The first step is to be clear about what you’re asking and what you’re trying to accomplish.
A whole bunch of things could be said to “cause” the crash, such as the power supplied to the system. You want a program that does what you want, and doesn’t crash. You could immediately exit the program and likely always avoid a crash. The lack of such an exit could be said to be “the cause” of the crash. But what good does identifying such a cause do you?
A cause isn’t necessarily “the thing that needs to be changed”, though people often treat it that way.
Do I need a probability distribution over crash frequencies?
I think the data you have, and some ignorance prior, and an independence assumption of crash trials (which I think is likely a false assumption), you have Bernoulli trials and can assign a probability distribution to each of the two states—with and without the line.
But I don’t know what good those distributions do you.
Why are you assigning probability distributions instead of doing more debugging? What do you expect to do with those distributions? What does the line do? Why not just remove it?
Basically, what’s the problem you’re trying to solve?
I’m reasonably confident I solved my actual coding issue; I have a mental model of what the race condition was and how I resolved it, and in many runs of the modified program I have not seen the crash. So the problem for this thread is just that I was confused on how to use Bayes in such a case, and would like to learn some math.
The first step is to be clear about what you’re asking and what you’re trying to accomplish.
A whole bunch of things could be said to “cause” the crash, such as the power supplied to the system. You want a program that does what you want, and doesn’t crash. You could immediately exit the program and likely always avoid a crash. The lack of such an exit could be said to be “the cause” of the crash. But what good does identifying such a cause do you?
A cause isn’t necessarily “the thing that needs to be changed”, though people often treat it that way.
I think the data you have, and some ignorance prior, and an independence assumption of crash trials (which I think is likely a false assumption), you have Bernoulli trials and can assign a probability distribution to each of the two states—with and without the line.
But I don’t know what good those distributions do you.
Why are you assigning probability distributions instead of doing more debugging? What do you expect to do with those distributions? What does the line do? Why not just remove it?
Basically, what’s the problem you’re trying to solve?
I’m reasonably confident I solved my actual coding issue; I have a mental model of what the race condition was and how I resolved it, and in many runs of the modified program I have not seen the crash. So the problem for this thread is just that I was confused on how to use Bayes in such a case, and would like to learn some math.
For the math on Bernoulli trials, see Jaynes and wikipedia for the Rule of Succession:
http://en.wikipedia.org/wiki/Rule_of_succession
http://www-biba.inrialpes.fr/Jaynes/cc18i.pdf
And this looks like a pretty good paper on setting priors by maximum entropy and transformation groups. http://bayes.wustl.edu/etj/articles/prior.pdf