Legend Brown Ale + Graphs

Mon 01 June 2015 | Tags: brown ale, legend, graph, data structures

How we got here and what we drank.

Today I find myself enjoying a Legend Brewing Company Brown Ale on the dock at my mother in law's home. She lives at Lake Anna, Virginia, right on the water. Even though I love the Pacific Northwest, it's always relaxing to come down to the lake and sip a beer by the water.

Since I do live in the Pacific Northwest and my mother in law in central Virginia, I had to travel here somehow. The distance is great enough that flying is the only viable option (though someday I hope to take the train — with the right tickets, I could get to Culpeper, Virginia, which is only a short drive away). Taking a flight always reminds me of the data structure we call a graph, so that's what we'll cover in today's Computer Science + Beer.

Appearance

Confession: I didn't drink this one out of a glass. Burn the heretic, I hear you cry. Well, that's the way it is when you're on vacation at the lake. I presume this would be a pretty standard-looking brown ale: Brown beer, light colored head, fairly clear.

We can examine the label, though, and I'll admit that it's off-putting to me. We have a unicorn rearing up in front of a red heraldic field surrounded by barley and hops: Quite Arthurian. I'm sure it's meaningful to the brewer and designer so I don't want to disparage, but it doesn't exactly scream "excellent beer" from the shelf.

A graph simply looks like a collection of circles connected by lines. The circles, officially called nodes, could represent airports served by a particular airline. The lines between them, or edges, could represent direct flights between the cities. In this example, if there's a line from my city to yours, I can fly straight there. If not, I might have to fly to one or more intermediate cities before I can get to you.

An image of a graph - thanks Wikipedia!

Aroma

In keeping with my confession above, take this with a grain of salt. I'm huffing through the mouth-scented rim of a bottle (you're welcome for that mental image). Despite adverse conditions, I get a lovely toffee note with little hop aroma. Nothing off (from the beer). There's a bit of a grainy note that's not unpleasant, and this is definitely going to be a sweet beer.

Any time you have a problem involving route-finding or networking, it should smell like a graph. Connections between entities, such as friends in a social network, are also a key place to think about graphs. There are specialized graphs that can solve other interesting problems: We'll cover trees and finite state machines another time.

Flavor and Mouthfeel

The toffee and grainy aromas I detected continued into the flavor. The brewer says molasses on their site, which I probably wouldn't have come up with on my own but it's not an unfair description. It's not as cloying as I feared, though definitely malty-sweet. It seems highly carbonated to me, which probably helps cut the sweetness. I also get a light hop bitterness (no particular flavor) on the tongue. Quite full-bodied — perhaps not the wisest beer choice on a 90 degree day, but I'm enjoying it nonetheless! Finishes sweet and sticky, a low point for me as I like my beers to finish fairly clean.

Graphs are pretty easy to draw on paper and relatively simple to implement in code. If I stripped out all the beer stuff, I could teach them to a bright five-year-old in 20 minutes. Graphs are well-studied, and we have stock solutions for a lot of different problems involving them. See, for instance, the dozens of ways to traverse a graph. Their simplicity and mathematical properties make graphs a powerful tool in the computer scientist's arsenal.

Overall Impression

The beer's easily a 4.5/5 for me. I've passed this up in the grocery store numerous times on previous trips because I tend toward the aggressively-bittered styles, but it's a mistake I won't repeat. Despite the label, the beer is great and I'm excited to finish the six-pack. And that's not just the sun talking.

Graphs may be one of my favorite topics in all of computer science. I remember learning about them in a college class and thinking, "Nothing so simple could possibly matter — when are we going to get to the compilers?!" As it turns out, graphs are everywhere; they definitely matter. If you count trees as graphs, they're even a prerequisite for understanding compilers.


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