Fix indexing BigInt axes with large indices

[jishnub]

This uses type-promotion for integer ranges to widen the axis type, which makes the result correct for large BigInt arguments. I don't like the special-casing, but I couldn't figure out how to work around floating-point ranges.

This required changing certain searchsorted methods to accept Integer instead of Int, which improves BigInt support. I've also removed the @inbounds annotations, as this isn't necessarily guaranteed. Since these are O(log n) operations, the expense of bounds-checking should not be much.

[codecov]

Codecov Report

Merging #142 (ae64dc9) into master (8fe1160) will increase coverage by 0.03%.
Report is 3 commits behind head on master.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #142      +/-   ##
==========================================
+ Coverage   85.89%   85.92%   +0.03%     
==========================================
  Files           6        6              
  Lines         730      732       +2     
==========================================
+ Hits          627      629       +2     
  Misses        103      103              

Files Changed	Coverage Δ
src/InfiniteArrays.jl	86.66% <100.00%> (ø)
src/infrange.jl	87.57% <100.00%> (+0.07%)	⬆️

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[dlfivefifty]

Why were the inbounds removed?

[jishnub]

The access may not be within bounds, unless we consider this to be an internal method that is never directly called by a user. Otherwise, a call like

julia> v = [1,2]
2-element Vector{Int64}:
 1
 2

julia> searchsorted(v, 2, firstindex(v), ∞, Base.Order.ForwardOrdering())
ERROR: BoundsError: attempt to access 2-element Vector{Int64} at index [1000]

may lead to memory corruption through out-of-bounds access.

The alternative is to add a bounds-check to the function, in which case we may retain the inbounds annotations.

[dlfivefifty]

Hmm I copied this code from Base which has the exact same issue:

julia> searchsorted([1,2], 2, 1, 10, Base.Order.ForwardOrdering())
2:3

I've started an issue: JuliaLang/julia#51176

I think its best to just check that hi ≤ length(v) here and keep the inbounds

[jishnub]

I have reverted the inbounds for now. This is unlikely to be an issue in practice, as these are internal methods. We may revisit this in the future, if necessary.