Monthly Archives: September 2012
Before moving back into media studies, I taught programming at various levels for quite a number of years. One of the things that always struck me, in particular at the beginner’s level, is how little my attempts to find different metaphors, explanations, ways of approaching the subject and practical exercises changed about a basic observation that would repeat itself over the years: some people get it, some don’t. Some students seem like they are born to program, while others cannot – even after long hours of training and no lack of trying – write even the simplest piece of functional and useful code.
Arstechnica has posted a really interesting piece relaying a Q&A on Stack Exchange on this exact topic: “can everyone be a programmer”? Amongst the different resources cited is a link to a paper from 2006 by Saeed Dehnadi and Richard Bornat from the School of Computing at Middlesex University that basically confirms the “double bump” so many programming teachers observe year after year (a lively discussion of the paper is here). What really struck me about the paper was not so much the empirical outcome though, neither the fact that a relatively simple test seems to yield robust results in predicting programming aptitude, but rather a passage that speculates on the reasons for the findings:
It has taken us some time to dare to believe in our own results. It now seems to us, although we are aware that at this point we do not have sufficient data, and so it must remain a speculation, that what distinguishes the three groups in the first test is their different attitudes to meaninglessness.
Formal logical proofs, and therefore programs – formal logical proofs that particular computations are possible, expressed in a formal system called a programming language – are utterly meaningless. To write a computer program you have to come to terms with this, to accept that whatever you might want the program to mean, the machine will blindly follow its meaningless rules and come to some meaningless conclusion. In the test the consistent group showed a pre-acceptance of this fact: they are capable of seeing mathematical calculation problems in terms of rules, and can follow those rules wheresoever they may lead. The inconsistent group, on the other hand, looks for meaning where it is not. The blank group knows that it is looking at meaninglessness, and refuses to deal with it.
While a single explanatory strategy like this is certainly not enough, I must admit that I have rarely read something about teaching programming that comes as close to my own experience and intuition. It was always my impression – and I have discussed this in great length with some of my peers – that programming requires a leap of faith, an acceptance of something that contradicts many of the things we have learned from our everyday experience. When programming, we are using words to build a machine and because the “meaning” of software is expressed through the medium of functionality, the words we write are simply not expressive in the same way as human language.
Over these last years, there has been a debate in software studies and related fields about the linguistic vs. functional dimension of “code”, and I have always found this debate to be strangely removed from the practice of programming itself (which may actually be a goal rather than an omission), perhaps simply because I have always seen the acceptance of the meaninglessness – in terms of semantics – of programming languages as a requirement to be a programmer. This does not mean that code does not have meaning as text but, to put it bluntly, if one cannot suspend that belief and look through the code directly into the functionality it produces, one cannot be a programmer. This is also the reason why I am so skeptical about the focus on code and the idea that scholars interested in software have to “learn how to write code”. Certainly, programming languages, development environments, etc. structure the practice – they open certain doors and close others, they orient and facilitate – but in the end, from the perspective of the programmer, the developer who actually builds a program the true expressiveness of software is behind the code; and when developers discuss the different advantages and disadvantages of various programming languages, they are measuring them in terms of how to get to that behind, how they allow us to pierce through their formalism, their meaninglessness to get to the level of expression we are actually speaking on: functionality.
This is the leap of faith that I have seen so many students not be able to commit to (for whatever reason, perhaps not the least my incapacity to present it in a way they can relate to): to accept the pure abstract performative formality of the words you are writing and see the machine behind the text. Because for those who program – and they are certainly not the only ones who have the right to speak about these matters – the challenge is to go through one kind of language (code) to get to another kind of language (function).
The example discussed in the paper – and used as a test – is telling:
int a = 10;
int b = 20;
a = b;
I do not know how many times I have tried to explain assignment. One of the tricks I came up with was the “arrow to the left” idea: a = 10 does not mean that a is equivalent to 10 but that the “=” should be a “<=” that puts “what is on the right” into “what is on the left”. In my experience – and the paper fully confirms that – not every student can get to a functional understanding of why “a” contains the value “20” at the end of this script. Actually, the “why” is completely secondary. “a = b” means that you are putting the value for b into a. You’re doing it. Really. Really? I don’t know. But if you want to write a program you need to accept that this is what’s happening here. You don’t have to believe in it; formalism is about the commitment to a method, not an ontology. Let go of the idea that words mean something; here, they do something.
Software is not “linguistic” because source code has meaning – it may very well, but to write a program you have to forget about that – but because functionality is itself a means of expression. Despite the many footnotes I should add here, it is the capacity to be able to express the meaningful through the meaningless that makes a programmer. We have to let go a little of the world as we know it, in order to find it again, but in a different way.
This implies a very specific epistemological and even psychological stance, a way of unveiling the world in a certain manner. The question why this manner is apparently not everybody’s cup of tea may be a fruitful way to better understand what it actually consists of.