Continuing the new tradition of clickbaity titles, let’s talk about explicitness. It’s a subject that comes up when bike-shedding language and API designs. Pointing out that a construct or a function exhibits implicit behaviour is often taunted as an ultimate winning argument against it.

There are two problems with such line of reasoning. First of all, people claim to care about feature being explicit but came to accept a lot of implicit behaviour without batting an eye. Second of all, no one actually agrees what the terms mean.

In this article I’ll demonstrate those two issues and show that ‘explicit over implicit’ is the wrong value to uphold. It’s merely a proxy for a much more useful goal interfaces should strive for. By the end I’ll demonstrate what we should look at instead.

Updated in October 2021 to include direct comparison shift usage between Dvorak and Programmer Dvorak layouts.

A few years age I’ve made a decision that had the potential to change the course of history. Had I went a different path, the pl(dvp) layout might have never seen the light of day. But did I make a wise choice? Or had I chosen poorly?

I’m talking of course about the decision to learn Programmer Dvorak rather than a regular Dvorak keyboard layout. The main differences between the two is that in the former digits are entered with Shift key pressed down which allows several punctuation marks often used when programming to be typed without the need to reach for Shift. The hypothesis goes that developers use digits less often thus such design optimises the layout for them.

To test this I’ve grabbed all my git repositories and constructed a histogram of characters used in text files present there. Since letters are on the same position on both layouts in question, only digits and punctuation characters are compared on the histogram:

Some years ago, during a friendly discussion about C++, a colleague challenged me with a question: what’s the best way to represent a sequence of numbers if delete operation is one that needs to be supported. I argued in favour of a linked list suggesting that with sufficiently large number of elements, it would be much preferred.

In a twist of fate, I’ve been recently discussing an algorithm which reminded my of that conversation. Except this time I was the one arguing against a node-based data structure. Rather than ending things at a conversation, I’ve decided to benchmark a few solutions to make sure which approach is the best.

The problem

The task at hand is simple. Design a data structure which stores a set of words, all of the same length, and offers lookup operation which returns all words matching globs in the form ‘prefix*suffix’. That is, words which start with a given prefix and end with a given suffix. Either part of the pattern may be empty and their concatenation is never longer than length of the words in the collection. Initialisation time and memory footprint are not a concern. Complexity of returning a result can be assumed to be constant.

In this article I’me going to describe possible solutions — some using a boring vector while others taking advantage of an exciting prefix tree — and benchmark the implementations in an ultimate battle between contiguous-memory-based and a node-based containers.

‘I’m using slock as my screen locker,’ a wise man once said. He had a beard so surely he was wise.

‘Oh?’ his colleague raised a brow intrigued. ‘Did they fix the PAM bug?’ he prodded inquisitively. Nothing but a confused stare came in reply. ‘slock crashes on systems using PAM,’ he offered an explanation and to demonstrate, he approached a nearby machine and pressed the Return key.

Screens, blanked by a locker a few minutes prior, came back to life, unlocked without the need to enter the password.

I’ve written about L*a*b* so it’s only fair that I’ll also describe its twin sister: the L*u*v* colour space (a.k.a. CIELUV). The two share a lot in common. For example, they use the same luminance value, base their chromaticity on opponent process theory and each of them has a corresponding cylindrical LCh coordinate system. Yet, despite those similarities — or perhaps because of them — the CIELUV colour space is often overlooked.

Even though L*a*b* is getting all the limelight, L*u*v* model has its advantages. Before we start comparing the two colour spaces, let’s first go through the conversion formulæ.

Here’s a puzzle: What does the following C++ code output:

#include <cstdio>
#include <string>

struct Foo {
	Foo(unsigned n = 1) {
		std::printf("Hell%s,", std::string(n, 'o').c_str());
	}
	~Foo() {
		std::printf("%s", " world");
	}
};

static constexpr double pi = 3.141592653589793238;

int main(void) {
	Foo foo();
	Foo bar(unsigned(pi));
}

In part one we’ve looked at the ARG_MAX parameter on Linux-based systems. We’ve established experimentally how it limits arguments passed to programs and what influences the value. This time, we’ll look directly at the source to verify our findings and see how ARG_MAX looks from the point of view of system libraries and kernel itself.

Anyone who uses a screen locker surely can recall a situation where they approached their computer and started typing their password to unlock it even though it was never locked. Even if the machine is configured to lock automatically after a period of inactivity, there may be situations when power saving blanks the monitor even before the automatic locking happens.

If one’s lucky, they realise their mistake in time before hitting Return in a chat window. It’s not uncommon however that one ends with the password blasted into ether over IRC or Google Docs; lazy people might ignore the secret getting saved in their shell history file but even that should facilitate, often annoying, password change.

What if I told you there’s a way to avoid those problems? A one simple trick which will eliminated at least some forms of possible leaks. Simply prefix all your passwords with /! (slash followed by an exclamation mark).

No, your eyes are not deceiving you. This website has gone through a redesign and in the process gained a dark mode. Thanks to media queries, the darkness should commence automatically according to reader’s system preferences (as reported by the browsers). You can also customise this website in settings panel in top right (or bottom right).

What are media queries? And how to use them to adjust website’s appearance based on user preferences? I’m glad you’ve asked, because I’m about to describe the CSS and JavaScript magic that enables this feature.

Media queries overview

body { font-family: sans-serif; }
@media print {
	body { font-family: serif; }
}

Media queries grew from the @media rule present since the inception of CSS. At first it provided a way to use different styles depending on a device used to view the page. Most commonly used media types where screen and print as seen in the example on the right. Over time the concept evolved into general media queries which allow checking other aspects of the user agent such as display size or browser settings. A simple stylesheet respecting reader’s preferences might be as simple as:

body {
	/* Black-on-white by default */
	background: #fff;
	color: #000;
}
@media (prefers-color-scheme: dark) {
	/* White-on-black if user prefers dark colour scheme */
	body {
		background: #000;
		color: #fff;
	}
}

That’s enough to get us started but not all browsers support that feature or provide a way for the user to specify desired mode. For example, without a desktop environment Chrome will report light theme preference and Firefox users need to go deep into the bowels of about:config to change ui.systemUsesDarkTheme flag if they are fond of darkness. To accommodate such situations, it’s desirable to provide a JavaScript toggle which defaults to option specified in system settings.

Fortunately, media can be queried through JavaScript and herein I’ll describe how it’s done and how to marry theme switching with browser preferences detection. TL;DR version is to grab a demonstration HTML file which includes a fully working CSS and JavaScript code that can be used to switch themes on a website.

After writing about conversion between sRGB and XYZ colour spaces I’ve been asked about a related process: moving between sRGB and CIELAB (perhaps better known as L*a*b*). As this may be of interest to others, I’ve decided to go ahead and make an article out of it. I’ll also touch on CIELCh_ab which is a closely related colour representation.

The L*a*b* colour space was intended to be perceptually uniform. While it’s not truly uniform it’s nonetheless useful and widely used in the industry. For example, it’s the basis of the ΔE*₀₀ colour difference metric. LCh_ab aim to make L*a*b* easier to interpret by replacing a* and b* axes with more intuitive chroma and hue parameters.

Importantly, the conversion between sRGB and L*a*b* goes through XYZ colour space. As such, the full process has multiple steps with a round trip conversion being: sRGB​→​XYZ​→​L*a*b*​→​XYZ​→​sRGB. Because of that structure I will describe each of the steps separately.