automotiveverificationci-cd

From MCU to SOC: Applying WCET and Timing Analysis in Safety-Critical CI/CD Pipelines

aappcreators

2026-02-05

10 min read

Automate WCET and timing verification with VectorCAST + RocqStat in embedded CI. Step-by-step CI examples, gating rules, and 2026 trends.

Hook: Why timing verification must move left in 2026 CI/CD

If you ship embedded or automotive software in 2026 and timing issues still show up late in the cycle, you know the cost: rework, missed certification milestones, and unpredictable field behavior. Teams tell us the same pain: long WCET cycles, fragile HIL runs, and manual gating of timing evidence. The answer is not just faster builds — it's integrating worst-case execution time (WCET) and timing analysis directly into automated pipelines so timing becomes a continuous, repeatable artifact of your CI/CD workflow.

Context: Vector + RocqStat and why it matters now

In January 2026 Vector Informatik acquired StatInf’s RocqStat timing-analysis technology to fold WCET and advanced timing analytics into the VectorCAST toolchain. This creates a practical path to combine functional verification (unit / integration / system tests) with precise timing verification under a unified toolchain — an important trend given rising requirements for timing evidence in ISO 26262 and other safety standards.

Vector will integrate RocqStat into its VectorCAST toolchain to unify timing analysis and software verification, addressing growing demand for reliable software verification in safety-critical systems. — Automotive World, Jan 16, 2026

What this article covers

This guide explains how to integrate VectorCAST and RocqStat into embedded CI/CD pipelines for MCU-to-SoC projects. Expect practical steps, CI examples (GitLab/GitHub Actions/Jenkins), recommended gating rules, artifact management, and certification-oriented best practices tailored for 2026 toolchains.

High-level integration pattern

At a glance, the recommended pipeline stages are:

Checkout & reproducible build
Unit tests (VectorCAST)
Static analysis & MISRA checks
WCET & timing analysis (RocqStat integrated into VectorCAST)
Hardware-in-the-loop (HIL) or virtual execution for measurement validation
Report, baseline, and release gating

Why unify functional and timing analysis?

Functional tests find logic errors; timing analysis proves timing budgets. Combining them in a single pipeline provides traceability: test case X exercises path Y whose execution time T (measured or estimated) feeds into safety arguments and ASIL-level artifacts. The VectorCAST + RocqStat unification announced in 2026 makes that traceability operational in automation.

Prerequisites: toolchain, licensing, and environment

Before automating, prepare these items:

Licenses: VectorCAST and RocqStat are commercial tools. Confirm CI runners have proper floating or node-locked licenses.
CLI/Headless APIs: Ensure you have access to VectorCAST CLI and RocqStat automation interfaces (Vector's roadmap indicates tight CLI integration following the acquisition).
Reproducible build environment: Use container images or immutable build VMs that include compiler, linker, and cross-compiler versions used for certification.
Hardware access: For measurement-based validation, reserve HIL benches or deterministic execution platforms (bare-metal runners) to gather timing traces.

Practical pipeline: step-by-step

1) Reproducible build

Create immutable build artifacts (ELFs/BINs) and signatures. Store exact toolchain and compiler options as part of the pipeline metadata — timing results are highly sensitive to optimization flags and linker scripts.

# Example: environment variables to freeze
COMPILER_VERSION=arm-none-eabi-gcc-12.2.1
CFLAGS='-Os -fno-exceptions -fdata-sections -ffunction-sections -g'
LINKER_SCRIPT=linker_runtime.ld

2) Unit & integration testing with VectorCAST

VectorCAST runs unit and module tests and produces coverage and traceability artifacts. Automate these runs in CI to ensure functional regressions are caught before timing analysis.

# Example VectorCAST (illustrative) CLI sequence
vcast init --project my-module.vcp
vcast build --config Release
vcast run --tests all --report ./reports/functional

Keep test harnesses consistent: the same harness used for timing analysis must be used functionally so that coverage maps to timing paths.

3) Static WCET estimation (RocqStat) — integrate with VectorCAST

With RocqStat integrated, configure analysis to consume the same binary and control-flow information from VectorCAST. There are two complementary approaches:

Static WCET — conservative analysis that provides an upper-bound execution time using microarchitectural models (caches, pipelines).
Measurement-based — uses execution traces to calibrate bounds; combine with static for mixed evidence.

Example (illustrative) CLI flow where RocqStat runs after VectorCAST produces the binary and control-flow graph:

# Illustrative commands — adapt to vendor CLI
vcast export-cfg --out cfg.json
rocqstat analyze --binary build/my-module.elf --cfg cfg.json --cpu-model cortex-a53 --output reports/wcet.json

Key options to tune:

CPU model and microarchitectural parameters (cache sizes, associativity, pipeline stages)
Function-level annotations for infeasible paths
Loop bounds and recursion limits — provide user annotations from source or test harness

4) Measurement & validation (HIL or virtual platform)

Use HIL or cycle-accurate virtual platforms to validate static WCET bounds. This is a critical feedback loop to detect modeling errors and to provide measured execution-time distributions for RocqStat’s statistical modules.

Run deterministic tests on isolated cores or with CPU affinity to minimize interference
Collect fine-grained traces (PC-level, timestamps, hardware counters)
Compare the measured maxima with the static WCET bound — track margins

5) Reporting, baselines and gating

Automate report generation and store machine-readable artifacts (JSON/XML) and human-readable summaries (HTML/PDF). Define gating rules in CI that enforce timing contracts.

# Example gate rules (concept)
- fail pipeline if wcet_delta_percent > 5% (regression)
- fail pipeline if measured_max > wcet_bound
- warn if coverage < 90% for timing-critical modules

Keep a golden baseline for WCET per build target and per critical function. When a regression is detected, CI should:

Attach the failing artifacts to the CI job
Open an automated issue with trace/coverage links
Optionally run an incremental focused timing analysis on the changed functions

CI examples

GitLab CI job snippet (illustrative)

stages:
  - build
  - test
  - timing

build:
  stage: build
  image: myregistry/embedded-build:2026-01
  script:
    - make all
  artifacts:
    paths:
      - build/my-module.elf

unit-test:
  stage: test
  image: myregistry/vectorcast-cli:latest
  script:
    - vcast run --project my-module.vcp --report reports/functional
  artifacts:
    paths:
      - reports/functional

wcet-analysis:
  stage: timing
  image: myregistry/rocqstat-cli:latest
  dependencies:
    - build
    - unit-test
  script:
    - vcast export-cfg --project my-module.vcp --out cfg.json
    - rocqstat analyze --binary build/my-module.elf --cfg cfg.json --cpu-model cortex-a53 --output reports/wcet.json
    - ./tools/check-wcet-regression.py reports/wcet.json baselines/wcet_baseline.json
  artifacts:
    paths:
      - reports/wcet.json
  when: on_success

The script check-wcet-regression.py enforces your organization’s regression policy and can fail the job if bounds are exceeded.

Jenkins / GitHub Actions: parallelization tips

Run unit tests and static analysis in parallel; WCET runs often need serialized access to licensed tools or HIL resources.
Use ephemeral runners for measurement stages (schedule to run when HIL benches are free).
Cache intermediate artifacts (CFG exports, annotation maps) to reduce analysis time on incremental changes.

Advanced strategies for robust timing CI

1) Incremental WCET for pull requests

Full WCET analysis can be expensive. Implement incremental analysis that focuses on changed functions and their callers — use control-flow deltas produced by VectorCAST to limit the scope while maintaining safety margins.

2) Statistical monitoring and learning

RocqStat supports statistical approaches to timing; use measurement traces accumulated across many CI runs to build probabilistic bounds and detect drift in execution-time distributions. In 2026, teams increasingly use hybrid deterministic-statistical evidence to reduce conservatism while preserving safety arguments.

3) Microarchitecture modeling as code

Keep CPU/cache/pipeline models in version control and treat them as first-class CI inputs. When you change models, re-run an expanded analysis and tag the run for certification evidence.

4) Traceability for certification

Produce traceability matrices that link requirements & test cases (VectorCAST) to timing evidence (RocqStat) and to artifacts used in certification packages (ISO 26262 / DO-178C). Automate packaging of these artifacts per release build.

Common pitfalls and mitigations

Pitfall: Treating measured maxima as WCET. Mitigation: Always annotate measured values and pair them with conservative static bounds.
Pitfall: Running timing tests on noisy hosts. Mitigation: Use dedicated, isolated hardware or virtualization that supports deterministic execution.
Pitfall: Not versioning microarchitectural models. Mitigation: Keep models in git and require model reviews with code changes.
Pitfall: No baseline or regression policy. Mitigation: Define precise gating rules and an SLA for addressing timing regressions. See also best practices for secure automation when you manage CI credentials and licenses.

Case study (abstracted)

A mid-size Tier-1 supplier optimized scheduling for a multicore SoC used in ADAS by integrating VectorCAST + RocqStat into its GitLab CI in late 2025. They adopted an incremental WCET strategy: pull requests triggered targeted RocqStat runs on changed modules; nightly full WCET runs validated end-to-end timing. Results:

CI cycle time for PRs with incremental timing: down from 6 hours to 50 minutes
Detected a 12% WCET regression introduced by a compiler flag change, fixed before integration
Reduced margin conservatism by 18% after 3 months of measurement-based calibration

Key success factors were versioned microarchitecture models, automated gating, and clear rules for when to escalate to a full WCET run.

2026 trends and what to watch next

Recent industry moves — notably Vector's acquisition of RocqStat in January 2026 — are driving tighter toolchain integration. Expect three developments in 2026 and beyond:

Tighter toolchain orchestration: unified GUIs and APIs between test and timing tools to reduce manual handoffs. See coverage of tooling partnerships and orchestration in vendor tooling news.
Cloud-native timing analysis: vendors will provide cloud-capable runners with deterministic virtual platforms for scalable analyses.
Hybrid static-statistical methods: broader adoption of probabilistic timing evidence for non-critical and soft-real-time domains to reduce conservatism while delivering safety evidence for critical flows.

Actionable checklist to get started this quarter

Confirm license model and tool CLI access for VectorCAST and RocqStat (or VectorCAST with integrated RocqStat modules).
Containerize your reproducible build and base image with the exact compiler and linker versions used in certification.
Implement VectorCAST runs in CI and export CFG/coverage artifacts automatically.
Run an initial RocqStat analysis offline and capture CPU model inputs; check for infra gaps (HIL access, counters).
Define gating rules (e.g., wcet_delta_percent threshold) and implement an automated regression checker in CI.
Set up nightly full WCET runs and PR incremental runs to balance feedback time vs. coverage.

Final recommendations

Integrating VectorCAST and RocqStat into CI/CD is a practical way to shift timing verification left and make timing evidence a continuous product output. Start small — automate unit tests and a minimal static WCET pass — then iterate to add measurement validation, baselining, and certification packaging. Treat microarchitecture models and timing artifacts as code, and lock down gating rules so timing becomes predictable instead of a late-stage surprise.

Key takeaways

Make timing continuous: run WCET and timing analysis as part of CI, not only at release time.
Unify tools and artifacts: VectorCAST + RocqStat integration provides coverage-to-timing traceability essential for safety cases.
Automate gating: baseline WCETs and enforce regression policies to catch timing drift early.
Mix static and measurement: use both conservative static bounds and measured traces to reduce over-conservatism while preserving safety evidence.

Next steps — call to action

Ready to harden timing verification in your embedded CI? Start by inventorying your current VectorCAST and timing workflows, then pilot a CI job that runs a VectorCAST unit test followed by a RocqStat analysis. If you need a hands-on blueprint, our team at appcreators.cloud can provide a tailored integration plan and sample CI config for your toolchain and target SoC.

Contact us to schedule a 30-minute technical workshop and get a custom CI starter template with VectorCAST and RocqStat integration for your environment.

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