Using Tracealyzer for Embedded Systems Analysis

In my latest research project I’m using the NXP FRDM-MCXN947 board. As part of that project I have to collect and export application trace data for later analysis. In that project I’m using the the Tracealyzer product from Percepio.

Trace Data in Percepio Tracealyzer
Trace Data in Percepio Tracealyzer

In this article I describe different ways to export trace data from the embedded target: using generic GDB commands or with an trace exporter in VS Code.

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Semihosting with LinkServer in VS Code

For an university research project, I need to write some console output and the same time write a file with data from the embedded board to the host. A logical choice for this is using semihosting.

Semihosting with LinkServer in VS Code
Semihosting with LinkServer in VS Code
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Debug C/C++ Apps in Docker with VS Code: A Step-by-Step Guide

Debugging a C/C++ application inside a Docker Container using VS Code is surprisingly easy.

This article shows the needed steps.

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Tutorial: Creating Self-Contained MCUXpresso SDK Projects

In Tutorial: Getting Started with MCUXpresso SDK – Repositories with VS Code and Tutorial: Getting Started with MCUXpresso SDK – west I showed how to get the MCUXpresso SDK. In this article it is about tweaking and streamlining the project.

The result is a clean, portable and self-contained MCUXpresso SDK project.

VS Code with streamlined NXP MCUXpresso project
VS Code with streamlined NXP MCUXpresso project
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Tutorial: Getting Started with MCUXpresso SDK – Tool Installation

The engineering and development landscape is constantly changing. This includes the embedded tooling and SDKs.

Back in the year 2017 I have used the version 2 (see Tutorial: Using Eclipse with NXP MCUXpresso SDK v2 and Processor Expert). Back then, it was Eclipse with make. Now we are in 2026 and things have changed to VS Code, cmake, ninja, python and west.

VS Code with MCUXpresso Installer
VS Code with MCUXpresso Installer

Luckily, although more and different tools are needed these days, the installation experience has improved significantly. It has shifted from installing multiple different tools to a streamlined installation process.

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Optimizing Embedded Development with VS Code and DevContainer

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.

VS Code running with DevContainer
VS Code running with DevContainer

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.

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MCU-Link with Cortex-Debug and LinkServer

The MCU-Link is a small and inexpensive $10 CMSIS-DAP debug probe from NXP. It can work with OpenOCD, but has better target support using the NXP LinkServer which implements a gdb server. This makes it an ideal combination for scripting or automated testing.

MCU-Link as external debug probe
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Semihosting with VS Code on RP2040

With semihosting I can use standard I/O function like printf() and I can read and write data on the host through the debug connection. If used with care, this is a great feature especially for unit testing.

Raspberry Pi Pico-W (RP2040) board
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VS Code: Virtual Environments for Embedded Development with Conda

Developing for an embedded target means using a certain version of GNU compiler, debugger and other tools. The challenge gets bigger if working with multiple different tool chains and environments.

Conda in VS Code

Conda is package, dependency and environment management tool. While it is heavily used for Python and Data Science development, it is surprisingly working very well to set up and managing environments for embedded development. Conda is great for managing non-Python dependencies and setups.

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VS Code: Telemetry-free VSCodium

“There is no such thing as a free lunch.”

https://en.wikipedia.org/wiki/No_such_thing_as_a_free_lunch

And this applies to VS Code and many of its extensions. You agree to the licensing conditions, and you pay with your data.

VS Code source code is MIT licensed, but the binaries you can download and install have telemetry built in: you are giving Microsoft your usage data in return for using VS Code.

If you are concerned about this, and looking for free and libre open source binaries of VS Code, then have a look at MIT-Licensed VSCodium.

https://vscodium.com
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