This article is based on concepts originally published at designnews.com. The observations and recommendations reflect common patterns in embedded software development practice.
Why Embedded Software Teams Need Better Build Pipelines
Embedded software development has long trailed the broader software industry when it comes to adopting modern engineering practices. In the late 1990s, the push was simply to move away from assembly language and toward structured C development. Today, while the general software industry has standardized on build pipelines, continuous integration, automated testing, and CI/CD workflows, many embedded teams — particularly at smaller companies — are still relying on largely manual, ad-hoc processes.
The gap matters. A well-designed build pipeline does not just speed up software delivery — it improves quality, reduces debugging time, lowers project costs, and makes firmware deployments more predictable and repeatable. This article explains what a modern embedded software build pipeline looks like, and how teams can incrementally implement one.
What Is a Software Build Pipeline?
A software build pipeline is the collection of processes and tools used to manage, build, test, and deploy an application in a structured, repeatable way. In a traditional embedded workflow, a developer writes code, manually tests it, and produces a firmware image that is manually flashed to the target device. This approach works at small scale, but it does not scale gracefully as team size or codebase complexity grows.
A modern build pipeline replaces manual, error-prone steps with automation. The core benefits include:
- Improved software quality through consistent, automated checks at every commit
- Reduced debugging time by catching defects early, before they compound
- Lower project costs by reducing rework and late-stage bug discovery
- Better deadline predictability through continuous visibility into code health
- Simplified deployment via automated, gated firmware delivery
The Four Stages of a Modern Embedded Build Pipeline
A practical embedded CI/CD pipeline can be broken down into four sequential stages. The first stage is triggered manually by the developer; the remaining three can be fully automated.
Stage 1: Commit (Manual Trigger)
The developer commits source code to a version control repository. This commit is the event that triggers all downstream automation. The quality of the pipeline depends heavily on how frequently developers commit. Small, frequent commits — ideally at least once per day — provide faster feedback loops and make it far easier to isolate the cause of a build or test failure.
Stage 2: Build and Analysis (Automated)
Once a commit lands, the CI server picks it up and triggers a full build of the firmware. This stage should also run static code analysis tools that examine the source for common defects, coding standard violations, and security vulnerabilities without executing the code. Both the compiler and static analysis tools should be invokable from the command line or expose plugins compatible with your CI server so that these steps require no human intervention.
Stage 3: Test and Reporting (Automated)
After a successful build, the pipeline runs automated tests and generates reports. These tests may run on a host-based simulator, an emulator, or actual target hardware depending on the maturity of the test infrastructure. Results — including pass/fail status, code coverage metrics, and any warnings from the analysis stage — are reported back to the developer. If anything fails at this stage, the pipeline stops and no deployment occurs. The developer is notified and the cycle restarts with a new commit after fixes are applied.
Stage 4: Deployment (Automated or Manual)
Only firmware that has passed all build, analysis, and test gates proceeds to deployment. Depending on the product and risk tolerance, deployment can be fully automated — pushing firmware to devices in the field via OTA (over-the-air) update mechanisms — or it can require a manual approval step before release. Either approach is valid; what matters is that the gate between test and deployment is enforced by the pipeline, not by human memory.
Building the Pipeline Incrementally
Setting up a full embedded CI/CD pipeline is not something that happens overnight. It requires research, tooling decisions, implementation work, and team training. The practical approach is to add each stage incrementally, making each one solid before moving on to the next.
Step 1: Establish Robust Version Control Practices
Most embedded teams now use some form of version control, which is a meaningful improvement from even a few years ago. However, committing code once a week — or less — is still common and largely defeats the purpose. The pipeline can only provide timely feedback if commits are frequent. Aim for at least one commit per developer per day, ideally more. This discipline also forces developers to break work into smaller, reviewable increments, which itself improves code quality.
Step 2: Stand Up a Continuous Integration Server
A CI server is the orchestration engine of the pipeline. It monitors the repository for new commits, triggers builds, runs analysis and tests, and reports results. Jenkins is one of the most widely adopted CI servers and has a large ecosystem of plugins relevant to embedded development, including support for various compilers and test frameworks. Other options exist and the right choice depends on your existing toolchain and infrastructure. What matters is that the CI server can be configured to execute your build and test steps automatically without manual intervention.
Step 3: Automate the Compiler and Add Static Analysis
Your compiler must be executable from the command line so the CI server can invoke it without a GUI. Most professional embedded compilers support this, but verify your toolchain does before committing to a CI approach. If your team does not yet use a static code analysis tool, this is an appropriate point to evaluate and adopt one. Static analysis catches entire classes of defects — null pointer dereferences, buffer overflows, uninitialized variables, MISRA violations — that compiler warnings alone will not surface. Integrating static analysis into the automated pipeline means every commit is checked, not just when a developer remembers to run the tool manually.
Step 4: Implement a Test Harness
Automated testing is the most valuable and also the most challenging stage to add to an embedded pipeline. Unlike application software, embedded code often has tight hardware dependencies that complicate host-based unit testing. Hardware Abstraction Layers (HALs) and dependency injection patterns can help decouple business logic from hardware-specific code, making more of the codebase testable without physical hardware.
Test harnesses for embedded C/C++ such as Unity, CppUTest, or GoogleTest can run unit tests on the host machine as part of the CI pipeline. For integration tests that require hardware, Hardware-in-the-Loop (HIL) test rigs can automate execution against real targets. Regardless of approach, the most important principle is to build tests alongside the code — not after the fact. Test-Driven Development (TDD) is one effective methodology for achieving this. Automated tests that cover only a fraction of the codebase can create false confidence; invest in meaningful coverage from the beginning.
Key Tools to Consider
| Pipeline Stage | Common Tool Examples |
|---|---|
| Version Control | Git (with GitHub, GitLab, or Bitbucket) |
| CI Server | Jenkins, GitLab CI, GitHub Actions |
| Static Analysis | PC-lint, Polyspace, Cppcheck, MISRA checkers |
| Unit Test Frameworks | Unity, CppUTest, GoogleTest |
| Build Systems | Make, CMake, SCons |
| Deployment / OTA | Custom scripts, Mender, balena |
Note: Tool selection should be driven by your target architecture, compiler ecosystem, and team familiarity. The table above lists representative options, not exhaustive recommendations.
Conclusion
Modernizing the embedded software build pipeline is a meaningful investment, but one that pays dividends throughout the entire product lifecycle. Faster feedback, earlier defect detection, and automated deployments reduce the unpredictability that plagues so many embedded development projects. The key is not to attempt the full pipeline transformation in a single sprint. Start with solid version control practices, add a CI server, automate the build and analysis stages, then gradually introduce automated testing. Each stage you add compounds the benefits of the previous one. Over time, you end up with a pipeline that gives your team continuous visibility into software health and the confidence to deploy firmware reliably.