You'll have noticed I haven't updated much recently. Even when I did, if was with distinctly non-tech stuff. The reason being I've been busy. Not "I've got a big to-do list" busy or "I've had a couple of browser tabs open for a few weeks that I'll get round to eventually" busy, either. I've got a text-file to-do list that's been open, unsaved in the background since January 2017 and there are a couple of background tabs I've been meaning to get round to reading since late 2014. Really.

What's been keeping me busy?

Easy answer: HERE Tracking.

A couple of years back, a few of us got interested in how IoT devices could work with location. What's the smallest, simplest device we can connect to the cloud and pin point on a map? Within a few weeks, we had a basic cloud and at CES in January this year, we launched a fully-fledged product. In that time, I've moved from 'prototyper who built version 0.1 on his laptop during the Christmas holidays' to something roughly equivalent to CTO of a medium-sized tech company. Not bad.

What's it do?

In essence, a small IoT device with some combination of GSM, WiFi and Bluetooth does a scan to find out what wireless networks, Bluetooth beacons and cell towers are visible and how strong they appear. They send their scan to HERE Tracking where it gets resolved into a latitude/longitude and then saved. The best bit is that it works indoors and outdoors.

Look, we've even got our own shiny video with cheesy voiceover!

And another that shows what it actually does!

There are a bunch of other features as well such as geofences, notifications, filtering, etc. but the main focus is this large-scale ingestion and storage of data.

At this point, our original Tracking team has grown to include HERE Positioning (the clever people who actually figure out where the devices are) and HERE Venues (we recently acquired Micello). By combining, the Tracking, Positioning and Venues bits together, we can follow one of these devices from one factory, across the country on a truck or train, overseas, into another country, into another factory, out into a shop... and so on.

Seeing as both Prolog and CSS are declarative languages, I found myself wondering if it would be possible to create a mapping from one to the other. It was an interesting thought experiment that quickly found itself being turned into code.

Way back when, Prolog was actually one of the first languages I learned to program in. It had been a while since I'd last used it for anything (a chess endgame solver in high school, I think) so I looked up an online tutorial. The following example is derived from section 1.1. of Learn Prolog Now

Simple rules

If you think of Prolog facts as denoting true/false attributes of elements, you can consider every known item in a KnowledgeBase (KB) as a DOM Element. For example:

mia.

Is equivalent to:

<div id="mia"></div>

While

woman(mia).

Equates to:

<div id="mia" class="woman"></div>

You can make multiple statements about an item in the KB:

woman(jody).
playsAirGuitar(jody).

Which is mapped to:

<div id="jody" class="woman playsAirGuitar"></div>

You can then represent these facts using visual attributes:

.woman {
  background: yellow;
}
.playsAirGuitar {
  border: 1px solid black;
}

The only real issue is that CSS values can’t be aggregated. If they could be, you could always use the same attribute (e.g. box-shadow) and combine them:

.woman {
  box-shadow: 1px 1px 0 red;
}
.playsAirGuitar {
  box-shadow: 2px 2px 0 red;
}

You'd want this to render two box-shadows, one with a 1px offset and one with a 2px offset.

Instead, you have to use a unique CSS attribute for each class of facts. However, for the simplest examples, It’s not too complicated...

If you want to query the KnowledgeBase, you need to map a standard Prolog query such as:

?- woman(mia).

Into the a different output mechanism: HTML.

The response is visualised in HTML and CSS using the following rules:

• There is an element with id "mia"
• There is a class "woman"
• The element with ID "mia" has the class "woman"

In the demo below, you can read this by verifying that the #mia div has a yellow background. Done.

Here's the complete KnowledgeBase for the first section of "Learn Prolog Now".

<!-- woman(mia). -->
<div id="mia" class="woman"></div>

<!-- woman(jody). -->
<!-- playsAirGuitar(jody). -->
<div id="jody" class="woman playsAirGuitar"></div>

<!-- woman(yolanda). -->
<div id="yolanda" class="woman"></div>

<div id="party"></div>

And here are the queries that could be answered by looking at the visual output:

?- woman(mia). 
Yes (the element with id="mia" has a yellow background)

?-  playsAirGuitar(jody).
Yes (the element with id="jody" has a solid black border)

?- playsAirGuitar(mia).
No (the element with id="mia" does not have a solid black border)

?- playsAirGuitar(vincent).
No (there is no element with id="vincent")

?- tattooed(jody).
No (there is no CSS style for a class '.tattooed')

?- party.
Yes (the element with id="party" exists)

?- rockConcert.
No (the element with id="rockConcert" does not exist)

View the output

More complex rules

It starts to get tricky when you have rules depending on other values such as

?- happy(jody):- playsAirGuitar(jody)
(“If jody plays air guitar, jody is happy”)

But I think some clever element nesting could handle that.

First, change the structure so that the classes/properties are on parent elements

<div class="woman">
    <div class="playsAirGuitar">
        <span id="jody"></span>
    </div>
</div>

Make properties into divs and entities into spans

Then update the structure of the rules:

.woman span {
    background: yellow;
}
.playsAirGuitar span {
    border: 1px solid black;    
}

Now you can make rules dependent using the cascade. First, add the property:

<!-- happy(jody):- playsAirGuitar(jody) -->

<div class="woman">
    <div class="playsAirGuitar">
        <div class="happy">
            <span id="jody"></span>
        </div>
    </div>
</div>

Then create the rule:

.playsAirGuitar .happy span {
    box-shadow: 1px 1px 0 red;  
}

The rule for happy(jody) will only be true (show box-shadow) if the rule for playsAirGuitar(jody) is also true.

View the output

Conclusion

Sure, it's all a bit silly but it was quite a fun little experiment. There are probably a few big aspects of Prolog that are unmappable but I like to think it might just be possible to create a chess endgame solver using nothing but a few thousand lines of CSS.

Thanks to some great work by Daniel Wabyick and his team, Hardy has had a bunch of improvements over the last few weeks.

The biggest change in this version is that, if you have GraphicsMagick installed on your machine, Hardy will use it for native image diffs but fall back to the built-in method if you don't. The current image diff technique involves creating an HTML page with a canvas, opening that with PhantomJS, loading the image into the canvas and using imagediff.js to calculate the diffs. It works everywhere PhantomJS works but it's slow. Daniel benchmarked the difference and it's a huge performance gain if you rely on image diff tests.

There's also some minor improvement around logging and the cucumber report format but I'll write about them later once I've had a chance to update the Hardy website.

Well, kinda. Before giving my Automated CSS Testing talk at CSS Summit in July, I recorded a video of it as a backup. If everything fell apart during my presentation, Ari could seamlessly switch over the One I Made Earlier. Fortunately, the Internet did what it does best and just worked fine.

That means I have an Automated CSS Testing video all ready and waiting that nobody's seen!

Yes, it does get progressively darker as you watch. That's not your eyes playing tricks on you, that's me sitting on my balcony recording as the sun went down.