Feynman’ s father Melville played a big role in shaping little Richard’s way of thinking. He used to read bedtime stories from the Encyclopedia Britannica.
“See this Tyrannosaurus Rex over here? It says here that this thing was 25 feet high, and the head was six feet across. That means that if it stood in our front yard, it would be high enough to put his head through the window, but not quite because the head is a little bit too wide, it would break the window as it came by”.
He always tried to translate things into some kind of reality, so little Richard would be able to figure out what it really meant, what it was really saying.
Melville would also take his kid for long walks in the Catskill mountains, telling him about nature and explaining that in order to really *know* something, you should start observing and noticing instead of merely naming (a thing most of his classmates seemed to do):
“You can know the name of a bird in all the languages of the world, but when you’re finished, you’ll know absolutely nothing whatever about the bird… So let’s look at the bird and see what it’s doing — that’s what counts. I learned very early the difference between knowing the name of something and knowing something.”
From “The pleasure of finding things out” (1981)
I think the above quote illustrates a phenomenon that occurs all too often in software testing: the nominal fallacy. Basically, this means applying a label or name to something and thinking you have explained it.
What about boundary value testing (or domain testing), for instance?
“First, we identify the boundaries, then we identify tests at each boundary. For example, one test each for >, =, <, using the first value in the > range, the value that is equal to the boundary, and the first value in the < range”.
A pretty straightforward and effective technique, right? We think we master it, until we realise that most textbooks are only talking about known and visible boundaries. What about the boundaries that are not known, not even by the developers that wrote the code? Most of the time, the software’s complexity stretches far beyond our imagination.
In case you need convincing: let’s revisit the ParkCalc exercise that took place a couple of months ago (here‘s a good write-up of that event by Selena Delesie). Matt Heusser put out a challenge to test ParkCalc, a small app on the Grand Rapids Airport website to calculate parking fees. The site provided entry and leaving times, date pickers and five different kinds of parking to choose from. Quickly, an instant test-flashmob formed via twitter. Testers from all over the globe jumped on the bandwagon. James Bach joined in and challenged everyone to beat his highest total parking fee. Extreme testing ensued. What followed was a good exercise in factoring, investigation and on-the-fly test design. And it happened to illustrate the complexity of boundary value analysis as well.
To get an even better idea of this complexity, there’s always Cem Kaner‘s online course on domain testing. Do we know boundary value analysis because we know its most basic definition?
I’m not trying to open Pandora’s box here, but these nominal fallacies also apply to a testing certification that mainly focuses on definitions. Naming things isn’t enough. As Feynman put it: knowing something requires practice and observation. The benefit? No need to memorize anything anymore when real understanding kicks in.
Of course, all this isn’t new. Half of the starr-cross’d lovers were already aware of this, way back in the late sixteenth century:
“What’s in a name? That which we call a rose
By any other name would smell as sweet.”
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