The Open-Source Post-Silicon Validation Stack

June 8, 2026

Engineer working with circuit boards and test equipment in a hardware lab

Most "hardware test" lists stop at oscilloscopes and logic analyzers. In practice, validating silicon on a real platform runs through twelve distinct stages, and broken tooling at any one of them slows bring-up. The good news: open-source software covers most of that pipeline today.

I built awesome-dvt-automation to map that landscape. This post is the companion guide: a stage-by-stage walkthrough of the tools that can complement or replace proprietary test executives in a post-silicon lab.

Key Takeaways

  • Post-silicon validation is a 12-stage pipeline, not a single "test script"
  • Open-source tools exist for lab infra, instruments, protocols, SerDes, power, triage, and hardware CI
  • The gap is integration knowledge: how labgrid, OpenTAP, PyMeasure, and pytest connect
  • The repo discovers new tools monthly via automated PRs

Why another awesome list?

Pre-silicon verification has awesome-open-hardware-verification. PCB design has awesome-pcb-workflow. Post-silicon platform validation did not have a single curated map.

Validation engineers still stitch together lab workflows from vendor app notes, internal wikis, and one-off scripts. That works until you onboard a new hire or try to run regression on every firmware build.

awesome-dvt-automation covers 81 tools across:

Planning → Lab infra → Instruments → Bring-up → Protocols → SerDes → Power → Thermal → Execution → Triage → CI/CD → Agents

Each entry includes a one-line description, stack integration note, and license.

Stage 1: Lab infrastructure and board farms

Before you measure anything, you need deterministic control of power, reset, serial, and remote access across benches.

labgrid is the anchor: a Python library with coordinator/exporter architecture and a pytest plugin. It abstracts the hardware control layer so tests do not hard-code "which USB relay is on which host."

Pair it with usbrelay for inexpensive power cycling and LAVA if you need distributed scheduling across a larger lab.

Stage 2: Instrument control

PyVISA plus pyvisa-py talk to LXI/GPIB/USB-TMC instruments without a Windows-only driver stack. PyMeasure adds higher-level procedures for supplies, DMMs, and scopes.

The pattern: OpenTAP or pytest owns sequencing; PyMeasure owns SCPI. Log raw transcripts alongside parsed measurements for triage later.

Stage 3: Execution and sequencing

OpenTAP is the open test executive with a plugin model for instruments and result listeners. pytest is the lingua franca for lab engineers who already think in fixtures and markers.

Use @pytest.mark.hardware for tests that require physical DUTs; run -m "not hardware" on cloud CI and full suites on self-hosted runners in the lab VLAN.

Stage 4: Results, triage, and hardware CI

Validation without observability is just data hoarding. Grafana + InfluxDB for time-series lab metrics. Allure or JUnit XML for pass/fail history across firmware builds.

GitHub Actions self-hosted runners on the lab network are the closest equivalent to software CI for hardware: gate merges on instrument captures and boot tests, not just lint.

The integration cheatsheet

OpenTAP sequencer   →  PyMeasure / SCPI instruments
pytest runner       →  labgrid fixtures
ocp-diag-core       →  JSON health checks → dashboards
GitHub Actions      →  self-hosted runner on lab VLAN

Full cheatsheet and quick-start guides live in the repo docs.

Monthly discovery

On the 1st of each month, a GitHub Action searches for new qualifying tools, rotates Featured This Month, and opens a PR. Eval harness, link checks, Mergify, and Cursor Bugbot gate what merges.

Watch the repo if you want the stream without polling GitHub search yourself.

How to contribute

  1. Star awesome-dvt-automation
  2. Find your stage in the workflow map
  3. Open a PR with one tool row (format in CONTRIBUTING.md)
  4. Point us at SerDes, OCP, or pytest+labgrid patterns we missed

Sources