Error Codes And The Law Of Least Astonishment

Do you know the law of least astonishment? I am not sure of its origin, but I first learned it from the excellent “Tao of Programming.” Simply put, it is the principle that software should always respond to the users in a way that least astonishes them. In other words, printing a document shouldn’t erase it from your file system.

Following the law of least astonishment, what should a program do when it hits a hard error? You might say that it should let the user know. Unfortunately, many systems just brush it under the rug these days.

I think it started with Windows. Or maybe the Mac. The thinking goes that end users are too stupid or too afraid of error codes or detailed messages so we are just leaving them out. Case in point: My wife’s iPhone wouldn’t upload pictures. I’m no expert since I carry an Android device, but I agreed to look at it. No matter what I tried, I got the same useless message: “Can’t upload photos right now. Please try again later.” Not only is this not very informative, but it also implies the problem is in something that might fix itself later like the network.

The real culprit? The iCloud terms of service had changed and she had not accepted the new contract. I have a feeling it might have popped up asking her to do that at some point, but for whatever reason she missed it. Until you dug into the settings and checked the box to agree to those terms, “later” was never going to happen.

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Christmas Lithophanes Make Neat Decorations

Lithophanes are neat little artistic creations that use variations in the thickness of a material to reveal an image when lit from behind. 3D printing is a great way to make lithophanes, and they can make for beautiful Christmas decorations, too!

It’s easy to make lithophane decorations for your Christmas tree with the help of the ItsLitho tool. The online application takes any image you upload, and can generate lithophane geometry that you can 3D print at home. Print your custom bell or bauble, add the printed hooks, and then the final decoration can be backlit to reveal its image by inserting an LED from a string of Christmas lights.

The result is a beautiful, glowing decoration that displays a detailed image when lit up. All you need is a few images and a 3D printer to produce decorations as unique gifts for your family and friends.

We’ve seen the technique put to other uses too, such as in this convincing lamp designed after our very own Moon. Video after the break.

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A Programming Language To Express Programming Frustration

Programming can be a frustrating endeavor. Certainly we’ve all had moments, such as forgetting punctuation in C or messing up whitespace in Python. Even worse, an altogether familiar experience is making a single change to a program that should have resulted in a small improvement but instead breaks the program. Now, though, there’s a programming language that can put these frustrations directly into the code itself into a cathartic, frustration-relieving syntax. The language is called AHHH and it’s quite a scream.

While it may not look like it on the surface, the language is Turing complete and can be used just like any other programming language. The only difference is that there are only 16 commands in this language which are all variants of strings of four capital- or lower-case-H characters. The character “A” in the command “AHHH” starts the program, and from there virtually anything can be coded as a long, seemingly unending scream. The programming language is loosely related to COW which uses various “moos” to create programs instead of screams, and of course is also distantly related to brainfuck which was an esoteric programming language created in order to have the smallest possible compiler.

We can’t really recommend that beginner programmers start to learn this language instead of something more practical like Python, esoteric languages like these can teach us a lot about the way that computers work. This language, for example, lets you code in pixels instead of characters. Others are more for fun such as this language which turns your code into an ’80s rock ballad.

Thanks to [Kyle F] for the tip!

Apple Falling Division

[Paul Curtis] over at Segger has an interesting series of blog posts about calculating division. This used to be a hotter topic, but nowadays many computers or computer languages have support for multiplication and division built-in. But some processors lack the instructions and a library to do it might be less than ideal. Knowing how to roll your own might allow you to optimize for speed or space. The current installment covers using Newton’s algorithm to do division.

Steve Martin had a famous bit about how to be a millionaire and never pay taxes. He started out by saying, “First… get a million dollar. Then…” This method is a bit like that since you first have to know how to multiply before you can divide. The basic premise is twofold: Newton’s method let you refine an estimate of a reciprocal by successive multiplications and then multiplying a number a reciprocal is the same as dividing. In other words, if we need to divide 34 by 6, you could rewrite 34/6 to 34 * 1/6 and the answer is the same.

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Cracking The Spotify Code

If you’ve used Spotify, you might have noticed a handy little code that it can generate that looks like a series of bars of different heights. If you’re like [Peter Boone], such an encoding will pique your curiosity, and you might set out to figure out how they work.

Spotify offers a little picture that, when scanned, opens almost anything searchable with Spotify. Several lines are centered on the Spotify logo with eight different heights, storing information in octal. Many visual encoding schemes encode some URI (Uniform Resource Identifier) that provides a unique identifier for that specific song, album, or artist when decoded. Since many URIs on Spotify are pretty long (one example being spotify :show:3NRV0mhZa8xeRT0EyLPaIp which clocks in at 218 bits), some mechanism is needed to compress the URIs down to something more manageable. Enter the media reference, a short sequence encoding a specific URI, generally under 40 bits. The reference is just a lookup in a database that Spotify maintains, so it requires a network connection to resolve. The actual encoding scheme from media reference to the values in the bars is quite complex involving CRC, convolution, and puncturing. The CRC allows the program to check for correct decoding, and the convolution enables the program to have a small number of read errors while still having an accurate result. Puncturing is just removing bits to reduce the numbers encoded, relying on convolution to fill in the holes.

[Peter] explains it all in his write-up helpfully and understandably. The creator of the Spotify codes stopped by in the comments to offer some valuable pointers, including pointing out there is a second mode where the lines aren’t centered, allowing it to store double the bits. [Peter] has a python package on Github with all the needed code for you to start decoding. Maybe you can incorporate a Spotify code scanner into your custom Spotify playing mini computer.

Watch Blender Plugin Make Animated PCB Traces (and More)

[Staacks]’s Blender plugin to animate growth is behind the sweet animation seen above. It’s an add-on that cleverly makes creating slick growth animations easier when using Blender. It isn’t limited to PCB images either, although they do happen to make an excellent example of the process.

The add-on isn’t limited to animating PCB traces.

The idea is that one begins with an image texture with a structure showing a bunch of paths (like a maze, or traces on a PCB), and that gets used as an input. The plugin then uses a path finding algorithm to determine how these paths could grow from an origin point, and stores the relevant data in the color channels of an output image. That output is further used within Blender as the parameters with which to generate the actual animation, resulting in the neat self-creating PCB seen above. That PCB isn’t just for show, by the way. It’s the PCB for [Staacks]’s smart doorbell project.

Blender is an amazingly comprehensive tool for modeling and animation, and while we’ve covered using it to create high-quality KiCad renders, this kind of animation is really something else.

Here is the GitHub repository for the Blender growth tool if you’re interested in giving it a spin. If you’d like to see more first, watch the video embedded below for a showcase of what it’s capable of, and how it works.

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A Super Speedy Lightweight Lossless Compression Algorithm

[Dominic Szablewski] was tinkering around with compressing RGB images, when he stumbled upon idea of how to make a simple lossless compression algorithm, resulting in the Quite OK Image Format, which seems to offer comparable file sizes to the PNG format but is so simple it runs up to 50 times faster for compression and up to four times faster for decompression. Implementation can be achieved with a miniscule 300 lines of C. Need a bit more detail on the real-world performance? Well [Dominic] has that covered too, with a complete set of benchmarks for your perusal.

Image formats are one of those things these days that are designed by consortium, with so much complexity wedged in making it hard to implement with limited resources, so we find it very refreshing to see someone going back to basics and producing something super lightweight, and plenty good enough in practical terms.

Other uses for the algorithm could be for super simple video compression, for applications where resource is tight and some low-effort bandwidth reduction would be beneficial. Implementation in a small FPGA would also be quite straightforward, since the memory requirement is quite low also.

The project is very new and already there are some tweaks happening to the format, so the GitHub project code may change without warning to reflect any corrections [Dominic] feels necessary.

Thanks [David] for the tip!