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  Saturday, August 30, 2003 

Code reading and literary criticism

Brian Marick has posted a wonderful essay on the subject of commenting code. "I do believe that code with comments should often be written to be more self-explanatory," he says. "But code can only ever be self-explanatory with respect to an expected reader." To illustrate, he shows an algorithm in C, then translates to the kind of Lisp a C programmer would write, then retranslates to the kind of Lisp a Lisp programmer would write. Then he walks through the Lisp code line by line, exploring how the code itself sets up and then satisfies expectations in the mind of a reader who is presumed Lisp-proficient.

The line by line analysis I gave above was inspired by the literary critic Stanley Fish. He has a style of criticism called "affective stylistics". In it, you read something (typically a poem) word by word, asking what effect each word (and punctuation mark, and line break...) will have on the canonical reader's evolving interpretation of the poem. [Exploration Through Example]

You don't run into the juxtaposition of Lisp and lit-crit every day! But as a former lit-crit person myself, I think there's a lot of merit to what Brian is saying here. The practical conclusions:

The more diverse your audience, the more likely you'll need comments. Teams will naturally converge on a particular "canonical reader", but perhaps that process could be accelerated if people were mindful of it.

Fascinating stuff, Brian.

 

In search of Office 2003 developers

You: A developer building an Office solution that couldn't have been done prior to Office 2003 -- i.e., that leverages the XML capabilities of (in particular) InfoPath, Excel, and Word.

Me: A journalist interested in interviewing you, starting Tuesday of next week.

Serious inquiries only, please.

 

More pleasant surprises, please

I want to be pleasantly surprised by software that notices when message patterns indicate the formation of a group or project, and volunteers to set up folders and filters for me. Likewise, I want to be pleasantly surprised by an RSS newsreader that notices how I save and organize items from my subscribed feeds. No breakthrough in artificial intelligence is needed to make this happen. We do the pattern recognition ourselves, quite naturally, as we process our information flows. If software paid more attention to what we attend to, and how, there could be more pleasant surprises. Full story at [InfoWorld.com].

I had a bit of a pleasant surprise today. Last night Greg Reinacker wrote to say that Outlook 2003 does have a Bayesian filtering capability (as I'd heard), and he's getting pretty good mileage out of it, though he admits there's no documentation on whether or how to train it, and points out that it's odd there's a "Not Junk" button but no "Junk This" button. For about a week I'd been using Outlook 2003 in parallel with Outlook 2000 + SpamBayes. In OL2003 I kept manually dragging spams -- mostly Sobig.F's -- into the junk folder, but it didn't seem to catch on. Nor did it catch more than a few non-Sobig.F's. Then, last night, I loaded up a batch of about 5000 choice spam messages from my SpamBayes training database into OL2003's junk folder. That seemed to do the trick. Now it's doing much better at catching non-Sobig.F's, though for reasons I can't determine it still hasn't trained on Sobig.F's, even though they're decorated with SpamAssassin headers. Is it possible it only looks at the body, not the header? Anyway, it's not as lame as I thought, though not nearly -- so far as I can tell -- as useful as SpamBayes.

 


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