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Why Version Control Matters for MATLAB Users
Version control is a system that keeps track of changes to your files over time. For MATLAB users, it is especially useful when you are working on scripts, functions, and projects that evolve gradually, or when several people edit the same code.
With version control you can record snapshots of your code, move back to earlier versions when something breaks, compare different versions of a file, and collaborate safely without overwriting each other’s work. Even if you work alone, version control gives you a structured history instead of ad hoc file copies like script_v2.m or analysis_final_reallyfinal.m.
MATLAB can integrate with common version control systems, so you can use these tools without leaving the MATLAB environment.
Overview of Common Version Control Systems
The most common version control system you will use with MATLAB is Git. Git is a distributed system, which means each copy of a repository contains the full history. Online services such as GitHub, GitLab, and Bitbucket provide remote hosting and collaboration features on top of Git.
MATLAB also supports Subversion (SVN), a centralized system, but if you are just starting and do not have a specific requirement at work or school, Git is the best choice to learn.
Inside MATLAB you do not need to understand every Git detail to get value from it. Basic operations like creating a repository, committing changes, and synchronizing with a remote can be done through the MATLAB interface once Git is set up on your system.
MATLAB Integration with Git
MATLAB detects when a folder is under version control and provides visual cues and tools inside the environment. After Git is installed on your computer, MATLAB can use it behind the scenes.
In the Current Folder browser you will see icons next to files that indicate their status. For example, new files, modified files, or files that are up to date all have different overlay icons. This gives you a quick overview of which files have changed since the last commit.
MATLAB also provides a context menu for Git operations when you right click within the Current Folder browser or the Editor. Typical actions such as viewing history, comparing revisions, or committing changes are available there. This lets you manage version control without running Git commands manually in a separate terminal.
Creating a Git Repository for a MATLAB Project
The simplest way to start using version control with an existing MATLAB project is to turn your project folder into a Git repository.
First, ensure that your code is organized inside a single main project folder. Then, in MATLAB, navigate to that folder in the Current Folder browser. MATLAB can initialize a Git repository in that folder and begin tracking files there.
Once a repository is created, Git stores all its information in a hidden subfolder named .git in the project root. You normally do not edit this folder manually. From that point on, when you create or modify .m files or other project files, you can select which ones should be tracked and included in commits.
It is a good idea to create a MATLAB Project (using the Projects feature) and associate it with Git. This stores project settings, shortcuts, and the Git configuration together, which helps keep your project reproducible and easier to share.
Basic Version Control Workflow in MATLAB
A typical beginner workflow with Git inside MATLAB follows a simple cycle. You edit your files, test your code, then record a snapshot of the project.
You start by adding or changing .m files, scripts, functions, or data files. MATLAB indicates that a file is modified. When you reach a logical point, for example after finishing a feature or fixing a bug, you stage those changes. Staging means selecting which modified or new files will be part of the next commit.
After staging, you create a commit. A commit is a snapshot of the selected files along with a message describing the change. Good commit messages are short but informative, such as Fix indexing bug in data import or Add plotting function for summary statistics. Commits form a linear history that you can view, compare, and revert.
If you use a remote repository on a service like GitHub, you can push your commits to the remote so they are backed up and shared. When working with others, you periodically pull from the remote to bring in their commits and keep your local copy up to date.
Viewing History and Comparing Versions
MATLAB can display a history of changes for your repository and for individual files. This lets you see when a file was changed, who changed it, and what was changed.
When you open the history for a file, you can compare two versions side by side. MATLAB highlights lines that were added, removed, or modified. This is extremely helpful when you want to understand why a result changed or to track down where an error was introduced.
You can also compare your current file in the Editor to the last committed version. This helps you review your own pending changes before committing, and gives you confidence that the differences you are about to record are exactly what you intended.
Best Practices for Using Version Control with MATLAB
A few simple habits can make version control much more effective for your MATLAB work.
Commit frequently in small, logical units of work. Each commit should represent a coherent step such as implementing a function, fixing a bug, or cleaning up code. Avoid massive commits that bundle unrelated changes, since they are harder to review and revert.
Write meaningful commit messages that tell you why the change was made instead of only what changed. For example, Improve performance of matrix multiplication by vectorization is more helpful than Update code.
Do not commit generated or temporary files. In MATLAB, this might include large cache files, output data that can be regenerated, or autosave files. Use a .gitignore file to list file patterns that Git should ignore. This keeps your repository clean and avoids cluttering history with unimportant changes.
Coordinate with collaborators so that everyone follows a similar structure. Store shared code in the repository, while user specific configuration or large raw data may be kept out of the main repository or in separate locations.
Connecting to Remote Repositories from MATLAB
Connecting your local repository to a remote service allows you to back up your MATLAB projects and collaborate with others. The basic idea is that you have a local copy on your computer and a remote copy on a server, and you synchronize them using Git operations.
When starting a new project, you can either create a remote repository first, then clone it to your computer, or you can initialize a local repository in MATLAB and later connect it to a newly created remote. MATLAB lets you specify the remote URL and remembers it as the place to push and pull changes.
Once a remote is configured, after committing locally you can push to the remote so other collaborators can access the new commits. When others have pushed changes, you pull from the remote to merge their work into your local copy. MATLAB can guide you through simple synchronization tasks, and you can still use command line Git for more advanced scenarios if needed.
For public or teaching projects, remote repositories also serve as a convenient way to share example MATLAB code, exercises, or solutions with others.
Important points to remember:
Use Git as your primary version control system with MATLAB, and keep your code inside a dedicated project folder.
Commit small, logical changes frequently, with clear and informative commit messages.
Avoid committing generated or temporary MATLAB files, and use ignore rules to keep the repository clean.
Use MATLAB’s built in integration to view file status, history, and differences directly in the environment, and connect to a remote repository to back up and share your work.