The geometric model of maintenance

James Shore posits that each person-month spent writing code results in 10 days of maintenance in the first year, then 5 days every year after that. Naïvely interpreted, this is a threshold-based model for induced maintenance, and its interesting because it’s so simple.

If it could be shown to be true, that’d be useful. The argument Shore is making about the effects of robot-generated code does not depend on the specific numbers, so Shore’s numbers come from a hypothetical wisdom-of-the-crowds aggregation rather than concrete data. But no hypotheticals are necessary here. We have a thing called git.

Full article (8–21 minute read): The geometric model of maintenance

Swemak: Colemak for Swedish

I have written before about my Swedish Colemak hack, but I never explained what makes it so good. This layout makes room for the three Swedish letters Å, Ä, and Ö, by only changing five keys in total, and they have changed very thoughtfully.

Full article (2–4 minute read): Swemak: Colemak for Swedish

Flashcard of the week

This is not strictly speaking a flashcard so you'll have to excuse that it's badly phrased. I just wanted to include the question here anyway because it delights me.

Why is it important to sample with known probabilities?

Because then one gets to compute the sampling error.

I'm on-and-off working on a Monte Carlo tree search problem where I'm trying to approximate the value of a node in a search tree. I don't know what the value is, but I would like to know how close the approximation is to the true value.

Because the process samples with known probabilities, I can run the process a few times with different seeds, and the spread of the results can be combined into a confidence interval!

That's so magical. I don't know what the true value is. I have no mechanical way of knowing how far from the approximation the true value is. But I can still sorta-kinda tell how far it can be from the approximation based on how spread out the guesses are.

That only works when the guesses are sampled with known probabilities.

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