Windel Bouwman

Embedded systems are hard to debug. Complex systems have a lot of variables. When debugging those systems, we often log data into some files, and visualize them later on, using excel, matplotlib or something else.

This talk is about tracing and logging. What are the options we have as embedded software developers? I will present the lognplot tool, a project to plot incoming data on the fly.

Embedded systems are hard to debug. Complex systems have a lot of variables. When debugging those systems, we often log data into some files, and visualize them later on, using excel, matplotlib or something else.

This talk is about tracing and logging. What are the options we have as embedded software developers? I will present the lognplot tool, a project to plot incoming data on the fly. There are two implementations, one in python, and one in rust with gtk-rs. The data is stored internally in a zoomable format, allowing large sets of data to be browsed easily.

During the talk you will learn how to draw a chart, and how to aggregate large sets of data into summaries.

I will demo a STM32 serial wire viewer output connected to this tool to enable live tracing of an embedded system.

Rust is a relatively new programming language aimed as a safe competitor of C. There are already attempts to write extension modules in rust and load them into CPython. A whole new approach would be to re-implement the Python language in rust. This is what RustPython is about.

RustPython is a relatively new project. The aim of the project is to create a Python interpreter written entirely in Rust. Until now we used many of the language features available in rust, such as vectors, hashmaps, iterators. To implement standard library modules, we would like to wrap existing rust crates. This is what we did with the json module for example.

During this talk, we will demo the current state of the art of the project. We will take a dive into the internals of RustPython, from parsing, compilation, bytecode to actual execution on the Python virtual machine. Next to this we will cover the growing community, and the road ahead!

Ppci is a compiler written entirely in Python. This allows for easy compiler development, portability and installation. The compiler is able to process C code into WASM, WASM into xtensa code, but there are more possible code paths. During this session a demo will be shown on how to compile some webassembly to the riscv platform.

The ppci project was started by the need for a better system level programming language then C. The compiler is implemented in python, and hence is not very fast. On the other hand, the compiler is portable and is easier to develop due to being implemented into a higher level language. Currently it supports msp430, x86, xtensa, avr, arm, open risc and stm8 computer architectures, in various levels of maturity. The supported languages are C3 and brainfuck. Language support for C is a work in progress.

The C3 language was the starting point for the compiler, aiming at being a better version of C. It has no header files, but features a more modular approach like C# and java. Furthermore its syntax is context free, making it easier to parse using standard compiler tools.

The backend of the compiler consists of a code generator featuring both instruction selection and register coloring algorithms. The output of the compiler is an instruction stream, which can be serialized as text or in binary form.

Possible uses of this library are:

Compile code and include it into the currently running python instance
Create ctypes bindings for C code by making use of the C parser frontend
Create a programming language using ply/textx and generate machine code from it using ppci

During this session, we will explore the various parts of the ppci library and have a good overview what it is capable of.

The residential heating division of Bosch thermotechnology is developing products for domestic hot water and central heating in homes. These products include an app (iOS and Android) connected smart room thermostat and a control unit for controlling a boiler appliances. During this presentation, we want to share our lessons learned by explaining our testing strategy and the usage of robotframework.

Specifically we will share our story about:

• Our usage of robotframework to test the mobile apps we develop. Show framework architecture for combined on target and simulator testing. How to test on several different real phones.
• The testing of the internet connected room thermostat with robotframework. How to handle (stub, mock or fake) the different (radio) interfaces.
• How we setup robotframework to test the embedded software with accelerated time. Show the architecture of the embedded software and how we can run this on both target and PC platform. How the modelled system dynamics were used during testing.
• Do's and dont's when testing a product during development.

About the authors:

• Alex van de Schootbrugge is an embedded software engineer working on the smart room thermostat.
• Windel Bouwman is an embedded software engineer working on the control units for boiler appliances.