# Discrete Event Probablities

My colleague, David, had an interesting problem:

“I want to simulate exceptional events (e.g. I/O errors) at predictable rates.

For example, if an error should occur 33% of the time, it should be predictable like: ERROR, ok, ok, ERROR, ok, ok, ...

Or at 50% error rate: ERROR, ok, ERROR, ok, ...

devdriven:

“Pseudo-random function p(t) in range [0,1) at time t and P is the probability of the event (e.g. I/O error) then: event?(t) = p(t) < P.

Pseudo-random numbers are predictable if you know the seed."

David:

“Not really what I had in mind. There’s got to be a better way…”