Unified Timing Analysis: Practical Implementation Scenarios with RocqStat and VectorCAST

Hook: Why timing analysis and software verification must be unified now

Teams building safety-critical AI and real-time systems face the same recurring pain: software passes functional tests but fails in the field because of missed timing assumptions. Unpredictable WCET, hidden non-determinism, and fractured evidence streams slow releases, inflate audit cycles, and increase recall risk. In 2026 the industry is moving fast — Vector's acquisition of RocqStat (announced in January 2026) signals a practical shift: timing analysis and verification must live in the same toolchain to deliver deterministic, traceable, and auditable releases.

The state of play in 2026 — trends that drive unified toolchains

Late-2025 and early-2026 developments accelerated demand for integrated workflows. Vehicle platforms have more software-defined control, avionics and industrial controllers embed ML inference on constrained cores, and regulators expect stronger traceability and timing evidence. The pragmatic response is toolchain consolidation: combining static and measurement-based timing (WCET) with unit, integration and system verification to produce cohesive release artifacts for ISO 26262, DO-178C, and IEC 61508 audits.

Vector’s move to integrate RocqStat into VectorCAST creates an opportunity: unified testflows that produce deterministic verification reports, co-located timing annotations, and consistent traceability between requirements, tests, and timing claims.

What “unified timing analysis + software verification” actually delivers

• Determinism assurance: verify functional correctness and timing constraints from the same execution traces and requirement links.
• Traceable artifacts: single-source evidence bundles mapping requirements → tests → traces → WCET analyses.
• Faster gating: automated CI gates that assess timing regressions against thresholds, not just pass/fail tests.
• Regulatory-ready reporting: consolidated reports suitable for safety audits with minimal manual correlation effort.

Implementation patterns — concrete, actionable testflows

Below are four practical patterns engineers and release managers can adopt now. Each pattern includes a sample testflow, expected artifacts, and a gating policy template that you can adapt to your safety level.

Pattern A — Unit-level timing gating (fast feedback)

Goal: catch algorithmic regressions and local timing regressions early in CI.

1. Run VectorCAST unit tests with instrumentation enabled to collect per-test execution traces (function-entry/exit timestamps).
2. Feed vectorcast traces into RocqStat's per-path analysis to produce local WCET candidates for hot functions or algorithmic paths.
3. Compare measured worst-case from CI (measurement-based, across test vectors) with static WCET estimates.
4. Fail the build if measured WCET exceeds allowed margin relative to static estimate or requirement deadline.

Sample CI pipeline snippet (GitLab CI / similar):

stages:
  - build
  - unit-test
  - timing-analyze

unit-test:
  stage: unit-test
  script:
    - vectorcast-cli run --project my-project --target unit --trace output/traces
    - tar -czf traces.tar.gz output/traces
  artifacts:
    paths:
      - traces.tar.gz

wcet-analyze:
  stage: timing-analyze
  script:
    - rocqstat analyze --input traces.tar.gz --target cortex-r5 --output rocq-report.json
    - rocqstat compare --report rocq-report.json --threshold 0.20 # 20% margin
  when: on_success
  allow_failure: false

Expected artifacts: VectorCAST unit test logs, RocqStat per-function WCET candidates, automated comparison result. Gating policy example: fail if measured WCET > static-WCET × 1.2 or measured WCET > requirement deadline.

Pattern B — Integration + HIL timing verification (system-level confidence)

Goal: validate end-to-end timing across software stacks and hardware interfaces with hardware-in-the-loop.

1. Execute VectorCAST integration and system tests on HIL; collect global traces and tracepoints for inter-task latencies and I/O timings.
2. Apply RocqStat's whole-system analysis to compute critical-path WCET across task chains (accounting for scheduling and interrupt behavior).
3. Correlate results with telemetry captured during HIL stress scenarios (worst-case load, sporadic interrupts).
4. Generate audit-friendly evidence bundle: requirements → testcases → traces → WCET report → signed artifacts.

Key considerations:

• Define critical-path topologies in advance (sensor → processing → actuator chains).
• Instrument both software and HIL stimuli to reproduce edge-case loads.
• Use deterministic task scheduling or temporal partitioning where possible to reduce analysis complexity.

Pattern C — Delta timing analysis for PR gating (developer-friendly)

Goal: keep timing impact of code changes localized and visible; block PRs that introduce meaningful regressions.

1. On PR open, run a targeted VectorCAST suite for changed modules with tracing enabled.
2. Run RocqStat differential analysis: compare WCETs for changed code paths against baseline from main branch.
3. Classify delta: negligible (<5%), attention (5–15%), reject (>15% or crosses deadline).
4. If reject, create actionable report highlighting the path, contributing commit, and test vectors that exposed the regression.

Sample gating matrix (example thresholds, tune for your ASIL/assurance level):

• Negligible: <5% increase — auto-approve timing-wise.
• Attention: 5–15% — require peer review and developer justification.
• Reject: >15% or crosses requirement deadline — block merge until resolved.

Pattern D — Certification artifact bundling (audit-ready releases)

Goal: produce a single, traceable package for certification reviews (ISO 26262, DO-178C).

1. Collect VectorCAST test matrices mapped to requirements (traceability matrix).
2. Include RocqStat static analyses, measurement logs, instrumentation configurations, and HIL traces.
3. Document analysis assumptions (WCET model, CPU microarchitecture, interrupt model, cache handling).
4. Produce consolidated PDF/JSON evidence with cryptographic signatures for artifact integrity.

Regulatory tip: include a layer-by-layer argument that explains how timing evidence supports safety goals, and annotate any residual uncertainties and mitigations.

Interpreting results — practical guidance for engineering teams

Tools produce numbers. Your team must convert them into engineering decisions. Below is a concise approach:

1. Validate the model: ensure RocqStat’s CPU model (cache, pipeline, interrupts) matches your target hardware. Discrepancies produce misleading WCETs.
2. Reconcile static vs measured: prefer static WCET as a conservative bound; if measured > static, this indicates instrumentation or modeling mismatch and triggers an investigation.
3. Quantify uncertainty: report both deterministic WCET and observed worst-case; include confidence intervals when measurement-based statistics are used.
4. Map to requirements: for each timing requirement, list traces and test cases that exercise the critical path. This mapping is essential for audits.
5. Prioritize fixes: triage by path criticality (safety impact) and by effort to remediate (algorithmic optimization, scheduling changes, or hardware isolation).

Example interpretation scenario:

Observed: Task A processing worst-case input measured at 3.6 ms on HIL; RocqStat static WCET = 3.2 ms; requirement deadline = 4.0 ms. Action: Investigate instrumentation overhead and input coverage. If measurement is valid, update static model with discovered path and re-run system-level schedulability. If measurement is a one-off noisy sample, increase HIL runs and gather distribution to compute robust statistics.

Dealing with sources of non-determinism

To get meaningful timing results you must control or reason about non-determinism. The usual suspects:

• Caches and pipelines: apply analysis-friendly compiler flags, enable cache-flushing or use WCET-aware models in RocqStat.
• Interrupts & asynchronous events: model interrupt budgets and worst-case phasing. Prefer prioritized, bounded-interrupt handling.
• Multicore interference: use temporal partitioning or spatial isolation to reduce cross-core interference and make analysis tractable.
• Dynamic memory and OS jitter: avoid dynamic allocation in critical paths; freeze scheduler parameters during certification runs.

Actionable mitigation examples:

• Pin critical tasks to dedicated cores and disable power modes during certification HIL runs.
• Use RTOS primitives that provide timing bounds (e.g., fixed-priority or ARINC 653 partitions).
• Compile timing-critical modules with deterministic optimization settings and annotate them for RocqStat to focus analysis.

Release gating policies — templates you can adapt

Below are three gating templates (developer → release → certified release). Use them as starting points and calibrate thresholds to your platform, safety goals, and historical variability.

Developer gate (fast feedback)

• Execute unit + targeted timing tests.
• Fail if delta-WCET > 10% on any critical function or crosses the local deadline.
• Auto-generate a report and require author comment for attention cases (5–10%).

Release gate (integration stage)

• Full integration + HIL runs under stress profiles.
• Require static WCET for safety-critical paths < 75% of hard deadline for ASIL C/D (example policy — tune by architecture).
• Block release if any critical chain crosses deadline or if variance from baseline > 15%.

Certification gate (auditable artifact)

• Complete traceability matrix linking requirements → VectorCAST testcases → RocqStat timing results.
• Signed artifact bundle (tests, traces, WCET analyses, HIL logs, model assumptions).
• Independent review of modeling assumptions and path coverage; remediation plan required for deviations.

Traceability and regulatory evidence — building the narrative

Regulators and auditors care about narrative: how you moved from requirements to a claim that the system meets timing constraints. Unified toolchains make that narrative machine-readable and repeatable.

Minimum evidence bundle to produce:

• Requirements list with unique IDs.
• Test matrix from VectorCAST mapping tests to requirement IDs.
• Trace logs from unit/integration/HIL with timestamps and tracepoint IDs.
• RocqStat analysis files: configuration, CPU model, static WCET per path.
• Decision log capturing gating outcomes and any approved deviations.

Automate packaging: produce a JSON manifest that associates each requirement ID with the tests and the RocqStat result files that justify the timing claim. This manifest is the single source for audit queries.

Benchmarks & example numbers — a realistic snapshot

Below is an anonymized example from an embedded control module ported to a Cortex-R5 family core. Use this only as a reference; your mileage will vary by hardware and workloads.

• Function: sensor_fusion_process()
• Observed worst-case (HIL, 1,000 runs): 3.6 ms
• RocqStat static WCET estimate: 3.2 ms
• Requirement deadline: 4.0 ms
• Decision: pass at release gate with note: static model updated to include previously unmodeled IO delay; additional 50% stress test added to certification suite.

Key takeaway: static WCET should generally be conservative; if the observed worst-case exceeds the static estimate then treat it as a modeling gap. Unified flows let you detect and remediate those gaps earlier.

Advanced strategies for scale

As you scale from prototypes to fleets, adopt these advanced patterns:

• Delta & distributed analysis: only analyze changed paths in PRs; periodically run full analyses on main branch to avoid drift.
• Risk-based sampling: focus HIL and stress testing on the highest-risk combinations of inputs rather than brute-force testing.
• Federated evidence stores: keep a secure artifact store that contains signed proofs of timing analyses per release; this reduces audit turnaround when multiple suppliers are involved.
• Model governance: treat CPU/OS models as versioned artifacts; changes to models trigger re-analysis and re-certification as necessary.

Case study (compact) — integrating RocqStat into VectorCAST for a braking controller

Scenario: a braking controller team needed to prove end-to-end determinism across sensor sampling, control loop, and actuator command under worst-case network jitter.

Flow implemented:

1. VectorCAST executed unit and integration tests with instrumentation and produced tracepoints aligned to requirement IDs.
2. RocqStat computed WCETs for critical chains accounting for preemptive interrupts and bus contention.
3. The team used delta analysis to catch a PR that added a mutex in the hot path that increased WCET by 12% — flagged as attention and fixed before merge.
4. Final release artifacts included signed RocqStat reports and a traceability matrix — auditors accepted the package with minimal follow-up questions.

Outcome: faster certification cycle and fewer late-stage regressions.

Actionable takeaways

• Start small: add RocqStat analysis to existing VectorCAST unit tests to get rapid feedback on hot paths.
• Automate gating: enforce delta thresholds in PRs to stop timing regressions early.
• Bundle evidence: create a machine-readable manifest linking requirements → tests → traces → WCET outputs for audits.
• Control nondeterminism: isolate critical tasks and freeze scheduling parameters during certification runs.
• Treat models as code: version CPU/OS models and require re-analysis on change.

Closing — how to get started this quarter

2026 is the year tools converge. If you manage real-time, safety-critical software, unify timing analysis and verification now to shorten audit cycles and reduce field incidents. Begin by adding RocqStat analysis to a single VectorCAST project, automate PR-level delta checks, and produce your first traceability manifest for a release candidate.

Next steps: pick one critical function, instrument it in your VectorCAST unit suite, and run RocqStat analysis in CI within two sprints. If your organization needs a checklist for mapping this to ISO 26262/DO-178C evidence, create a traceability manifest template and iterate with your safety office.

Call to action

Ready to unify timing and verification for your next release? Start with a 2-week pilot that integrates VectorCAST traces with RocqStat analyses and produces an auditable evidence bundle. Contact your Vector tools representative or set up a cross-functional spike: engineering, QA, and safety — and measure the reduction in gating cycles by sprint three.

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