specialize isassigned for performance

[nsajko]

Fixes #14

The below benchmark shows many orders of magnitude of performance improvement, more so for arrays with many undef elements:

using BenchmarkTools, FixedSizeArrays

function new_arr(len, prob)
  ret = FixedSizeVector{FixedSizeVector{Nothing}}(undef, len)
  for i ∈ eachindex(ret)
    if rand() < prob
      ret[i] = eltype(ret)(undef, 0)
    end
  end
  ret
end

function assigned_count(arr)
  cnt = 0
  for i ∈ eachindex(arr)
    cnt += isassigned(arr, i)
  end
  cnt
end

len = 10000

arr = new_arr(len, 0.1);
@btime assigned_count(arr)
# prior to this change: 244.170 ms
# with this change:     6.879 μs

arr = new_arr(len, 0.5);
@btime assigned_count(arr)
# prior to this change: 134.400 ms
# with this change:     6.871 μs

arr = new_arr(len, 0.9);
@btime assigned_count(arr)
# prior to this change: 27.091 ms
# with this change:     6.879 μs

versioninfo()
# Julia Version 1.12.0-DEV.379
# Commit aad72458539 (2024-04-20 23:40 UTC)
# Build Info:
#   Official https://julialang.org/ release
# Platform Info:
#   OS: Linux (x86_64-linux-gnu)
#   CPU: 8 × AMD Ryzen 3 5300U with Radeon Graphics
#   WORD_SIZE: 64
#   LLVM: libLLVM-16.0.6 (ORCJIT, znver2)
# Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores)

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 100.00%. Comparing base (4a1613e) to head (469101b).

Additional details and impacted files

@@            Coverage Diff            @@
##              main       #15   +/-   ##
=========================================
  Coverage   100.00%   100.00%           
=========================================
  Files            1         1           
  Lines           32        33    +1     
=========================================
+ Hits            32        33    +1     

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