What is the best approach to debugging an embedded system?

Effectively debugging an embedded system involves a systematic approach. Begin by thoroughly reviewing the code and documentation to understand the system architecture and potential issues. Utilize debugging tools, such as hardware debuggers and software emulators, to trace and identify errors. Employ strategic logging and breakpoints to isolate problematic code sections. Regularly test the system in various scenarios to replicate and identify elusive bugs. Collaborate with team members to leverage diverse perspectives and problem-solving approaches for a comprehensive debugging strategy.

One of the most critical steps in debugging an embedded system is to design it with debugging in mind from the outset. This involves incorporating features and strategies into the design that facilitate debugging activities throughout the development lifecycle. For example, implementing modular and well-organized code structures enables easier isolation and identification of issues during debugging. Including built-in diagnostic capabilities, such as logging mechanisms or debug output interfaces, provides valuable insights into system behaviour. Additionally, designing for testability by incorporating hardware and software test points and instrumenting the code for traceability enhances the effectiveness of debugging efforts.

Designing for debugging is not hard however if the software engineer is left out of the planning stage, this will be harder. The two most essential items are debug pins and a serial interface separated from the JTAG port. The debug pins and serial ports should have some kind of connector where the interface can be brought outside of the device. Debug pins are great to toggle to confirm the software has reached certain locations in the code. I considered printf to be one of the most powerful debug tools. Using printf to a serial terminal is very helpful in determining code locations, actions, and variable states.

Various functionalities include setting breakpoints to pause code execution at specific points, stepping through the code line by line to observe its behaviour, and examining variables and memory contents in real-time. Additionally, debuggers often offer features such as watchpoints to monitor changes to specific memory locations and stack traces to analyse the call hierarchy of functions. By leveraging these capabilities, developers can gain valuable insights into the runtime behaviour of their code, diagnose issues efficiently, and facilitate the debugging process to ensure the robustness and reliability of their software.

While it's obvious to use a debugger that can connect through some kind of hardware interface such as JTAG or SWD, you need to pick the right eco-system that allows debugging. For example microchip on certain processors can only allow only two breakpoints compared to STI where many more can be used. I personally find that the real time output of variables to be very useful. So work with the hardware team to pick the right processor and debugging environment.

Write your code so that the parts interfacing with the hardware are separate from the rest of the code. Then you can replace those by simulated layers, as in a Software-in-the-loop or Hardware-in-the-loop simulations. The ability to compile and run your code on a desktop PC with real or simulated hardware will make debugging much easier, as debugging tools on a PC are much more powerful. In addition you will be able to record more data, program reproducible tests and even "pause time" if you have simulated hardware.

Simulation involves creating a software-based representation of the target device or system, allowing developers to execute code and observe its behaviour in a controlled environment. In contrast, emulation utilises hardware-based models to mimic the behaviour of the target device more accurately. Both techniques offer benefits such as testing code without access to physical hardware, faster iteration cycles, and enhanced debugging capabilities. However, while simulation may sacrifice accuracy for speed, emulation provides a closer approximation of real-world performance. By leveraging both, developers can validate code functionality, assess performance, and identify potential issues before deploying software to the target platform.

I have started using python to write simulations of algorithms for my devices. For example, I was working on a motor controller that needed to limit the current. Instead of putting the electronics and motor at risk, I wrote simulations in python to develop the right control algorithm. I use the pygal module for graphing for my output.

I had great success and seeing sensor behavior by graphing the output data from a device using the serial port. By streaming the sensor values from the device, I can see behavior changes for developing control algorithms. Data can be captured and plotted using various tools such as excel, python, and tables. My best success is writing a real time interface control program using C# on windows. I was able to graph the data using the built-in chart module in C# winforms.

I swear that 60% of the code is handling user errors or fault tolerance . It's important to do the engineering analysis of fault tolerance before you design the system or even write the software. Doing this after the fact creates unnecessary complexity in the code.