Electronics Guide

Managing Binary Files

Electronics projects typically include numerous binary files that Git handles less efficiently than text. Schematic files, PCB layouts, compiled libraries, and FPGA bitstreams can bloat repository size and cannot be meaningfully merged. Git Large File Storage (LFS) addresses this by storing binary files on a separate server while maintaining references in the repository, keeping the main repository manageable while preserving complete version history.

Some teams maintain separate repositories for source files and generated outputs, linking them through build automation. Others use Git attributes to configure specific handling for different file types, applying binary diff tools or enforcing lock-modify-unlock workflows for files that cannot be merged. The appropriate strategy depends on team size, file types, and collaboration patterns.

Branching Strategies for Hardware Development

Hardware development cycles differ from software in important ways that affect branching strategies. Physical prototypes cannot be updated as easily as software deployments, and hardware revisions create permanent artifacts that must be traceable to specific design file versions. Common approaches include maintaining long-lived branches for each hardware revision, using tags to mark versions that correspond to manufactured boards, and creating feature branches for experimental changes that may affect multiple hardware generations.

Git flow and trunk-based development can both work for electronics projects with appropriate modifications. The key is establishing clear conventions for when branches are created, how they relate to hardware revisions, and when changes are merged back to main development lines. Documentation of these conventions ensures team members follow consistent practices.

Submodules and Monorepos

Large electronics projects often combine multiple components: microcontroller firmware, FPGA designs, PC applications, test scripts, and manufacturing documentation. Git submodules allow these components to be developed in separate repositories while maintaining coordinated versions. Alternatively, monorepo approaches keep all project components in a single repository, simplifying version coordination at the cost of increased repository size and complexity.

The choice between submodules and monorepos depends on team structure and component dependencies. Tightly coupled components that must always be released together often benefit from monorepo organization, while loosely coupled libraries shared across multiple projects may work better as submodules or separate packages.

HDL-Specific Considerations

HDL files benefit from the same version control practices as software source code: meaningful commit messages, atomic commits that represent logical changes, and code review before merging. However, HDL projects often include generated files from synthesis and place-and-route tools that require special handling. These generated files are typically large, change frequently, and can be regenerated from source, making them candidates for exclusion from version control or storage in separate artifact repositories.

Constraint files that specify pin assignments, timing requirements, and physical placement are particularly important to version control carefully. These files directly affect whether a design meets timing and functions correctly in hardware. Changes to constraints should be reviewed with the same scrutiny as HDL source changes, and constraint files should always be committed alongside the HDL code they configure.

IP Core Management

FPGA designs frequently incorporate intellectual property cores from vendors or third parties. These IP cores may be delivered as encrypted netlists, parameterized generators, or source code with licensing restrictions. Version control strategies must accommodate these different forms while respecting licensing terms and maintaining reproducibility.

For vendor-provided IP, teams often store configuration parameters and generation scripts rather than the generated IP itself, regenerating cores as part of the build process. This approach reduces repository size and ensures IP versions match the installed tool versions. Third-party IP with source code access can be managed as submodules or vendored copies, depending on licensing and update frequency requirements.

Simulation and Verification Assets

Testbenches, stimulus files, and expected results form an essential part of HDL projects and should be version controlled alongside the design under test. Simulation waveform databases and log files are typically excluded as generated outputs, though teams may choose to archive specific verification results for compliance documentation.

File Format Considerations

Modern EDA tools increasingly use text-based formats (often XML or JSON) for schematic storage, improving version control compatibility. Tools like KiCad store schematics in human-readable text formats that produce meaningful diffs, while others like Altium Designer use binary formats that require specialized comparison tools. When selecting EDA tools, version control friendliness should be a consideration alongside design capabilities.

For tools with binary formats, teams can export text-based representations (such as netlists or bills of materials) alongside the native files. While these exports cannot replace the schematic files themselves, they provide diffable artifacts that reveal functional changes even when the schematic files appear as binary modifications.

Visual Diff Tools

Several tools provide visual comparison capabilities for schematic files. These tools render before and after versions side by side, highlighting added, removed, or modified components and connections. Some integrate directly with version control systems, allowing engineers to review schematic changes as part of the normal commit and pull request workflow.

Visual diff tools may be standalone applications, plugins for specific EDA tools, or web-based services that process uploaded files. Integrating visual diffing into the review process helps catch design errors and ensures that schematic changes receive appropriate scrutiny from qualified reviewers.

Component Library Management

Schematic symbols and PCB footprints form reusable libraries that multiple projects may share. Version controlling these libraries ensures consistency across projects and provides traceability when components are modified. Library management strategies include centralized library repositories, project-local copies with periodic synchronization, and database-driven systems that track component parameters alongside graphical representations.

Changes to component libraries require careful review since errors can propagate to multiple projects. Many teams implement library review processes separate from project-level reviews, with designated librarians responsible for maintaining component quality and consistency.

Platform Options

GitHub, GitLab, and Bitbucket dominate the hosted platform market, each offering version control integrated with issue tracking, pull requests, continuous integration, and collaboration features. Self-hosted options like GitLab Community Edition and Gitea provide similar capabilities for teams requiring on-premises deployment due to security or compliance requirements.

For electronics-specific needs, specialized platforms have emerged that combine version control with EDA tool integration, component management, and manufacturing interfaces. These platforms understand electronics file formats and provide features like visual diff, design rule checking, and bill of materials management that general-purpose platforms lack.

Access Control and Permissions

Professional electronics projects often involve sensitive intellectual property requiring careful access control. Platforms support various permission models including repository-level access, branch protection rules, and fine-grained permissions that control who can view, modify, and approve changes to specific files or directories.

Branch protection rules prevent direct commits to important branches, requiring changes to go through pull requests with appropriate reviews. This ensures that production-ready branches maintain quality and that all changes are reviewed before integration. Protection rules can also require passing automated tests before changes are merged.

Integration with Development Tools

Modern platforms integrate with IDEs, EDA tools, and other development software through plugins and APIs. These integrations allow engineers to perform version control operations, view issues, and participate in reviews without leaving their primary development environment. Webhook integrations enable automated responses to repository events, triggering builds, tests, notifications, and other workflows.

Pull Request Workflows

Pull requests (or merge requests) provide a structured mechanism for proposing, reviewing, and integrating changes. The typical workflow involves creating a branch for changes, pushing commits to that branch, opening a pull request to propose merging into the target branch, receiving and addressing review feedback, and merging once approved.

Effective pull requests include clear descriptions of what changes were made and why, reference to related issues or requirements, evidence that changes were tested, and appropriate scope (neither too large to review effectively nor too small to be meaningful). Templates can guide contributors to provide necessary information consistently.

Review Criteria and Checklists

Establishing clear review criteria helps reviewers focus on important aspects and ensures consistent quality. Common review criteria for electronics projects include functional correctness, adherence to coding standards, appropriate error handling, test coverage, documentation updates, and consideration of hardware constraints like memory usage and timing.

Checklists formalize review criteria into explicit items that reviewers verify before approving changes. Platform features or automation can enforce that checklists are completed before merging is permitted. Different checklists may apply to different types of changes, with more stringent requirements for safety-critical components.

Automated Review Assistance

Static analysis tools, linters, and automated testing provide objective feedback that complements human review. Configuring these tools to run automatically on pull requests catches common issues before human reviewers spend time on them. Automated checks can enforce coding standards, detect potential bugs, verify that tests pass, and measure code coverage.

Some teams configure automation to block merging if automated checks fail, ensuring that all integrated code meets minimum quality standards. Others use automation as advisory information, leaving final merge decisions to human judgment. The appropriate approach depends on team culture, project requirements, and the reliability of automated checks.

CI Pipeline Components

A typical CI pipeline for electronics projects includes several stages. The build stage compiles firmware for all target configurations, generating binary images and build artifacts. The test stage runs unit tests, integration tests, and potentially hardware-in-the-loop tests. Analysis stages perform static analysis, measure code coverage, and check compliance with coding standards. Artifact stages archive build outputs for later deployment or testing.

Pipeline configuration typically lives alongside the project code, ensuring that build and test procedures evolve with the project. YAML-based configuration files define pipeline stages, dependencies, and conditions for execution. Parameterized pipelines support building for multiple hardware variants or test configurations from a single definition.

Hardware-in-the-Loop Testing

Electronics CI can extend beyond software simulation to include hardware-in-the-loop (HIL) testing. Dedicated test systems running actual hardware execute automated test sequences whenever code changes, providing confidence that firmware functions correctly on real devices. HIL testing catches issues that simulation might miss, including timing problems, hardware-specific bugs, and integration issues with peripheral devices.

Setting up HIL CI requires dedicated hardware installations, test fixture design, and careful management of shared resources. Test systems must handle concurrent test requests, recover from failures, and provide meaningful results that help developers diagnose issues. The investment in HIL CI infrastructure pays off through reduced manual testing effort and earlier detection of hardware-software integration problems.

FPGA Build Automation

FPGA development benefits significantly from CI automation. Synthesis and place-and-route runs are time-consuming, often taking hours for complex designs. Automating these builds ensures that the design continues to meet timing constraints as changes accumulate and that bitstreams are available for testing without waiting for local builds to complete.

FPGA CI pipelines typically include synthesis, implementation, timing analysis, and potentially simulation stages. Reports from each stage are archived for review, and failures in any stage block the pipeline. License management for commercial FPGA tools requires attention in CI environments, with floating licenses shared across build agents or cloud-based tool access for scalability.

CI Platform Options

Platform-integrated CI services like GitHub Actions, GitLab CI, and Bitbucket Pipelines provide convenient CI capabilities without separate infrastructure. These services offer free tiers for open-source projects and paid tiers for private repositories and additional compute resources. For specialized requirements, Jenkins, TeamCity, and other CI servers can be self-hosted with custom build agents configured for specific toolchains.

Electronics projects may require specific EDA tools, cross-compilation toolchains, or hardware access that cloud CI services cannot easily provide. Hybrid approaches use cloud services for standard tasks while delegating specialized builds to self-hosted runners with the necessary tools and hardware access.

Documentation as Code

The documentation-as-code approach treats documentation source files as first-class project artifacts, subject to the same version control, review, and automation as source code. Markdown, reStructuredText, and AsciiDoc provide text-based formats that diff well in version control while supporting rich formatting when rendered. Static site generators transform these source files into polished documentation websites.

Storing documentation in the same repository as code encourages keeping documentation current as designs evolve. Pull requests that change functionality can require corresponding documentation updates, and automated checks can verify that documentation builds successfully before changes are merged.

Automated Documentation Generation

Tools can extract documentation from source code comments, generating API references, module descriptions, and dependency diagrams automatically. Doxygen remains popular for C and C++ firmware projects, while HDL documentation tools extract module interfaces and timing information from Verilog and VHDL source files.

Automated generation ensures that documentation reflects the actual code structure, reducing the effort required to maintain accurate references. Generated documentation complements hand-written explanations that provide context, examples, and guidance that cannot be extracted from code alone.

Design Documentation and Traceability

Electronics projects often require traceability between requirements, design decisions, implementation, and testing. Documentation systems can support this traceability through structured documents, cross-references, and integration with requirements management tools. For regulated industries, proper documentation and traceability are mandatory for compliance with standards like IEC 62304 for medical devices or ISO 26262 for automotive electronics.

Wiki systems provide collaborative documentation with version history, suitable for evolving design discussions and team knowledge bases. For formal deliverables, document control systems manage approval workflows, revision tracking, and distribution, ensuring that stakeholders always access current, approved versions.

Repository Organization

Organize repositories to reflect project structure logically. Common approaches include directories for firmware, hardware design files, documentation, tests, and tools. Consistent naming conventions and directory structures across projects help team members navigate unfamiliar repositories quickly.

Include README files at the repository root and in major directories explaining the contents and providing getting-started instructions. Contribution guidelines document the expected workflow for submitting changes, including branching conventions, commit message formats, and review requirements.

Commit Practices

Make commits atomic, representing single logical changes that can be understood and potentially reverted independently. Write commit messages that explain not just what changed but why the change was made. Reference issue numbers or requirements identifiers to provide traceability.

Avoid committing generated files, build outputs, or temporary files that can be recreated from source. Configure gitignore files appropriately for the development tools used, excluding IDE settings, build directories, and other ephemeral content. When binary files must be committed, use Git LFS to keep repository size manageable.

Tagging and Releases

Use tags to mark significant points in project history, particularly versions that correspond to manufactured hardware or released firmware. Semantic versioning provides a consistent scheme for numbering releases, with major, minor, and patch components indicating compatibility and change significance.

Release notes document the changes included in each version, helping users understand what has changed and whether upgrades are necessary. Automated release processes can generate release notes from commit history or pull request descriptions, reducing manual effort while ensuring completeness.

Backup and Recovery

While distributed version control provides inherent redundancy through multiple repository copies, explicit backup procedures ensure recovery from disasters. Regular backups of the canonical repository, including Git LFS content, provide protection against data loss. Periodic verification that backups can be successfully restored catches problems before they matter.

For critical projects, geographic distribution of repository copies and backups protects against site-level failures. Cloud-hosted platforms typically provide their own backup and disaster recovery capabilities, though understanding these capabilities and their limitations remains important for risk assessment.