CI/CD with MATLAB and Simulink
A Technical FAQ for Engineering and DevOps Teams
Teams using MATLAB and Simulink in continuous integration and continuous delivery (CI/CD) need a reliable way to run builds, tests, and verification workflows noninteractively while keeping results reproducible and auditable. This FAQ explains how Model-Based Design fits into modern DevOps pipelines and helps you assess whether these tools can support your CI/CD workflows. It focuses on the key questions teams ask early, before committing to an implementation.
How MATLAB and Simulink Fit Into CI/CD Workflows
CI helps teams detect issues earlier by running model checks, simulations, test suites (including MATLAB Test™ and Simulink Test™), and code generation on every change. This approach reduces integration risk and establishes a repeatable development process with outputs such as test results, coverage metrics, and analysis reports that support confident releases.
Yes. Model-Based Design workflows align with standard CI/CD stages because simulations; tests, including software in the loop (SIL) and processor in the loop (PIL); checks; and code generation can run programmatically and be orchestrated like other pipeline steps. From the pipeline’s perspective, Simulink models and MATLAB code are versioned inputs that produce traceable outputs, including reports, logs, coverage data, and generated artifacts.
Yes. MATLAB and Simulink run on CI/CD platforms that execute command-line tools, scripts, or container jobs, including Azure® DevOps, GitHub® Actions, Jenkins®, and GitLab® CI/CD. Integration typically involves launching MATLAB noninteractively, running scripted workflows, and publishing outputs such as test results, coverage metrics, and reports as pipeline artifacts.
How to Get Started with CI/CD
A CI workflow starts with source control. A runner needs access to the repository, a MATLAB installation or container image, required products, and valid licensing. The pipeline launches MATLAB noninteractively and runs the same scripted steps used in local development.
MATLAB and Simulink are core requirements. Additional products depend on what you want to automate, such as:
- Simulink Test for test execution
- Simulink Coverage™ for coverage metrics
- Embedded Coder® for code generation
- Simulink Check™ for modeling standards
- Polyspace® static analysis tools
To accelerate adoption, teams can use CI Support Package for Simulink, which provides example pipelines, helper functions, and starter configurations.
Start with existing workflows, such as model checks, simulations, tests, or builds, and make them repeatable with scripts. Once the workflow is stable locally, configure your CI system to run the same commands automatically and expand over time.
No. Interactive development continues in the desktop environment. CI changes how build, test, and verification steps are packaged so they can run noninteractively and consistently across environments.
Automating Build, Test, and Verification Workflows
A typical pipeline follows familiar stages: pull, build, test, analyze, and publish. Workflows often include Model Advisor checks, simulation-based testing (including SIL/PIL where applicable), code generation, static analysis, and coverage collection. Each stage produces artifacts that the CI system captures and displays.
Yes. Simulation, test execution, and code generation can be run as scripted CI steps. Pipelines capture outputs such as logs, test results, coverage metrics, and generated code to support review and traceability.
Yes. Containers help standardize runtime environments, reduce drift across agents, and improve reproducibility by starting jobs from a consistent image. Many teams use the MATLAB Dockerfile reference architecture to define pinned releases and required products for noninteractive CI workflows.
Yes. Teams decide which stages to run and implement them as scripts or tasks, aligning pipelines with branching strategies, review checkpoints, and quality gates. Tools such as CI Support Package for Simulink and the Process Advisor app can help generate an initial workflow that teams refine over time.
Supporting Quality, Traceability, and Review
Yes. CI automates verification workflows and produces repeatable outputs, including test results, reports, coverage metrics, and analysis findings. These practices are commonly used in engineering workflows that require traceable, reviewable verification evidence, including work aligned to standards such as DO-178C, IEC 61508, or ISO 26262.
Model Advisor checks and Polyspace static analysis tools run as scripted CI steps and produce structured artifacts, making results consistent, traceable, and easier to review.
CI enforces standards by running the same configured checks on every change and publishing results as durable artifacts. This approach establishes a consistent quality baseline and reduces reliance on manual execution.
Planning for Scale and Infrastructure
Pipelines scale by splitting workflows into independent stages and distributing them across multiple runners. Separating fast checks from long-running simulations or builds helps maintain predictable cycle times.
Yes. CI systems run independent jobs in parallel, enabling teams to scale simulation, testing, and build workloads on available compute and licensing resources.
Governance, Auditability, and Quality Gates
CI produces repeatable evidence on every run and stores versioned artifacts tied to commits and configurations. The result is a durable record of verification outcomes.
Quality gates enforce consistency by blocking changes when required checks fail or when metrics fall below defined thresholds.
Common Use Cases and Adoption Considerations
Common use cases include automated checks, simulation-based testing, code generation, static analysis, coverage, and publishing structured results. These workflows are widely used in domains that rely on simulation and rigorous verification.
Teams use CI to stabilize and scale verification workflows. CI helps maintain consistency, scale automation, and retain evidence across long-running programs.
Common pitfalls include workflows that require interaction, unplanned parallelism that overwhelms resources, and results that remain trapped in logs instead of published as actionable artifacts.
When to Engage with MathWorks
Teams typically reach out when they are:
- Scaling simulation-heavy workflows into CI/CD
- Integrating Model-Based Design into existing DevOps pipelines
- Establishing traceable verification workflows for regulated programs
- Transitioning from manual testing to automated, repeatable pipelines
- Aligning models, tests, and generated code within a single pipeline
If these challenges reflect your current needs, a focused discussion can help you identify a starting point and avoid common adoption pitfalls.
Conclusion
MATLAB and Simulink integrate directly into CI/CD pipelines, enabling teams to automate simulation, testing, code generation, and analysis within a repeatable workflow. For teams applying Model-Based Design with MATLAB and Simulink, CI/CD provides a practical way to improve development speed while maintaining traceable evidence of quality.
