Recently I have been asked “How can I debug a Linux application with VS Code?”. I’m covering that topic in my ‘Embedded Application Development Course on Linux”.
I realized, that I have never covered that topic in any of my blog articles. So here we go: I show how easy it is to use VS Code to debug a Linux application. You can use this for example with an Raspberry Pi. Or for example the NXP i.MX93 which I’m using in this article.
Continue readingThe latest release of the NXP LinkServer supports ARM 64bit (Debian) besides Windows, Linux and MacOS. With this, I can now develop on an NXP i.MX board. Plus, this enables an inexpensive way for automated on-target tests and CI/CD.
Docker or Development Container are great for isolation. And they work very well with things outside which are TCP/IP based. But most debug probes are USB only. Docker container don’t work well with USB. In Remote Debugging with DevContainer and VS Code, I showed how to use USB based debug probes. I demonstrated using them with an IP connection. In this article I show how Windows USB devices can be used from a container, with the help of usbipd.
I recently upgraded from Win10 to Win11. Windows 10 was not great for building performance compared to Linux. And I feel that with Windows 11 things got worse too.
Dev Container in VS Code uses docker-based environments. This enables me using a full-featured development environment, with isolated dependencies. This is especially very useful for development in the embedded systems space. There I have to use many different SDKs, toolchains and libraries. Using Dev Containers is super easy. But file I/O operations with building etc/is not that great.
The solution is to use a Docker Volume with VS Code and Dev Container:
I’m shifting more and more of my CI/CD testing infrastructure using the LinkServer runner. One reason is the LinkServer runner can run the test on-target. It can also collect GNO gcov coverage information at the same time. LinkServer is a suite of software tools for launching and managing GDB servers for NXP debug probes.
Remote debugging an embedded target is very useful: I don’t need a direct debug probe or USB cable connection. Instead, I’m using a network connection (wired or even wireless) over TCP/IP to talk to the debug probe and target. That way I can place the debug probe and target system away from my desk.
In Debugging ARM Cores with IP based Debug Probes and Eclipse I have used IP-based debug probes. This is a logical path, but expensive.
In Remote Debugging with USB based JTAG/SWD Debug Probes I showed how normal USB based debug probes can be used. This approach uses a remote host machine (e.g. desktop machine or notebook). This approach is still expensive, not scalable and the host machine needs a lot of space too.
So what if I use a Raspberry Pi instead? The RPi is small, inexpensive and ideal for such a task. Additionally, I can easily use it to build a test or debug farm. In this article, I show the use of the Raspberry Pi for remote debugging. A sub $20 or embedded target debug probe can be employed.
Embedded System have a lifetime of 10 or 15 years. During that time the software and tools has to be maintained. This can be very challenging. Who knows if that compiler or tool used is still available in 10 years from now? Additionally installing and configuring the tool chain and environment for a new team member is difficult. Even worse: using a different host operating system for the cross development can produce different results or introduce issues.
One solution for all these problems is to use Docker images and containers. I can pack all the necessary tools and software into a virtual environment and container. But developing inside a container comes with many challenges. In this article I’ll show how Visual Studio Code or VS Code makes working with containers very easy. In this article I show how easy it is to use modern development tools and methodologies for embedded development.
Continue readingIn CI/CD for Embedded with VS Code, Docker and GitHub Actions, I used GitHub to build a pipeline. This setup supports continuous integration within a CI/CD environment.
This time, let’s do a similar thing. But instead of GitHub, I use GitLab with VS Code. And I use it for a project where three different MCUs are used: the Raspberry Pi Pico-W, an Espressif ESP32 plus the NXP K22FX512 on the Sumo robot:
The year 2024 is coming to its end, time for a Year-End-Processor-Expert-Component-Release.
Also, this is now the 10th anniversary of the releases on Sourceforge, starting with https://mcuoneclipse.com/2014/10/21/mcuoneclipse-releases-on-sourceforge/ back in 2014.
Continue readingThe new year 2024 is coming, so time to close the current year with a new release: I’m pleased to announce a new release of the Processor Expert components, available on SourceForge and GitHub.
MCU on Eclipse 