diff --git a/Project.toml b/Project.toml
index 0a5157e..208dab9 100644
--- a/Project.toml
+++ b/Project.toml
@@ -18,13 +18,21 @@ SparseArraysExt = "SparseArrays"
 StatisticsExt = "Statistics"
 
 [compat]
+Aqua = "0.8.12"
+Distributed = "<0.0.1, 1"
 ExplicitImports = "1.13.2"
+LinearAlgebra = "<0.0.1, 1"
 Primes = "0.4, 0.5"
+Random = "<0.0.1, 1"
+Serialization = "<0.0.1, 1"
 SparseArrays = "<0.0.1, 1"
+SpecialFunctions = "0.8, 1, 2"
 Statistics = "<0.0.1, 1"
+Test = "<0.0.1, 1"
 julia = "1.10"
 
 [extras]
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 ExplicitImports = "7d51a73a-1435-4ff3-83d9-f097790105c7"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
@@ -32,4 +40,4 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["ExplicitImports", "SparseArrays", "SpecialFunctions", "Statistics", "Test"]
+test = ["Aqua", "ExplicitImports", "SparseArrays", "SpecialFunctions", "Statistics", "Test"]
diff --git a/src/DistributedArrays.jl b/src/DistributedArrays.jl
index 51f50ce..f9b0c4c 100644
--- a/src/DistributedArrays.jl
+++ b/src/DistributedArrays.jl
@@ -10,6 +10,8 @@ using Serialization: Serialization, AbstractSerializer, deserialize, serialize
 
 using Primes: factor
 
+import SparseArrays
+
 # DArray exports
 export DArray, SubDArray, SubOrDArray, @DArray
 export dzeros, dones, dfill, drand, drandn, distribute, localpart, localindices, ppeval
diff --git a/src/broadcast.jl b/src/broadcast.jl
index be6a4ac..a689faa 100644
--- a/src/broadcast.jl
+++ b/src/broadcast.jl
@@ -60,7 +60,7 @@ end
 #     - Q: How do decide on the cuts
 #   - then localise arguments on each node
 ##
-@inline function Base.copyto!(dest::DDestArray, bc::Broadcasted)
+@inline function Base.copyto!(dest::DDestArray, bc::Broadcasted{Nothing})
     axes(dest) == axes(bc) || Broadcast.throwdm(axes(dest), axes(bc))
 
     # Distribute Broadcasted
diff --git a/src/darray.jl b/src/darray.jl
index 9d4d8a4..e343c83 100644
--- a/src/darray.jl
+++ b/src/darray.jl
@@ -368,7 +368,9 @@ Can return a view into `localpart(A)`
 end
 
 # shortcut to set/get localparts of a distributed object
-function Base.getindex(d::DArray, s::Symbol)
+Base.getindex(d::DArray, s::Symbol) = _getindex(d, s)
+Base.getindex(d::DistributedArrays.DArray{<:Any, 1}, s::Symbol) = _getindex(d, s)
+function _getindex(d::DArray, s::Symbol)
     @assert s in [:L, :l, :LP, :lp]
     return localpart(d)
 end
@@ -438,6 +440,14 @@ function Base.:(==)(d1::SubDArray, d2::SubDArray)
     return t
 end
 
+# Fix method ambiguities
+for T in (:DArray, :SubDArray)
+    @eval begin
+        Base.:(==)(d1::$T{<:Any,1}, d2::SparseArrays.ReadOnly) = d1 == parent(d2)
+        Base.:(==)(d1::SparseArrays.ReadOnly, d2::$T{<:Any,1}) = parent(d1) == d2
+    end
+end
+
 """
     locate(d::DArray, I::Int...)
 
@@ -497,10 +507,28 @@ dfill(v, d1::Integer, drest::Integer...) = dfill(v, convert(Dims, tuple(d1, dres
 Construct a distributed uniform random array.
 Trailing arguments are the same as those accepted by `DArray`.
 """
-drand(r, dims::Dims, args...) = DArray(I -> rand(r, map(length,I)), dims, args...)
-drand(r, d1::Integer, drest::Integer...) = drand(r, convert(Dims, tuple(d1, drest...)))
-drand(d1::Integer, drest::Integer...) = drand(Float64, convert(Dims, tuple(d1, drest...)))
-drand(d::Dims, args...)  = drand(Float64, d, args...)
+drand(::Type{T}, dims::Dims) where {T} = DArray(I -> rand(T, map(length, I)), dims)
+drand(X, dims::Dims) = DArray(I -> rand(X, map(length, I)), dims)
+drand(dims::Dims) = drand(Float64, dims)
+
+drand(::Type{T}, d1::Integer, drest::Integer...) where {T} = drand(T, Dims((d1, drest...)))
+drand(X, d1::Integer, drest::Integer...) = drand(X, Dims((d1, drest...)))
+drand(d1::Integer, drest::Integer...) = drand(Float64, Dims((d1, drest...)))
+
+# With optional process IDs and number of chunks
+for N in (1, 2)
+    @eval begin
+        drand(::Type{T}, dims::Dims, args::Vararg{Any,$N}) where {T} = DArray(I -> rand(T, map(length, I)), dims, args...)
+        drand(X, dims::Dims, args::Vararg{Any,$N}) = DArray(I -> rand(X, map(length, I)), dims, args...)
+        drand(dims::Dims, args::Vararg{Any,$N}) = drand(Float64, dims, args...)
+    end
+end
+
+# Fix method ambiguities
+drand(dims::Dims, procs::Tuple{Vararg{Int}}) = drand(Float64, dims, procs)
+drand(dims::Dims, procs::Tuple{Vararg{Int}}, dist) = drand(Float64, dims, procs, dist)
+drand(X::Tuple{Vararg{Int}}, dim::Integer) = drand(X, Dims((dim,)))
+drand(X::Tuple{Vararg{Int}}, d1::Integer, d2::Integer) = drand(X, Dims((d1, d2)))
 
 """
      drandn(dims, ...)
@@ -620,7 +648,7 @@ allowscalar(flag = true) = (_allowscalar[] = flag)
 _scalarindexingallowed() = _allowscalar[] || throw(ErrorException("scalar indexing disabled"))
 
 getlocalindex(d::DArray, idx...) = localpart(d)[idx...]
-function getindex_tuple(d::DArray{T}, I::Tuple{Vararg{Int}}) where T
+function getindex_tuple(d::DArray{T,N}, I::NTuple{N,Int}) where {T,N}
     chidx = locate(d, I...)
     idxs = d.indices[chidx...]
     localidx = ntuple(i -> (I[i] - first(idxs[i]) + 1), ndims(d))
@@ -632,11 +660,13 @@ function Base.getindex(d::DArray, i::Int)
     _scalarindexingallowed()
     return getindex_tuple(d, Tuple(CartesianIndices(d)[i]))
 end
-function Base.getindex(d::DArray, i::Int...)
+function Base.getindex(d::DArray{<:Any,N}, i::Vararg{Int,N}) where {N}
     _scalarindexingallowed()
     return getindex_tuple(d, i)
 end
-
+function Base.getindex(d::DArray{<:Any,N}, I::Vararg{Any,N}) where {N}
+    return view(d, I...)
+end                                                
 Base.getindex(d::DArray) = d[1]
 Base.getindex(d::SubDArray, I::Int...) = invoke(getindex, Tuple{SubArray{<:Any,N},Vararg{Int,N}} where N, d, I...)
 Base.getindex(d::SubOrDArray, I::Union{Int,UnitRange{Int},Colon,Vector{Int},StepRange{Int,Int}}...) = view(d, I...)
@@ -667,6 +697,15 @@ function Base.copyto!(dest::SubOrDArray, src::AbstractArray)
     return dest
 end
 
+# Fix method ambiguities
+# TODO: Improve efficiency?
+Base.copyto!(dest::SubOrDArray{<:Any,2}, src::SparseArrays.AbstractSparseMatrixCSC) = copyto!(dest, Matrix(src))
+@static if isdefined(SparseArrays, :CHOLMOD)
+    Base.copyto!(dest::SubOrDArray, src::SparseArrays.CHOLMOD.Dense) = copyto!(dest, Array(src))
+    Base.copyto!(dest::SubOrDArray{T}, src::SparseArrays.CHOLMOD.Dense{T}) where {T<:Union{Float32,Float64,ComplexF32,ComplexF64}} = copyto!(dest, Array(src))
+    Base.copyto!(dest::SubOrDArray{T,2}, src::SparseArrays.CHOLMOD.Dense{T}) where {T<:Union{Float32,Float64,ComplexF32,ComplexF64}} = copyto!(dest, Array(src))
+end
+
 function Base.deepcopy(src::DArray)
     dest = similar(src)
     @sync for p in procs(src)
diff --git a/src/mapreduce.jl b/src/mapreduce.jl
index 3df1e10..ff4254b 100644
--- a/src/mapreduce.jl
+++ b/src/mapreduce.jl
@@ -11,7 +11,13 @@ function Base.map!(f::F, dest::DArray, src::DArray{<:Any,<:Any,A}) where {F,A}
     return dest
 end
 
-function Base.reduce(f, d::DArray)
+# Only defining `reduce(f, ::DArray)` causes method ambiguity issues with
+# - `reduce(hcat, ::AbstractVector{<:AbstractVecOrMat})`
+# - `reduce(vcat, ::AbstractVector{<:AbstractVecOrMat})`
+Base.reduce(f, d::DArray) = _reduce(f, d)
+Base.reduce(::typeof(hcat), d::DArray{<:AbstractVecOrMat, 1}) = _reduce(hcat, d)
+Base.reduce(::typeof(vcat), d::DArray{<:AbstractVecOrMat, 1}) = _reduce(vcat, d)
+function _reduce(f, d::DArray)
     results = asyncmap(procs(d)) do p
         remotecall_fetch(p) do
             return reduce(f, localpart(d))
diff --git a/test/aqua.jl b/test/aqua.jl
new file mode 100644
index 0000000..ec7a70b
--- /dev/null
+++ b/test/aqua.jl
@@ -0,0 +1,6 @@
+using DistributedArrays, Test
+import Aqua
+
+@testset "Aqua" begin
+    Aqua.test_all(DistributedArrays)
+end
diff --git a/test/runtests.jl b/test/runtests.jl
index dcdf380..2c1da1d 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -36,6 +36,7 @@ function check_leaks()
     end
 end
 
+include("aqua.jl")
 include("explicit_imports.jl")
 include("darray.jl")
 include("spmd.jl")