My physical model consists of results requested, test subjects and variable set of phenomena acting upon the subjects. It’s convenient to keep all phenomena-related function calls conditioned by if-else statements within main program for test-driven development and retrospection, but compilation time grows as big as 22 minutes. When non-production branches are cut, i.e. control flow is solved, manually, compilation time is reduced to 2 minutes. This is how i see original problem:
X=1:N. AX is code.
- Create file “dummy.jl”. Write:
function dummy(;kwarg1=false,...,kwargN=false) for j=1:T if kwarg1 execute A1 end if kwarg2 execute A2 end . . . if kwargN execute AN end end nothing end
Do we already know, how does compilation time depend on N?
Say, if kwarg1 is true, is compilation time dominated by O(A1)? Is compilation time dominated by O(dummy)?
I wonder if i may make version control system to merge just enough code for a task, where whole argument array of length 200+, destined to dummy’s real-world prototype, will be supplied to shell script, calling for e.g. git.