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There recently have been some discussions about what can be done in Julia to prevent composing various package in a way that leads to silent error or nonsensical result. A possible solution is better test infrastructure.
I thought about what it could mean for IA since we had quite serious silent bugs caused by IA being used with boolean operations.
It could be interesting to provide a function like
plays_well_with_IA(func, args...)
where args contains some interval arguments. Then func(args...) is computed as well as the values of func for a bunch of point inside the intervals (maybe the bounds and random points inside) and the values are checked to fall inside func(args...).
This would allow users to easily have a sanity check to see if everything seems fine and could be used in the package tests as well.
The text was updated successfully, but these errors were encountered:
Fully agree with the idea! Incidentally, the same function could be used inside our own tests to check consistency. In TaylorModels I implemented something like that, though certainly not so user friendly, which includes calculations using extended precision.
There recently have been some discussions about what can be done in Julia to prevent composing various package in a way that leads to silent error or nonsensical result. A possible solution is better test infrastructure.
I thought about what it could mean for IA since we had quite serious silent bugs caused by IA being used with boolean operations.
It could be interesting to provide a function like
where
args
contains some interval arguments. Thenfunc(args...)
is computed as well as the values offunc
for a bunch of point inside the intervals (maybe the bounds and random points inside) and the values are checked to fall insidefunc(args...)
.This would allow users to easily have a sanity check to see if everything seems fine and could be used in the package tests as well.
The text was updated successfully, but these errors were encountered: