Upgrade MATLAB and Simulink

Upgrade MATLAB and Simulink

Best practices for migrating to newer MATLAB releases

Stay current with the latest software version of MATLAB® and Simulink® for new functionality, improved performance, and current regulatory compliance. Most users upgrade every release, but you can explore other cadence options that work best for your organization.

Read the MATLAB and Simulink Version Upgrades white paper to learn about the upgrade process, including a roll-out plan for large organizations and a checklist for quick reference.

“When new tools become available to improve your process, you have to maintain a growth opportunity to make use of them.”

Danilo Viazzo, Millennium Engineering and Integration Company


You can use various tools to assist your upgrade depending on your current software version and the upgrade version. After R2017a, use the Upgrade Project tool to upgrade all models in one project or upgrade all project models, libraries, and MATLAB code to the latest release. Between R2012b through R2016b, use Upgrade Advisor to upgrade your models.

Other tools and resources are available:



  • Simulink Performance Advisor: Produces a report that recommends better configuration settings, implements them automatically, and runs simulations in accelerator mode to improve simulation performance
  • Simulink Model Comparison: Compares models between two versions and merges differences
  • Simulink Test: Provides tools for authoring, managing, and executing systematic, simulation-based tests of models, generated code, and simulated or physical hardware
  • Run tests in multiple releases of MATLAB: Enables you to test functionality from later releases while running the tests in your preferred release of Simulink
  • Equivalence test: Compare functional equivalence for two Simulink model simulations that were run in different releases
  • Requirements Toolbox: Lets you author, link, and validate requirements within MATLAB or Simulink
  • Requirements-based testing: Provides model verification, interpreting, and reporting test results
  • Simulink Coverage: Performs model and code coverage analysis that measures testing completeness in models and generated code
  • Code coverage: Enables you to collect code coverage metrics during software-in-the-loop (SIL) and processor-in-the-loop (PIL) simulations
  • Continuous integration (CI): Use CI to automatically test and verify MATLAB code and Simulink models, and generate code in the new release

Embedded Coder

“You see these new options and you think about things differently. It just gets you really excited about what you do.”

Tom Allen, Triumph Engine Control Systems LLC