This assumes that the probability of a tool failing in any given year is the same, but that's almost certainly not true is it? Something is much more likely to break in the first year (or first month) than it is in year 10.
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Replying to @ssylvan @JoshuaBarczak
At this risk of stating the obvious, _that is what a probability assignment is_. Just pick the average probability, whatever you're comfortable with. For these kinds of graphs you do not need to model the behavior you're talking about, it doesn't matter.
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Replying to @cmuratori @JoshuaBarczak
While I agree with the general "long tail" issue you're describing, I don't think I agree that this behavior doesn't matter. It absolutely does. If most tools fail in the first month vs if it fails with uniform probability over ten years, makes a huge difference.
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In the former case, you can try something and if it doesn't work out you've only lost a month's worth of stuff built on top of it. In the latter, you could have years worth of stuff built on top.
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So once you take that into account, the simple exponential graphs you make don't really match reality anymore, because the flaky tools get pruned early and stop causing issues.
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Replying to @ssylvan @JoshuaBarczak
We definitely don't live in that reality, so I'm not sure I'm that concerned about it :) But in general these graphs actually paint a much rosier picture than they should, even so. If you actually wanted to measure failure rates, it has to be pair-wise.
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So at the point where you want to accurately model software failure, you have to make a much more complicated model, that is true.
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Replying to @cmuratori @JoshuaBarczak
So on the one hand, lots of software just sits dormant and keeps working year after year without bothering anyone. On the other hand, I intuitively and experientially agree with you that accumulating dependencies is bad for stability. Not sure about the math like that though.
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Replying to @ssylvan @JoshuaBarczak
I mean I think honestly the basic equation does pretty much tell you that, though. In my experience, things with no dependencies written in old languages (ergo, the language isn't a dependency) tend to "just work". Things in evolving languages with lots of dependencies don't.
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I write as many hobby and commercial applications, as i can, in Pascal with as near to zero dependencies as possible. After 12 years, only a few projects failed to compile due to being incompatible with the new tooling. It's why I don't NodeJS & npm. I think your math is spot on.
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node.js is insane this way - I don't think I've ever updated Electron and had it work. You always have to modify your code for one reason or another, no matter how simple it may be!
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