Semantic Werks

See here: Deadline Iraq: Untold Stories of the Iraq War. It’s a good documentary, but my problem with it is that I don’t think this type of unnarrated exposition does enough to raise the important questions. We sort of flit from scene to scene: a firefight, a missile explosion, a hospital… but what is the connection? What message should we take from it all? A few of mine:

War seems so banal in the videos, unreal, just a bunch of guys yelling at each other. Bullets fly through the air with a muted buzz. These sounds and images can’t possibly capture the fear and terror and adrenaline flowing. How can we do this?

Are embeds soldiers or journalists? The big tragedy is that some journalists have been shot in the Palestine Hotel? Amid all the other shit going on in Iraq? The torture before the invasion, the murders after the invasion?

In every country, you can find any thousand people willing to say what you want. So photos of cheering, jeering, dead civilians, and so on, really don’t tell us anything. I think this still affects our coverage of the Middle East. I think what is most telling is Peter Mansbridge’s comment, that ideally you would be able to go anywhere you want on the battlefield, but that you cannot, so you make do. Sometimes this means accepting what the local authorities are willing, or want, to show.

Maher Abdullah: there is no such thing as an objective journalist. And if that’s the case, then what is the point? Presumably the point of reportage on these situations is to give the decision-makers, the public, all the information they need. But the people on the frontlines only send these stories to their editors, and then the editors make decisions about how those photos will sell papers. On top of that, there are Pentagon apologists who get paid to go on CNN/Fox/MSNBC and offer their ‘analysis’ of the war. One minute of their (unacknowledged) biased opinions can wreck any useful data coming out of the theatre of war. I’m sure the reason the Pentagon allowed embeds is because the staffers in Washington realize the average journalist isn’t a threat, so long as they can steer the distribution back home.

One of the journalists claims this was the best-covered war in history, but what is the coverage? If the public never sees dead Americans, or gets the meaningful, in depth analyses (monthly death tolls, economic ruin, etc), then what is the point? That we see some neat photos and videos, make some TV shows, and on we go?

Perhaps blogs are one way to address these problems. People like Michael Yon, who are freelance and self-publish, and most importantly, are very clear about their biases. He’s resolutely pro-military, but he still brings some important data points to the conflicts he covers.

Talk at the University of Toronto CS department’s distinguished lecture series today by Alan Kay. Kay doesn’t believe there is a discipline of computer science. There’s a slurry of incremental, cul-de-sac research aimed at generating maximum publications (according to Kay, the UC system only cares about absolute numbers of papers published). And there’s a bunch of vendor junk, like SAP and Microsoft Office. This point really resonates: how can taking direction from IBM (autonomic computing, Eclipse, Jazz) be any different than taking direction from Pfizer, or Monsanto, or DARPA?

There’s an intuitive appeal to the argument against CS as a scientific discipline: if you look at what Sutherland, PARC, etc. built in the 1970s, or LISP in the 1950s, there’s not a lot of progress since then on the fundamental questions they were addressing. I think there’s a lot of room for criticism of Kay’s comparisons, but strong reactions are obviously what he was going for.

Interesting point: if we consider IQ, knowledge, and outlook (which I think of as perspective), the first one dominates among computer scientists. He characterizes this as making piles of bricks, e.g., the Pyramids. However, being able to solve small problems does not address the nature of those problems; hence his comment that architecture dominates materials. The second aspect is knowledge, which is akin to making good cars with available parts, re-engineering the available to address the issue. Henry Ford typifies this aspect. Finally, he uses Einstein as evidence of someone who (on top of having a high IQ and a lot of knowledge) shifted the perspective (paradigm, as Kuhnians would say) in a new direction, e.g., that Truth is relative, that time is relative, etc.

His main work seems to be focused on implementing work that is shifting perspectives in CS, rethinking problems in novel and unseen ways. His Viewpoints Research Institute is the main place he currently works in.

Caution: arguing that you are shifting perspectives or doing radical new work is also often associated with crackpot science. Not that this is what Kay is doing.

The challenge I’m undertaking is to report on something ‘interesting’ (and novel) about projects under the Gnome umbrella. Since my thesis is on requirements evolution, I’ve tried to use the Challenge to help me understand the nature of the evolution problem. I suppose the first issue is to convince one that there is a problem. Are requirements changing over time? What factors are driving that change?

Rather than looking at functional requirements, which can vary tremendously across projects (I have my opinions about this but more later), I’ve chosen to look instead at software qualities, aka ‘ilities’ aka NFRs. These are notions such as usability, security, and maintainability. These concepts can be said, tentatively, anyway, to transcend software ecosystems. That is, every piece of software can be judged according to its fulfilment of these ’soft goals’. In particular, I’ve decided to use the ISO 9126 standard, which lists a brief taxonomy of software qualities. The advantage is that it is relatively well-known, and ’standard’, for what that’s worth. The problem with using it is that there are as many taxonomies of software qualities as corrupt bankers on Wall Street. Some might argue that even non-functional qualities are not universally applicable.

How am I going to apply this model to the corpus? I’m doing this somewhat iteratively, in that I’m going to start simple and build from there. So for now, my goal is to show how these qualities are discussed over time in a given project. My guiding framework is to model word use (and related terms) as events in the timeline of a project. So if a developer or user mentions ‘usability’ on a mailing list, that becomes an event in my system. Then I record these events and use a timeline to show how they occur over time. Not a terribly sophisticated NLP technique, but let’s see where it gets us before delving into Markov models, naive Bayesian algorithms, and so on.

I have a few hypotheses about the presence of my events, relating to how NFRs are more or less important (as gauged by frequency of mention) at various lifestages of a software system, for numbers of developers, for project focus (media, utility, OS, etc.), and so on. More on these later.