File Exchange

image thumbnail


version (541 KB) by Paul Peeling
Code and Examples for "Developing Robust MATLAB Code"


Updated 08 Jun 2018

GitHub view license on GitHub

As the size and complexity of your MATLAB application increases, you want make sure to structure software projects well, ensuring users can run code without encountering unexpected behaviour or errors, for example. In this session at the MATLAB Computational Finance Conference 2018, we learned about relevant advanced MATLAB software development capabilities, including error handling, object-oriented programming (OOP), unit testing, version control, and change tracking.

Cite As

Paul Peeling (2020). mathworks/robust-matlab-2018 (, GitHub. Retrieved .

Comments and Ratings (1)

Azy Rz

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Inspired: Cluster-Head based Routing in VANET