Putting The Firmware In Your Firmware

September 15, 2020 by Kerry Scharfglass 12 Comments

Performing over-the-air updates of devices in the field can be a tricky business. Reliability and recovery is of course key, but even getting the right bits to the right storage sectors can be a challenge. Recently I’ve been working on a project which called for the design of a new pathway to update some small microcontrollers which were decidedly inconvenient.

There are many pieces to a project like this; a bootloader to perform the actual updating, a robust communication protocol, recovery pathways, a file transfer mechanism, and more. What made these micros particularly inconvenient was that they weren’t network-connected themselves, but required a hop through another intermediate controller, which itself was also not connected to the network. Predictably, the otherwise simple “file transfer” step quickly ballooned out into a complex onion of tasks to complete before the rest of the project could continue. As they say, it’s micros all the way down.

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Grasp Kotlin’s Coroutines With This Short Tutorial

August 31, 2020 by Donald Papp 1 Comment

Kotlin is a relatively new programming language; a derivative of Java with lots of little handy functional bits such as coroutines. [Foalyy] is porting an app to Android and learning Kotlin at the same time, and after wrapping their mind around coroutines, has written up a concise five-part tutorial on them.

Coroutines in Kotlin are a way to simplify writing asynchronous code, which is code that doesn’t necessarily execute in the order it is written. Coroutines are like light-weight threads that can be launched and managed easily, making it simpler to bridge together blocking and non-blocking code. (However, coroutines are not threads. They are more akin to suspending functions that play very well together.)

[Foalyy] found that the official Kotlin documentation on coroutines went into great detail on how coroutines function, but wanted a more bottom-up approach to understanding how they work and can be used. Luckily for anyone who thinks the same way, [Foalyy] wrote it all up and begins with a great recap of important elements, but if you prefer you can jump straight to the examples.

Kotlin has been around for a while, and readers with sharp memories may recall it was featured in this excellent introduction to what neural networks are and how they work.

Assembly Language For Real

August 25, 2020 by Al Williams 48 Comments

We all probably know that for ultimate control and maximum performance, you need assembly language. No matter how good your compiler is, you’ll almost always be able to do better by using your human smarts to map your problem onto a computer’s architecture. Programming in assembly for PCs though is a little tricky. A lot of information about PC assembly language dates back from when assembly was more common, but it also covers old modes that, while still available, aren’t the best answer for the latest processors. [Gpfault] has launched a series on 64-bit x86 assembly that tries to remedy that, especially if you are working under Windows.

So far there are three entries. The first covers setting up your toolchain and creating a simple program that does almost nothing. But it is a start.

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Frances Allen Optimised Your Code Without You Even Knowing

August 25, 2020 by Ben James 9 Comments

In 2020, our digital world and the software we use to create it are a towering structure, built upon countless layers of abstraction and building blocks — just think about all the translations and interactions that occur from loading a webpage. Whilst abstraction is undoubtedly a great thing, it only works if we’re building on solid ground; if the lower levels are stable and fast. What does that mean in practice? It means low-level, compiled languages, which can be heavily optimised and leveraged to make the most of computer hardware. One of the giants in this area was Frances Allen, who recently passed away in early August. Described by IBM as “a pioneer in compiler organization and optimization algorithms,” she made numerous significant contributions to the field. Continue reading “Frances Allen Optimised Your Code Without You Even Knowing” →

Don’t Let Endianness Flip You Around

August 4, 2020 by Maya Posch 26 Comments

Most of the processor architectures which we come into contact with today are little-endian systems, meaning that they store and address bytes in a least-significant byte (LSB) order. Unlike in the past, when big-endian architectures, including the Motorola 68000 and PowerPC, were more common, one can often just assume that all of the binary data one reads from files and via communication protocols are in little-endian order. This will often work fine.

The problem comes with for example image formats that use big-endian formatted integers, including TIFF and PNG. When dealing directly with protocols in so-called ‘network order’, one also deals with big-endian data. Trying to use these formats and protocol data verbatim on a little-endian system will obviously not work.

Fortunately, it is very easy to swap the endianness of any data which we handle. Continue reading “Don’t Let Endianness Flip You Around” →

Busting GPS Exercise Data Out Of Its Garmin-controlled IoT Prison

July 28, 2020 by Mike Szczys 21 Comments

If you take to the outdoors for your exercise, rather than walking the Sisyphusian stair machine, it’s nice to grab some GPS-packed electronics to quantify your workout. [Bunnie Huang] enjoys paddling the outrigger canoe through the Singapore Strait and recently figured out how to unpack and visualize GPS data from his own Garmin watch.

By now you’ve likely heard that Garmin’s systems were down due to a ransomware attack last Thursday, July 23rd. On the one hand, it’s a minor inconvenience to not be able to see your workout visualized because of the system outage. On the other hand, the services have a lot of your personal data: dates, locations, and biometrics like heart rate. [Bunnie] looked around to see if he could unpack the data stored on his Garmin watch without pledging his privacy to computers in the sky.

Obviously this isn’t [Bunnie’s] first rodeo, but in the end you don’t need to be a 1337 haxor to pull this one off. An Open Source program called GPSBabel lets you convert proprietary data formats from a hundred or so different GPS receivers into .GPX files that are then easy to work with. From there he whipped up less than 200 lines of Python to plot the GPS data on a map and display it as a webpage. The key libraries at work here are Folium which provides the pretty browsable map data, and Matplotlib to plot the data.

These IoT devices are by all accounts amazing, listening for satellite pings to show us how far and how fast we’ve gone on web-based interfaces that are sharable, searchable, and any number of other good things ending in “able”. But the flip side is that you may not be the only person seeing the data. Two years ago Strava exposed military locations because of an opt-out policy for public data sharing of exercise trackers. Now Garmin says they don’t have any indications that data was stolen in the ransomware attack, but it’s not a stretch to think there was a potential there for such a data breach. It’s nice to see there are Open Source options for those who want access to exercise analytics and visualizations without being required to first hand over the data.