diff --git a/src/lib/array.jl b/src/lib/array.jl
index d38751331..049a49f3d 100644
--- a/src/lib/array.jl
+++ b/src/lib/array.jl
@@ -30,25 +30,26 @@ end
 @adjoint (::Type{T})(sz) where {T<:Zeros} = T(sz), Δ->(nothing,)
 @adjoint (::Type{T})(sz) where {T<:Ones} = T(sz), Δ->(nothing,)
 
-_zero(xs::AbstractArray{<:Number}, T=float(eltype(xs))) = fill!(similar(xs, T), false)
-_zero(xs::AbstractArray, T=Any) = Union{Nothing, T}[nothing for x in xs]
-
 @adjoint getindex(x::AbstractArray, inds...) = x[inds...], ∇getindex(x, inds)
 
 @adjoint view(x::AbstractArray, inds...) = view(x, inds...), ∇getindex(x, inds)
 
 ∇getindex(x::AbstractArray, inds) = dy -> begin
-  if inds isa  NTuple{<:Any,Integer}
+  if inds isa  NTuple{<:Any, Integer}
     dx = _zero(x, typeof(dy))
     dx[inds...] = dy
   else
     dx = _zero(x, eltype(dy))
     dxv = view(dx, inds...)
-    dxv .+= _droplike(dy, dxv)
+    dxv .= accum.(dxv, _droplike(dy, dxv))
   end
-  (dx, map(_->nothing, inds)...)
+  return (dx, map(_->nothing, inds)...)
 end
 
+_zero(xs::AbstractArray{<:Number}, T::Type{Nothing}) = fill!(similar(xs), zero(eltype(xs)))
+_zero(xs::AbstractArray{<:Number}, T) = fill!(similar(xs, T), false)
+_zero(xs::AbstractArray, T) = fill!(similar(xs, Union{Nothing, T}), nothing)
+
 _droplike(dy, dxv) = dy
 _droplike(dy::Union{LinearAlgebra.Adjoint, LinearAlgebra.Transpose}, dxv::AbstractVector) =
   dropdims(dy; dims=2)
diff --git a/test/gradcheck.jl b/test/gradcheck.jl
index 3d95f7f8d..8994f974d 100644
--- a/test/gradcheck.jl
+++ b/test/gradcheck.jl
@@ -138,33 +138,41 @@ end
 @test gradient(logdet, 2.0)[1] == 0.5
 
 @testset "getindex" begin
-  @test gradtest(x -> x[:,2,:], (3,4,5))
-  @test gradtest(x -> x[1:2,3:4], (3,4))
+  @test gradtest(x -> x[:, 2, :], (3, 4, 5))
+  @test gradtest(x -> x[1:2, 3:4], (3, 4))
 
   imat = [1 2; 3 4]
-  @test gradtest(x -> x[:,imat], (3,4))
-  @test gradtest(x -> x[:,[1,2,2]], (3,4))
+  @test gradtest(x -> x[:, imat], (3, 4))
+  @test gradtest(x -> x[:, [1, 2, 2]], (3, 4))
   irep = [1 2; 2 2]
-  @test gradtest(x -> x[1,irep], (3,4))
+  @test gradtest(x -> x[1, irep], (3, 4))
 
   # https://github.com/invenia/Nabla.jl/issues/139
   x = rand(3)
-  z = [1,2,3,3]
-  y(x,z) = dot(ones(4), x[z])
-  @test gradient(y, x,z) == ([1,1,2], nothing)
+  z = [1, 2, 3, 3]
+  y(x, z) = dot(ones(4), x[z])
+  @test gradient(y, x, z) == ([1, 1, 2], nothing)
 
   # https://github.com/FluxML/Zygote.jl/issues/376
   _, back = Zygote._pullback(x->x[1]*im, randn(2))
   @test back(1.0)[2] == [-im, 0]
 
   # _droplike
-  @test gradient(x -> sum(inv, x[1,:]'), ones(2,2)) == ([-1 -1; 0 0],)
-  @test gradient(x -> sum(inv, x[1:1,:]'), ones(2,2)) == ([-1 -1; 0 0],)
-  @test gradient(x -> sum(inv, transpose(view(x,1,:))), ones(2,2)) == ([-1 -1; 0 0],)
+  @test gradient(x -> sum(inv, x[1, :]'), ones(2, 2)) == ([-1 -1; 0 0],)
+  @test gradient(x -> sum(inv, x[1:1, :]'), ones(2, 2)) == ([-1 -1; 0 0],)
+  @test gradient(x -> sum(inv, transpose(view(x, 1, :))), ones(2, 2)) == ([-1 -1; 0 0],)
 
   # https://github.com/FluxML/Zygote.jl/issues/513
-  @test gradient(p -> sum(Float32[1,0] - p), [2,3]) == ([-1,-1],)
-  @test gradient(x -> sum(Float32[1,x] .+ x), 4) == (3.0f0,)
+  @test gradient(p -> sum(Float32[1, 0] - p), [2, 3]) == ([-1, -1],)
+  @test gradient(x -> sum(Float32[1, x] .+ x), 4) == (3.0f0,)
+
+  # Ensure that nothings work with numeric types.
+  _, back = Zygote.pullback(getindex, randn(4), [1])
+  @test back([nothing]) == (zeros(4), nothing)
+
+  # Ensure that nothings work with non-numeric types.
+  _, back = Zygote.pullback(getindex, [randn(2) for _ in 1:3], [1])
+  @test back([nothing]) == ([nothing for _ in 1:3], nothing)
 end
 
 @testset "view" begin