What we deliver
Framework design
A layered architecture of test cases, keyword or fixture layer, and device and instrument drivers, so tests survive hardware and firmware changes.
Test libraries
Reusable libraries for CAN, LIN, Ethernet, UART, SPI and I2C, UDS diagnostics, power control and measurement through PyVISA and SCPI.
Bench automation
Automated power cycling, flashing through debug probes or bootloaders, relay and fault-insertion control and instrument capture, so benches run unattended overnight.
CI for embedded
Jenkins, GitLab CI or GitHub Actions pipelines with hardware runners, board farms, test sharding and results published per build.
Migration and refactoring
Moving ad-hoc scripts or legacy sequences into a maintained framework without losing existing regression coverage.
Reporting and traceability
JUnit XML, Allure or TestStand reports, results pushed to Polarion, codebeamer or Jira, and trend views that expose flaky tests.
Choosing a framework
| Framework | Best suited to | Notes |
|---|---|---|
| pytest | Firmware, device and lab automation in Python | Fixtures model benches well; large plugin ecosystem; PyVISA for instruments |
| Robot Framework | System and acceptance tests read by non-programmers | Keyword-driven, with Python libraries underneath |
| Vector CANoe with CAPL | Automotive network, diagnostic and ECU tests | Native restbus and UDS support; vTESTstudio for test design |
| NI TestStand | Sequencing on NI PXI hardware, validation and production stations | Calls LabVIEW, Python or C modules; built-in reporting |
| dSPACE AutomationDesk / ecu.test | HIL test automation | AutomationDesk works directly with dSPACE models; ecu.test spans tool vendors |
How we work
01
Audit existing tests
Inventory scripts, benches, flaky tests and manual steps, and measure how long a regression run takes today.
02
Agree the architecture
Pick or extend the framework, define layers and coding rules, and decide how results reach your ALM.
03
Automate in priority order
Start with smoke tests and high-value regression, then widen coverage release by release.
04
Connect to CI
Register benches as CI runners, add scheduling, retries for infrastructure faults only, and result publishing.
05
Maintain
Keep libraries current with hardware and firmware changes, and review flaky tests every week.
Where AI helps in testing today
Adoption is earlier than vendor marketing suggests. The World Quality Report 2025-26 (Capgemini and OpenText) finds that 89% of organisations are piloting or deploying generative AI in quality engineering, but only 15% have scaled it enterprise-wide, and average automation coverage is about a third of test cases.
Where it helps today: drafting test cases and test data from well-written requirements, suggesting boundary values, generating script boilerplate and clustering failures from long CI logs. Each output is reviewed like any engineer-written artefact. On safety-related programmes, a tool whose output is relied on as evidence falls under DO-330 tool qualification or ISO 26262-8 tool confidence rules, so AI works as an assistant to verification engineers rather than a verification tool in its own right.
Automation usually supports automotive testing, embedded software testing and HIL test bench setup. For HIL-specific automation, see HIL/SIL testing.
Standards
Toolchains our engineers work with
- Allure
- dSPACE AutomationDesk
- ecu.test
- GitHub Actions
- GitLab CI
- Jenkins
- NI LabVIEW
- NI TestStand
- pytest
- PyVISA
- Robot Framework
- Vector CANoe
- Vector vTESTstudio
Related work
Case studies →Fuzz and penetration testing an industrial gateway for the Cyber Resilience Act and IEC 62443-4-2
A recurring security test cycle for an industrial gateway: fuzzing, penetration tests and SBOMs mapped to IEC 62443-4-2 and the CRA.
Planning MIL-STD-810H and MIL-STD-461 pre-compliance for an indigenised rugged subsystem
Tailoring MIL-STD-810H and 461 requirements, writing procedures, running pre-scans and preparing a rugged LRU for its accredited lab campaign.
Closing DO-178C structural coverage with independent verification for a DAL B component
Independent verification closes statement and decision coverage, coupling analysis and tool qualification for a DAL B software component.
Further reading
All insights →Building an engineering or test team for a mid-market GCC in India
Ramp waves, dedicated team vs Build-Operate-Transfer, governance and the measures that matter for a mid-market GCC's engineering or test team.
Euro NCAP 2026 ADAS Testing: What Changes for SIL/HIL Test Plans and Test Capacity
Euro NCAP 2026 multiplies ADAS test variations. How to restructure SIL/HIL plans around ISO 34502 and OpenSCENARIO, and plan the capacity.
Automotive Cybersecurity Penetration Testing for R155: Fuzzing, OTA and ISO/SAE 21434 Evidence
What R155, R156 and ISO/SAE 21434 test evidence suppliers need, and where fuzzing, penetration testing and OTA tests fit.
Frequently asked questions
Can test automation use AI safely in safety-critical projects?
Yes, if AI is an assistant inside a reviewed process. Drafted test cases, generated scripts and log triage are reviewed and approved by engineers before they count as evidence. Where a tool's output is relied on without review, it needs qualification under DO-330 or a tool confidence assessment under ISO 26262-8, which few AI tools can support today.
Which test automation framework should we use?
Match the framework to the product and the team. pytest suits firmware and lab automation, Robot Framework suits system tests that non-programmers read, CANoe with CAPL suits automotive networks and diagnostics, TestStand suits NI-based stations and AutomationDesk or ecu.test suit HIL. Most programmes end up with two: one for the bench and one for system-level tests.
Will you replace our existing framework?
Rarely. Most programmes already have working tests in a framework the team knows, and a rewrite costs coverage and time. We usually extend what you run, refactor the libraries underneath and add CI, and migrate only when the current tool blocks the work, for example through missing hardware support or licence limits.
How do you deal with flaky tests on hardware benches?
By separating infrastructure faults from product faults. Bench health checks run before a suite, infrastructure failures such as a lost probe connection trigger a bounded retry and an alert, and product failures are never retried silently. Flaky tests are tracked, quarantined with an owner and fixed or removed, so the regression signal stays trustworthy.
Can automated tests count as evidence for ISO 26262 or DO-178C?
Yes, provided the tests are traced to requirements, reviewed, run on a controlled configuration, and the tools are assessed for confidence or qualified where they could hide an error. Results must be reproducible from the recorded software version, test version and bench configuration.
How does test automation fit into CI for embedded targets?
Hardware benches register as CI runners. A pipeline builds the firmware, runs host unit tests and static analysis, flashes the target, then runs the hardware suite and publishes results. Fast suites run per merge request; longer HIL and soak tests run nightly. Board farms with remote power and debug access let several teams share benches.
Can we hire test automation engineers instead?
Yes. We recruit test automation engineers with pytest, Robot Framework, CAPL, TestStand and AutomationDesk experience on contract, contract-to-hire or permanent terms. See hire test engineers for role profiles and screening.
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