Reflections on HIL testing setups: Between cost, flexibility, and a growing open community
In the world of embedded systems, bugs that escape into production environments aren’t just technical oversights. They can have real-world consequences, from financial losses to erosion of user trust. And as any engineer working in embedded software testing knows, catching those issues early can save enormous downstream effort and cost.
That’s why strategies like “shift left” testing have become so popular. But while unit and integration tests catch many issues during development, they often miss problems that only appear when software starts interacting with real (or simulated) hardware.
This is where Hardware-in-the-Loop (HIL) testing proves its value.
Why HIL still matters
HIL testing makes it possible to simulate real-world hardware conditions in a controlled environment. It validates how the embedded software behaves when it receives signals from sensors, communicates over CAN, Ethernet, or other buses, or responds to timing conditions in a physical feedback loop.
When implemented well, HIL testing acts as a bridge between pure software validation and real-world physical testing. It provides system-level insights early in the cycle and supports daily regression testing as part of a continuous integration process. This makes it a surprisingly good fit for Agile workflows.
However, setting up and maintaining HIL environments presents its own challenges.
Two common approaches (and their tradeoffs)
In my experience, most teams building HIL setups follow one of two paths:
Vendor solutions: These setups are robust and packed with features. They often come with excellent support and stability. However, the price is typically very high. This can be a barrier for smaller teams or companies just beginning to explore HIL testing. Flexibility can also be limited, especially when trying to adapt or extend the system for specific needs.
Homegrown setups: These solutions offer maximum flexibility. They can be tailored precisely to the needs of the project or team. But this freedom comes at a cost. Custom setups often require a dedicated team for development and maintenance, and they can become difficult to scale over time. Changes, upgrades, and onboarding new users can be time-consuming.
A third option: Open source and community-driven HIL
Recently, I’ve been exploring a third path as part of my own learning. It’s based on open source tools that aim to bring automation, flexibility, and CI/CD integration into the world of HIL testing. This approach shows real promise, especially for teams that want to start building something powerful without the cost and complexity of traditional vendor systems.
Two projects in this space stand out:
Labgrid – A Python-based test automation framework that enables remote control of embedded targets. It supports a wide range of interfaces and integrates well with CI systems.
Jumpstarter – A lightweight tool focused on automating flashing, power cycling, and logging for embedded targets. It aims to simplify the orchestration of HIL tests in development and test environments.
Both tools can be combined with affordable hardware modules with GPIO controllers, CAN interfaces, and Ethernet switches to build flexible, cost-effective setups.
The OpenHIL Initiative
What really caught my interest is the emerging OpenHIL community (openhil.github.io). This initiative is driven by the idea of making HIL testing more accessible. It's a place where developers and testers exchange ideas, share reusable tools, and promote a mindset shift in how hardware testing can be approached.
Instead of treating HIL as something exclusive to large enterprises, OpenHIL encourages practical, scalable solutions that smaller teams can implement and grow with.
Final thoughts
For embedded teams, HIL testing is often essential, but not always easy to adopt. Between costly vendor tools and high-effort internal solutions, open source tools supported by an active community offer an exciting middle ground.
As I continue exploring and experimenting with these setups, I’ll share what I learn and what challenges come up. If you’re working on similar solutions, or thinking about how to integrate HIL into your own testing workflows, I’d love to exchange ideas.
