectorCAST to exercise unit and integration test cases. Coverage data and test traces help the timing tool focus on realistic execution paths and reduce grossly pessimistic estimates. Read how coverage-driven approaches improve signal in analysis in the analytics playbook.

Step 3 – run RocqStat timing analysis

With Vector's integration, expect a Ray of convenience where a VectorCAST post-processing action triggers RocqStat. If RocqStat is available as a CLI, a typical call looks like this (example):

rocqstat-cli analyze --binary build/ecu.elf --map build/ecu.map --hw-model hw/target-model.json --coverage test/coverage.xml --out reports/wcet-report.json

The report will contain per-function WCET numbers, critical path annotations, and aggregated task-level budgets.

Step 4 – fail-fast on regressions

Make the WCET check a gating stage in your CI. Parse the report and compare the computed WCET against the budget defined in your configuration. If the analysis shows violation or significant regression, fail the job and open a ticket automatically. Use a patch orchestration runbook to avoid a cascade of quick fixes that leave the system vulnerable (patch orchestration runbook).

# pseudo-shell logic in CI
wcet_value=$(jq '.summary.max_wcet_ms' reports/wcet-report.json)
budget_ms=2.5
if [ $(echo "$wcet_value > $budget_ms" | bc) -eq 1 ]; then
  echo 'WCET budget exceeded: failing pipeline'
  exit 1
fi

Step 5 – store artifacts for audit and triage

Persist the WCET report, execution traces, and coverage artifacts to your artifact store with a reproducible tag. Treat retention and archival the same way you would preserve important lecture or research artifacts (archival playbooks).
Attach reports to your MR/PR for reviewers to inspect timing regressions alongside code diffs.

Example CI snippets

Below are compact examples showing where a timing analysis step sits in common CI providers. Replace executable names with your installed binaries when the integrated VectorCAST/RocqStat tooling is available.

GitLab CI example

stages:
  - build
  - test
  - timing

build:
  stage: build
  script:
    - make clean all
    - cp build/ecu.elf artifacts/
  artifacts:
    paths:
      - artifacts/ecu.elf
      - artifacts/ecu.map

unit_tests:
  stage: test
  script:
    - vectorcast-cli run --project tests/unit
    - vectorcast-cli export-coverage --output coverage.xml
  artifacts:
    paths:
      - coverage.xml

wcet_analysis:
  stage: timing
  script:
    - rocqstat-cli analyze --binary artifacts/ecu.elf --map artifacts/ecu.map --hw-model hw/arm-cortex-m7.json --coverage coverage.xml --out wcet.json
    - python scripts/check_wcet.py wcet.json 2.5
  dependencies:
    - unit_tests
  when: on_success

GitHub Actions example

jobs:
  build-test-wcet:
    runs-on: self-hosted
    steps:
      - uses: actions/checkout@v4
      - name: Build
        run: make -j4
      - name: Run VectorCAST tests
        run: |
          vectorcast-cli run --project tests/unit
          vectorcast-cli export-coverage --output coverage.xml
      - name: Run RocqStat timing analysis
        run: |
          rocqstat-cli analyze --binary build/ecu.elf --map build/ecu.map --hw-model hw/arm-cortex-m7.json --coverage coverage.xml --out wcet.json
          python scripts/check_wcet.py wcet.json 2.5

These snippets show a single-step timing gate. In practice, split the work into a fast static pre-check and a slower, more accurate analysis that runs nightly or on release branches. Orchestrate those stages with cloud-native workflow patterns (cloud-native orchestration).

Handling common embedded timing challenges

Timing analysis is rarely plug-and-play. Here are strategies to address typical obstacles:

Non-deterministic hardware behavior: Use accurate hardware models for caches and pipelines; when unavailable, use conservative configuration and then validate with hardware-in-the-loop (HIL). Operational guidance for on-prem HIL and edge runners is in the micro-edge operational playbook.
Multicore interference: For today's multi-core ECUs, use compositional WCET approaches or isolate cores during timing-critical execution. Consider architectural guidance from broader systems evolution research (enterprise architecture evolution).
RTOS preemption and interrupts: Model the scheduler and interrupt load in RocqStat or use measurement-driven scenarios to supplement static estimates.
Compiler optimizations: Lock and document optimization flags and reproduce builds in controlled CI runners.
Scaling analysis time: Use a two-stage approach: fast, conservative per-commit checks; periodic deep-analysis runs for release branches. Automate orchestration of those stages with workflow tooling (cloud-native orchestration).

Best practices for teams adopting continuous timing verification

Define budgets early: Have a per-task timing budget and a project-level WCET policy in your requirements. Make budgets part of the CI config.
Baseline and monitor: Capture a baseline per commit range and detect deltas; alert when regression exceeds a tolerance threshold, not just absolute failure. Observability patterns help here (observability patterns).
Automate triage: When a regression occurs, automatically capture diffs linking the code change to functions showing increased WCET and assign owners. Use patch orchestration runbooks to manage remediation flow (patch orchestration runbook).
Use coverage to reduce pessimism: Passing test traces dramatically reduce over-conservative WCET results by ruling out infeasible paths.
Keep artifacts immutable: Archive the exact binary, map, and report used for a WCET claim to support audits and certification evidence.

Case study (illustrative)

An automotive ECU supplier integrated RocqStat into their VectorCAST pipeline in Q4 2025 as part of a controlled pilot. Before integration, timing regressions were often discovered late during integration testing. After adopting a CI gate with daily deep analysis and per-commit fast checks, the team reported:

Detection of timing regressions within hours rather than weeks.
Reduction of late-stage remediation work by an estimated 40% on a single product line.
Stronger traceability for verification artifacts used in ISO 26262 evidence packs.

This is a composite example but reflects a reproducible pattern teams are seeing as timing tools integrate into mainstream verification flows.

What to watch in 2026 and beyond

Tool convergence: Expect more timing tools embedded in functional verification suites. Vector's acquisition of RocqStat is the leading example.
Cloud-assisted verification: Hybrid flows where fast static checks run in cloud CI and hardware-accurate analyses run on-prem or in secure cloud HIL farms will become standard. Plan hybrid infrastructure with multi-cloud considerations (multi-cloud migration).
ML-assisted path selection: Machine learning will help select realistic worst-case paths from traces to speed up deep analyses. See approaches that integrate on-device signals with cloud analytics (on-device AI integration).
Standards alignment: Timing evidence will be more tightly mapped to safety argumentation in certification dossiers.

Checklist before you flip the switch

Have stable build reproducibility and pinned toolchains documented in repo.
Identify per-task timing budgets and document pass/fail rules for CI.
Install VectorCAST and RocqStat on CI runners and validate a local reproducer for one critical task.
Create automation to archive reports and link them to PRs and tickets. Use archival/playbook guidance (archival playbooks).
Plan for staged rollout: developer preview, CI fast checks, nightly deep-analysis, and release gating.

Final takeaways and next steps

Vector's acquisition of RocqStat is an operational inflection point for embedded teams. It lowers the bar to implement continuous WCET and timing verification and converts timing analysis from a heavyweight, late-stage activity into a routine, automated step in your CI/CD pipeline. For automotive and safety-critical projects this isn’t just efficiency: it’s risk reduction and stronger evidence for certification.

Actionable next steps you can do this week:

Identify one timing-critical task and add it to your CI as a candidate for timing checks.
Ensure your build pipeline produces map and symbol files and archives them alongside test coverage.
Prototype a pipeline step that invokes RocqStat (or the integrated VectorCAST action) and fails on budget violation.

Adopting these practices now will make your team resilient to the increasing software complexity of modern vehicles and reduce late-stage surprises.

Call to action

If you manage embedded or automotive verification, start a pilot to add timing verification to your CI this quarter. Request a demo of VectorCAST with RocqStat integration, or spin up a small internal PoC using the CI examples above. Share your constraints with your tool vendor and plan an integration sprint that includes setting budgets, running a baseline, and automating regression alerts. Timing safety should no longer be a late-stage afterthought—make it a continuous, automated property of your delivery process.

webdev

Contributor

Senior editor and content strategist. Writing about technology, design, and the future of digital media. Follow along for deep dives into the industry's moving parts.