diff --git a/NEWS.md b/NEWS.md
index 1126cb2d117962..8c7fbc1a523b88 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -509,6 +509,9 @@ Deprecated or removed
     particularly, consider instead `triu!(copy(parent(A)))`. On `LowerTriangular` matrices
     `A` particularly, consider instead `tril!(copy(parent(A)))` ([#24250]).
 
+  * `speye` has been deprecated in favor of `I`, `sparse`, and `SparseMatrixCSC`
+    constructor methods ([#24356]).
+
   * Calling `union` with no arguments is deprecated; construct an empty set with an appropriate
     element type using `Set{T}()` instead ([#23144]).
 
diff --git a/base/deprecated.jl b/base/deprecated.jl
index ee81e772f9360a..8fc2b2c1e554cf 100644
--- a/base/deprecated.jl
+++ b/base/deprecated.jl
@@ -2070,6 +2070,55 @@ end
 # deprecate bits to bitstring (#24263, #24281)
 @deprecate bits bitstring
 
+# deprecate speye
+export speye
+function speye(n::Integer)
+    depwarn(string("`speye(n::Integer)` has been deprecated in favor of `I`, `sparse`, and ",
+                    "`SparseMatrixCSC` constructor methods. For a direct replacement, consider ",
+                    "`sparse(1.0I, n, n)`, `SparseMatrixCSC(1.0I, n, n)`, or `SparseMatrixCSC{Float64}(I, n, n)`. ",
+                    "If `Float64` element type is not necessary, consider the shorter `sparse(I, n, n)` ",
+                    "or `SparseMatrixCSC(I, n, n)` (with default `eltype(I)` of `Bool`)."), :speye)
+    return sparse(1.0I, n, n)
+end
+function speye(m::Integer, n::Integer)
+    depwarn(string("`speye(m::Integer, n::Integer)` has been deprecated in favor of `I`, ",
+                    "`sparse`, and `SparseMatrixCSC` constructor methods. For a direct ",
+                    "replacement, consider `sparse(1.0I, m, n)`, `SparseMatrixCSC(1.0I, m, n)`, ",
+                    "or `SparseMatrixCSC{Float64}(I, m, n)`. If `Float64` element type is not ",
+                    " necessary, consider the shorter `sparse(I, m, n)` or `SparseMatrixCSC(I, m, n)` ",
+                    "(with default `eltype(I)` of `Bool`)."), :speye)
+    return sparse(1.0I, m, n)
+end
+function speye(::Type{T}, n::Integer) where T
+    depwarn(string("`speye(T, n::Integer)` has been deprecated in favor of `I`, `sparse`, and ",
+                    "`SparseMatrixCSC` constructor methods. For a direct replacement, consider ",
+                    "`sparse(T(1)I, n, n)` if `T` is concrete or `SparseMatrixCSC{T}(I, n, n)` ",
+                    "if `T` is either concrete or abstract. If element type `T` is not necessary, ",
+                    "consider the shorter `sparse(I, n, n)` or `SparseMatrixCSC(I, n, n)` ",
+                    "(with default `eltype(I)` of `Bool`)."), :speye)
+    return SparseMatrixCSC{T}(I, n)
+end
+function speye(::Type{T}, m::Integer, n::Integer) where T
+    depwarn(string("`speye(T, m::Integer, n::Integer)` has been deprecated in favor of `I`, ",
+                    "`sparse`, and `SparseMatrixCSC` constructor methods. For a direct ",
+                    "replacement, consider `sparse(T(1)I, m, n)` if `T` is concrete or ",
+                    "`SparseMatrixCSC{T}(I, m, n)` if `T` is either concrete or abstract. ",
+                    "If element type `T` is not necessary, consider the shorter ",
+                    "`sparse(I, m, n)` or `SparseMatrixCSC(I, m, n)` (with default `eltype(I)` ",
+                    "of `Bool`)."), :speye)
+    return SparseMatrixCSC{T}(I, m, n)
+end
+function speye(S::SparseMatrixCSC{T}) where T
+    depwarn(string("`speye(S::SparseMatrixCSC{T})` has been deprecated in favor of `I`, ",
+                    "`sparse`, and `SparseMatrixCSC` constructor methods. For a direct ",
+                    "replacement, consider `sparse(T(1)I, size(S)...)` if `T` is concrete or ",
+                    "`SparseMatrixCSC{eltype(S)}(I, size(S))` if `T` is either concrete or abstract. ",
+                    "If preserving element type `T` is not necessary, consider the shorter ",
+                    "`sparse(I, size(S)...)` or `SparseMatrixCSC(I, size(S))` (with default ",
+                    "`eltype(I)` of `Bool`)."), :speye)
+    return SparseMatrixCSC{T}(I, m, n)
+end
+
 # issue #24167
 @deprecate EnvHash EnvDict
 
diff --git a/base/essentials.jl b/base/essentials.jl
index cc4e01f647709c..cdfc50f9a272f0 100644
--- a/base/essentials.jl
+++ b/base/essentials.jl
@@ -119,7 +119,7 @@ true
 Similarly, if `T` is a composite type and `x` a related instance, the result of
 `convert(T, x)` may alias part or all of `x`.
 ```jldoctest
-julia> x = speye(5);
+julia> x = sparse(1.0I, 5, 5);
 
 julia> typeof(x)
 SparseMatrixCSC{Float64,Int64}
diff --git a/base/exports.jl b/base/exports.jl
index 0e30396010261f..df357ab5e28b33 100644
--- a/base/exports.jl
+++ b/base/exports.jl
@@ -1256,7 +1256,6 @@ export
     sparse,
     sparsevec,
     spdiagm,
-    speye,
     spones,
     sprand,
     sprandn,
diff --git a/base/linalg/arnoldi.jl b/base/linalg/arnoldi.jl
index 70e696c83eb669..fe05312d94f27e 100644
--- a/base/linalg/arnoldi.jl
+++ b/base/linalg/arnoldi.jl
@@ -145,7 +145,7 @@ final residual vector `resid`.
 
 # Examples
 ```jldoctest
-julia> A = speye(4, 4); B = Diagonal(1:4);
+julia> A = sparse(1.0I, 4, 4); B = Diagonal(1:4);
 
 julia> λ, ϕ = eigs(A, B, nev = 2);
 
diff --git a/base/sparse/cholmod.jl b/base/sparse/cholmod.jl
index 4939f1af57890b..49114148e96c3d 100644
--- a/base/sparse/cholmod.jl
+++ b/base/sparse/cholmod.jl
@@ -16,7 +16,7 @@ export
     Factor,
     Sparse
 
-import ..SparseArrays: AbstractSparseMatrix, SparseMatrixCSC, increment, indtype, sparse, speye,
+import ..SparseArrays: AbstractSparseMatrix, SparseMatrixCSC, increment, indtype, sparse,
     spzeros, nnz
 
 #########
diff --git a/base/sparse/sparse.jl b/base/sparse/sparse.jl
index 4bffa183a8fbb9..af3b16bc873dcb 100644
--- a/base/sparse/sparse.jl
+++ b/base/sparse/sparse.jl
@@ -31,7 +31,7 @@ import Base: @get!, acos, acosd, acot, acotd, acsch, asech, asin, asind, asinh,
 
 export AbstractSparseArray, AbstractSparseMatrix, AbstractSparseVector,
     SparseMatrixCSC, SparseVector, blkdiag, droptol!, dropzeros!, dropzeros,
-    issparse, nonzeros, nzrange, rowvals, sparse, sparsevec, spdiagm, speye, spones,
+    issparse, nonzeros, nzrange, rowvals, sparse, sparsevec, spdiagm, spones,
     sprand, sprandn, spzeros, nnz, permute
 
 include("abstractsparse.jl")
diff --git a/base/sparse/sparsematrix.jl b/base/sparse/sparsematrix.jl
index 32c242a7a19841..0d80afc3a8f3d7 100644
--- a/base/sparse/sparsematrix.jl
+++ b/base/sparse/sparsematrix.jl
@@ -59,11 +59,11 @@ Returns the number of stored (filled) elements in a sparse array.
 
 # Examples
 ```jldoctest
-julia> A = speye(3)
-3×3 SparseMatrixCSC{Float64,Int64} with 3 stored entries:
-  [1, 1]  =  1.0
-  [2, 2]  =  1.0
-  [3, 3]  =  1.0
+julia> A = sparse(2I, 3, 3)
+3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:
+  [1, 1]  =  2
+  [2, 2]  =  2
+  [3, 3]  =  2
 
 julia> nnz(A)
 3
@@ -83,17 +83,17 @@ modifications to the returned vector will mutate `A` as well. See
 
 # Examples
 ```jldoctest
-julia> A = speye(3)
-3×3 SparseMatrixCSC{Float64,Int64} with 3 stored entries:
-  [1, 1]  =  1.0
-  [2, 2]  =  1.0
-  [3, 3]  =  1.0
+julia> A = sparse(2I, 3, 3)
+3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:
+  [1, 1]  =  2
+  [2, 2]  =  2
+  [3, 3]  =  2
 
 julia> nonzeros(A)
-3-element Array{Float64,1}:
- 1.0
- 1.0
- 1.0
+3-element Array{Int64,1}:
+ 2
+ 2
+ 2
 ```
 """
 nonzeros(S::SparseMatrixCSC) = S.nzval
@@ -108,11 +108,11 @@ nonzero values. See also [`nonzeros`](@ref) and [`nzrange`](@ref).
 
 # Examples
 ```jldoctest
-julia> A = speye(3)
-3×3 SparseMatrixCSC{Float64,Int64} with 3 stored entries:
-  [1, 1]  =  1.0
-  [2, 2]  =  1.0
-  [3, 3]  =  1.0
+julia> A = sparse(2I, 3, 3)
+3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:
+  [1, 1]  =  2
+  [2, 2]  =  2
+  [3, 3]  =  2
 
 julia> rowvals(A)
 3-element Array{Int64,1}:
@@ -1453,8 +1453,6 @@ julia> spones(A)
   [3, 3]  =  1.0
   [2, 4]  =  1.0
 ```
-
-Note the difference from [`speye`](@ref).
 """
 spones(S::SparseMatrixCSC{T}) where {T} =
      SparseMatrixCSC(S.m, S.n, copy(S.colptr), copy(S.rowval), ones(T, S.colptr[end]-1))
@@ -1487,55 +1485,11 @@ function spzeros(::Type{Tv}, ::Type{Ti}, sz::Tuple{Integer,Integer}) where {Tv,
     spzeros(Tv, Ti, sz[1], sz[2])
 end
 
-speye(n::Integer) = speye(Float64, n)
-speye(::Type{T}, n::Integer) where {T} = speye(T, n, n)
-speye(m::Integer, n::Integer) = speye(Float64, m, n)
-
-"""
-    speye(S)
-
-Create a sparse identity matrix with the same size as `S`.
-
-# Examples
-```jldoctest
-julia> A = sparse([1,2,3,4],[2,4,3,1],[5.,4.,3.,2.])
-4×4 SparseMatrixCSC{Float64,Int64} with 4 stored entries:
-  [4, 1]  =  2.0
-  [1, 2]  =  5.0
-  [3, 3]  =  3.0
-  [2, 4]  =  4.0
-
-julia> speye(A)
-4×4 SparseMatrixCSC{Float64,Int64} with 4 stored entries:
-  [1, 1]  =  1.0
-  [2, 2]  =  1.0
-  [3, 3]  =  1.0
-  [4, 4]  =  1.0
-```
-
-Note the difference from [`spones`](@ref).
-"""
-speye(S::SparseMatrixCSC{T}) where {T} = speye(T, size(S, 1), size(S, 2))
-eye(S::SparseMatrixCSC) = speye(S)
-
-"""
-    speye([type,]m[,n])
-
-Create a sparse identity matrix of size `m x m`. When `n` is supplied,
-create a sparse identity matrix of size `m x n`. The type defaults to [`Float64`](@ref)
-if not specified.
-
-`sparse(I, m, n)` is equivalent to `speye(Int, m, n)`, and
-`sparse(α*I, m, n)` can be used to efficiently create a sparse
-multiple `α` of the identity matrix.
-"""
-speye(::Type{T}, m::Integer, n::Integer) where {T} = SparseMatrixCSC{T}(UniformScaling(one(T)), Dims((m, n)))
-sparse(s::UniformScaling, m::Integer, n::Integer=m) = SparseMatrixCSC(s, Dims((m, n)))
+eye(S::SparseMatrixCSC{T}) where {T} = SparseMatrixCSC{T}(I, size(S))
 
 function one(S::SparseMatrixCSC{T}) where T
-    m,n = size(S)
-    if m != n; throw(DimensionMismatch("multiplicative identity only defined for square matrices")); end
-    speye(T, m)
+    S.m == S.n || throw(DimensionMismatch("multiplicative identity only defined for square matrices"))
+    return SparseMatrixCSC{T}(I, S.m, S.n)
 end
 
 ## SparseMatrixCSC construction from UniformScaling
@@ -1573,6 +1527,7 @@ function Base.isone(A::SparseMatrixCSC)
     return true
 end
 
+sparse(s::UniformScaling, m::Integer, n::Integer=m) = SparseMatrixCSC(s, m, n)
 
 # TODO: More appropriate location?
 conj!(A::SparseMatrixCSC) = (@inbounds broadcast!(conj, A.nzval, A.nzval); A)
@@ -3141,13 +3096,13 @@ Concatenate matrices block-diagonally. Currently only implemented for sparse mat
 
 # Examples
 ```jldoctest
-julia> blkdiag(speye(3), 2*speye(2))
-5×5 SparseMatrixCSC{Float64,Int64} with 5 stored entries:
-  [1, 1]  =  1.0
-  [2, 2]  =  1.0
-  [3, 3]  =  1.0
-  [4, 4]  =  2.0
-  [5, 5]  =  2.0
+julia> blkdiag(sparse(2I, 3, 3), sparse(4I, 2, 2))
+5×5 SparseMatrixCSC{Int64,Int64} with 5 stored entries:
+  [1, 1]  =  2
+  [2, 2]  =  2
+  [3, 3]  =  2
+  [4, 4]  =  4
+  [5, 5]  =  4
 ```
 """
 function blkdiag(X::SparseMatrixCSC...)
@@ -3599,6 +3554,6 @@ end
 
 ## Uniform matrix arithmetic
 
-(+)(A::SparseMatrixCSC, J::UniformScaling) = A + J.λ * speye(A)
-(-)(A::SparseMatrixCSC, J::UniformScaling) = A - J.λ * speye(A)
-(-)(J::UniformScaling, A::SparseMatrixCSC) = J.λ * speye(A) - A
+(+)(A::SparseMatrixCSC, J::UniformScaling) = A + sparse(J, size(A)...)
+(-)(A::SparseMatrixCSC, J::UniformScaling) = A - sparse(J, size(A)...)
+(-)(J::UniformScaling, A::SparseMatrixCSC) = sparse(J, size(A)...) - A
diff --git a/doc/src/manual/arrays.md b/doc/src/manual/arrays.md
index 0bc4a53a53f8fb..916b8695c5099f 100644
--- a/doc/src/manual/arrays.md
+++ b/doc/src/manual/arrays.md
@@ -781,19 +781,13 @@ stored zeros. (See [Sparse Matrix Storage](@ref man-csc).).
 
 ### Sparse Vector and Matrix Constructors
 
-The simplest way to create sparse arrays is to use functions equivalent to the [`zeros`](@ref)
-and [`eye`](@ref) functions that Julia provides for working with dense arrays. To produce
-sparse arrays instead, you can use the same names with an `sp` prefix:
+The simplest way to create a sparse array is to use a function equivalent to the [`zeros`](@ref)
+function that Julia provides for working with dense arrays. To produce a
+sparse array instead, you can use the same name with an `sp` prefix:
 
 ```jldoctest
 julia> spzeros(3)
 3-element SparseVector{Float64,Int64} with 0 stored entries
-
-julia> speye(3,5)
-3×5 SparseMatrixCSC{Float64,Int64} with 3 stored entries:
-  [1, 1]  =  1.0
-  [2, 2]  =  1.0
-  [3, 3]  =  1.0
 ```
 
 The [`sparse`](@ref) function is often a handy way to construct sparse arrays. For
@@ -867,7 +861,7 @@ You can go in the other direction using the [`Array`](@ref) constructor. The [`i
 function can be used to query if a matrix is sparse.
 
 ```jldoctest
-julia> issparse(speye(5))
+julia> issparse(spzeros(5))
 true
 ```
 
@@ -895,7 +889,7 @@ section of the standard library reference.
 |:-------------------------- |:---------------------- |:--------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | [`spzeros(m,n)`](@ref)     | [`zeros(m,n)`](@ref)   | Creates a *m*-by-*n* matrix of zeros. ([`spzeros(m,n)`](@ref) is empty.)                                                                                              |
 | [`spones(S)`](@ref)        | [`ones(m,n)`](@ref)    | Creates a matrix filled with ones. Unlike the dense version, [`spones`](@ref) has the same sparsity pattern as *S*.                                                 |
-| [`speye(n)`](@ref)         | [`eye(n)`](@ref)       | Creates a *n*-by-*n* identity matrix.                                                                                                                                 |
+| [`sparse(I, n, n)`](@ref)  | [`eye(n)`](@ref)       | Creates a *n*-by-*n* identity matrix.                                                                                                                                 |
 | [`Array(S)`](@ref)         | [`sparse(A)`](@ref)    | Interconverts between dense and sparse formats.                                                                                                                       |
 | [`sprand(m,n,d)`](@ref)    | [`rand(m,n)`](@ref)    | Creates a *m*-by-*n* random matrix (of density *d*) with iid non-zero elements distributed uniformly on the half-open interval ``[0, 1)``.                            |
 | [`sprandn(m,n,d)`](@ref)   | [`randn(m,n)`](@ref)   | Creates a *m*-by-*n* random matrix (of density *d*) with iid non-zero elements distributed according to the standard normal (Gaussian) distribution.                  |
diff --git a/doc/src/stdlib/arrays.md b/doc/src/stdlib/arrays.md
index 0073510805c5f7..03669888f18f93 100644
--- a/doc/src/stdlib/arrays.md
+++ b/doc/src/stdlib/arrays.md
@@ -188,8 +188,6 @@ Base.SparseArrays.issparse
 Base.SparseArrays.nnz
 Base.SparseArrays.spzeros
 Base.SparseArrays.spones
-Base.SparseArrays.speye(::Type, ::Integer, ::Integer)
-Base.SparseArrays.speye(::SparseMatrixCSC)
 Base.SparseArrays.spdiagm
 Base.SparseArrays.sprand
 Base.SparseArrays.sprandn
diff --git a/test/arrayops.jl b/test/arrayops.jl
index 7fb1ef21890f3e..89aeb76bf3201c 100644
--- a/test/arrayops.jl
+++ b/test/arrayops.jl
@@ -1008,7 +1008,7 @@ end
     @test m[1,2] == ([2,4],)
 
     # issue #21123
-    @test mapslices(nnz, speye(3), 1) == [1 1 1]
+    @test mapslices(nnz, sparse(1.0I, 3, 3), 1) == [1 1 1]
 end
 
 @testset "single multidimensional index" begin
diff --git a/test/hashing.jl b/test/hashing.jl
index e2f277ab5b61ce..703dcb9a412532 100644
--- a/test/hashing.jl
+++ b/test/hashing.jl
@@ -73,7 +73,7 @@ vals = Any[
     Dict(x => x for x in 1:10),
     Dict(7=>7,9=>9,4=>4,10=>10,2=>2,3=>3,8=>8,5=>5,6=>6,1=>1),
     [], [1], [2], [1, 1], [1, 2], [1, 3], [2, 2], [1, 2, 2], [1, 3, 3],
-    zeros(2, 2), spzeros(2, 2), eye(2, 2), speye(2, 2),
+    zeros(2, 2), spzeros(2, 2), eye(2, 2), sparse(1.0I, 2, 2),
     sparse(ones(2, 2)), ones(2, 2), sparse([0 0; 1 0]), [0 0; 1 0],
     [-0. 0; -0. 0.], SparseMatrixCSC(2, 2, [1, 3, 3], [1, 2], [-0., -0.])
 ]
diff --git a/test/linalg/arnoldi.jl b/test/linalg/arnoldi.jl
index e6950f32255d44..7ec173bcd018be 100644
--- a/test/linalg/arnoldi.jl
+++ b/test/linalg/arnoldi.jl
@@ -178,7 +178,7 @@ let
     # Adjust the tolerance a bit since matrices with repeated eigenvalues
     # can be very stressful to ARPACK and this may therefore fail with
     # info = 3 if the tolerance is too small
-    @test eigs(speye(50), nev=10, tol = 5e-16)[1] ≈ ones(10) #Issue 4246
+    @test eigs(sparse(1.0I, 50, 50), nev=10, tol = 5e-16)[1] ≈ ones(10) #Issue 4246
 end
 
 @testset "real svds" begin
diff --git a/test/linalg/special.jl b/test/linalg/special.jl
index bc1cfb0f34bafa..295882508eaf82 100644
--- a/test/linalg/special.jl
+++ b/test/linalg/special.jl
@@ -178,7 +178,7 @@ end
     annotations = testfull ? (triannotations..., symannotations...) : (LowerTriangular, Symmetric)
     # Concatenations involving these types, un/annotated, should yield sparse arrays
     spvec = spzeros(N)
-    spmat = speye(N)
+    spmat = sparse(1.0I, N, N)
     diagmat = Diagonal(ones(N))
     bidiagmat = Bidiagonal(ones(N), ones(N-1), :U)
     tridiagmat = Tridiagonal(ones(N-1), ones(N), ones(N-1))
diff --git a/test/linalg/uniformscaling.jl b/test/linalg/uniformscaling.jl
index c506f7c7ef5e70..82833b19f9fb73 100644
--- a/test/linalg/uniformscaling.jl
+++ b/test/linalg/uniformscaling.jl
@@ -82,7 +82,7 @@ let
         @test B + I == B + eye(B)
         @test I + B == B + eye(B)
         AA = randn(2, 2)
-        for SS in (sprandn(3,3, 0.5), speye(Int, 3))
+        for SS in (sprandn(3,3, 0.5), sparse(Int(1)I, 3, 3))
             for (A, S) in ((AA, SS), (view(AA, 1:2, 1:2), view(SS, 1:3, 1:3)))
                 @test @inferred(A + I) == A + eye(A)
                 @test @inferred(I + A) == A + eye(A)
diff --git a/test/perf/kernel/getdivgrad.jl b/test/perf/kernel/getdivgrad.jl
index 04ba5663d8ab6a..d0db3b0eca6a9d 100644
--- a/test/perf/kernel/getdivgrad.jl
+++ b/test/perf/kernel/getdivgrad.jl
@@ -5,9 +5,9 @@
 #----------------- Get the A matrix
 function getDivGrad(n1,n2,n3)
     # the Divergence
-    D1 = kron(speye(n3),kron(speye(n2),ddx(n1)))
-    D2 = kron(speye(n3),kron(ddx(n2),speye(n1)))
-    D3 = kron(ddx(n3),kron(speye(n2),speye(n1)))
+    D1 = kron(sparse(1.0I, n3, n3), kron(sparse(1.0I, n2), ddx(n1)))
+    D2 = kron(sparse(1.0I, n3, n3), kron(ddx(n2), sparse(1.0I, n1, n1)))
+    D3 = kron(ddx(n3), kron(sparse(1.0I, n2, n2), sparse(1.0I, n1, n1)))
     # DIV from faces to cell-centers
     Div = [D1 D2 D3]
 
diff --git a/test/perf/sparse/fem.jl b/test/perf/sparse/fem.jl
index 80559921c9eba1..63940cdf1cf9d5 100644
--- a/test/perf/sparse/fem.jl
+++ b/test/perf/sparse/fem.jl
@@ -7,7 +7,7 @@ function fdlaplacian(N)
     # create a 1D laplacian and a sparse identity
     fdl1 = spdiagm(-1 => ones(N-1), 0 => -2*ones(N), 1 => ones(N-1))
     # laplace operator on the full grid
-    return kron(speye(N), fdl1) + kron(fdl1, speye(N))
+    return kron(sparse(1.0I, N, N), fdl1) + kron(fdl1, sparse(1.0I, N, N))
 end
 
 # get the list of boundary dof-indices
diff --git a/test/show.jl b/test/show.jl
index a3075d722ba16f..97aba3140b2ff3 100644
--- a/test/show.jl
+++ b/test/show.jl
@@ -492,7 +492,7 @@ end
 # issue #12960
 mutable struct T12960 end
 let
-    A = speye(3)
+    A = sparse(1.0I, 3, 3)
     B = similar(A, T12960)
     @test sprint(show, B)  == "\n  [1, 1]  =  #undef\n  [2, 2]  =  #undef\n  [3, 3]  =  #undef"
     @test sprint(print, B) == "\n  [1, 1]  =  #undef\n  [2, 2]  =  #undef\n  [3, 3]  =  #undef"
diff --git a/test/sparse/cholmod.jl b/test/sparse/cholmod.jl
index 256732c71c3083..410d54090e8d1a 100644
--- a/test/sparse/cholmod.jl
+++ b/test/sparse/cholmod.jl
@@ -188,7 +188,7 @@ end
 end
 
 @testset "Issue #9915" begin
-    @test speye(2)\speye(2) == eye(2)
+    @test sparse(1.0I, 2, 2) \ sparse(1.0I, 2, 2) == eye(2)
 end
 
 @testset "test Sparse constructor Symmetric and Hermitian input (and issymmetric and ishermitian)" begin
@@ -660,12 +660,12 @@ end
 end
 
 @testset "Further issue with promotion #14894" begin
-    @test cholfact(speye(Float16, 5))\ones(5) == ones(5)
-    @test cholfact(Symmetric(speye(Float16, 5)))\ones(5) == ones(5)
-    @test cholfact(Hermitian(speye(Complex{Float16}, 5)))\ones(5) == ones(Complex{Float64}, 5)
-    @test_throws MethodError cholfact(speye(BigFloat, 5))
-    @test_throws MethodError cholfact(Symmetric(speye(BigFloat, 5)))
-    @test_throws MethodError cholfact(Hermitian(speye(Complex{BigFloat}, 5)))
+    @test cholfact(sparse(Float16(1)I, 5, 5))\ones(5) == ones(5)
+    @test cholfact(Symmetric(sparse(Float16(1)I, 5, 5)))\ones(5) == ones(5)
+    @test cholfact(Hermitian(sparse(Complex{Float16}(1)I, 5, 5)))\ones(5) == ones(Complex{Float64}, 5)
+    @test_throws MethodError cholfact(sprase(BigFloat(1)I, 5, 5))
+    @test_throws MethodError cholfact(Symmetric(sparse(BigFloat(1)I, 5, 5)))
+    @test_throws MethodError cholfact(Hermitian(sparse(Complex{BigFloat}(1)I, 5, 5)))
 end
 
 @testset "test \\ for Factor and StridedVecOrMat" begin
@@ -684,7 +684,7 @@ end
 @testset "Make sure that ldltfact performs an LDLt (Issue #19032)" begin
     m, n = 400, 500
     A = sprandn(m, n, .2)
-    M = [speye(n) A'; A -speye(m)]
+    M = [I A'; A -I]
     b = M * ones(m + n)
     F = ldltfact(M)
     s = unsafe_load(pointer(F))
@@ -730,11 +730,12 @@ end
 end
 
 @testset "sparse right multiplication of Symmetric and Hermitian matrices #21431" begin
-    @test issparse(speye(2)*speye(2)*speye(2))
+    S = sparse(1.0I, 2, 2)
+    @test issparse(S*S*S)
     for T in (Symmetric, Hermitian)
-        @test issparse(speye(2)*T(speye(2))*speye(2))
-        @test issparse(speye(2)*(T(speye(2))*speye(2)))
-        @test issparse((speye(2)*T(speye(2)))*speye(2))
+        @test issparse(S*T(S)*S)
+        @test issparse(S*(T(S)*S))
+        @test issparse((S*T(S))*S)
     end
 end
 
@@ -780,7 +781,7 @@ end
 
 @testset "Issue #22335" begin
     local A, F
-    A = speye(3)
+    A = sparse(1.0I, 3, 3)
     @test LinAlg.issuccess(cholfact(A))
     A[3, 3] = -1
     F = cholfact(A)
diff --git a/test/sparse/higherorderfns.jl b/test/sparse/higherorderfns.jl
index 4eddb17ed1605e..3e716a95bbd809 100644
--- a/test/sparse/higherorderfns.jl
+++ b/test/sparse/higherorderfns.jl
@@ -269,7 +269,7 @@ end
 
 @testset "sparse map/broadcast with result eltype not a concrete subtype of Number (#19561/#19589)" begin
     N = 4
-    A, fA = speye(N), eye(N)
+    A, fA = sparse(1.0I, N, N), eye(N)
     B, fB = spzeros(1, N), zeros(1, N)
     intorfloat_zeropres(xs...) = all(iszero, xs) ? zero(Float64) : Int(1)
     stringorfloat_zeropres(xs...) = all(iszero, xs) ? zero(Float64) : "hello"
diff --git a/test/sparse/sparse.jl b/test/sparse/sparse.jl
index 29a611454affaf..769c88f66a0900 100644
--- a/test/sparse/sparse.jl
+++ b/test/sparse/sparse.jl
@@ -52,7 +52,7 @@ end
     @test SparseMatrixCSC{Float64,Int32}(0I, 3, 3)::SparseMatrixCSC{Float64,Int32} == spzeros(Float64, Int32, 3, 3)
 end
 
-se33 = speye(3)
+se33 = SparseMatrixCSC{Float64}(I, 3, 3)
 do33 = ones(3)
 
 @testset "sparse binary operations" begin
@@ -75,7 +75,7 @@ do33 = ones(3)
 end
 
 @testset "concatenation tests" begin
-    sp33 = speye(3, 3)
+    sp33 = sparse(1.0I, 3, 3)
 
     @testset "horizontal concatenation" begin
         @test all([se33 se33] == sparse([1, 2, 3, 1, 2, 3], [1, 2, 3, 4, 5, 6], ones(6)))
@@ -89,11 +89,11 @@ end
         @test length(([sp33; 0I]).nzval) == 3
     end
 
-    se44 = speye(4)
+    se44 = sparse(1.0I, 4, 4)
     sz42 = spzeros(4, 2)
     sz41 = spzeros(4, 1)
     sz34 = spzeros(3, 4)
-    se77 = speye(7)
+    se77 = sparse(1.0I, 7, 7)
     @testset "h+v concatenation" begin
         @test all([se44 sz42 sz41; sz34 se33] == se77)
         @test length(([sp33 0I; 1I 0I]).nzval) == 6
@@ -105,7 +105,7 @@ end
 
     @testset "concatenation promotion" begin
         sz41_f32 = spzeros(Float32, 4, 1)
-        se33_i32 = speye(Int32, 3, 3)
+        se33_i32 = sparse(Int32(1)I, 3, 3)
         @test all([se44 sz42 sz41_f32; sz34 se33_i32] == se77)
     end
 
@@ -181,7 +181,7 @@ end
 @testset "complex matrix-vector multiplication and left-division" begin
     if Base.USE_GPL_LIBS
     for i = 1:5
-        a = speye(5) + 0.1*sprandn(5, 5, 0.2)
+        a = I + 0.1*sprandn(5, 5, 0.2)
         b = randn(5,3) + im*randn(5,3)
         c = randn(5) + im*randn(5)
         d = randn(5) + im*randn(5)
@@ -204,7 +204,7 @@ end
         @test_throws DimensionMismatch α*a.'*c + β*c
         @test_throws DimensionMismatch α*a.'*ones(5) + β*c
 
-        a = speye(5) + 0.1*sprandn(5, 5, 0.2) + 0.1*im*sprandn(5, 5, 0.2)
+        a = I + 0.1*sprandn(5, 5, 0.2) + 0.1*im*sprandn(5, 5, 0.2)
         b = randn(5,3)
         @test (maximum(abs.(a*b - Array(a)*b)) < 100*eps())
         @test (maximum(abs.(a'b - Array(a)'b)) < 100*eps())
@@ -213,7 +213,7 @@ end
         @test (maximum(abs.(a'\b - Array(a')\b)) < 1000*eps())
         @test (maximum(abs.(a.'\b - Array(a.')\b)) < 1000*eps())
 
-        a = speye(5) + tril(0.1*sprandn(5, 5, 0.2))
+        a = I + tril(0.1*sprandn(5, 5, 0.2))
         b = randn(5,3) + im*randn(5,3)
         @test (maximum(abs.(a*b - Array(a)*b)) < 100*eps())
         @test (maximum(abs.(a'b - Array(a)'b)) < 100*eps())
@@ -222,7 +222,7 @@ end
         @test (maximum(abs.(a'\b - Array(a')\b)) < 1000*eps())
         @test (maximum(abs.(a.'\b - Array(a.')\b)) < 1000*eps())
 
-        a = speye(5) + tril(0.1*sprandn(5, 5, 0.2) + 0.1*im*sprandn(5, 5, 0.2))
+        a = I + tril(0.1*sprandn(5, 5, 0.2) + 0.1*im*sprandn(5, 5, 0.2))
         b = randn(5,3)
         @test (maximum(abs.(a*b - Array(a)*b)) < 100*eps())
         @test (maximum(abs.(a'b - Array(a)'b)) < 100*eps())
@@ -231,7 +231,7 @@ end
         @test (maximum(abs.(a'\b - Array(a')\b)) < 1000*eps())
         @test (maximum(abs.(a.'\b - Array(a.')\b)) < 1000*eps())
 
-        a = speye(5) + triu(0.1*sprandn(5, 5, 0.2))
+        a = I + triu(0.1*sprandn(5, 5, 0.2))
         b = randn(5,3) + im*randn(5,3)
         @test (maximum(abs.(a*b - Array(a)*b)) < 100*eps())
         @test (maximum(abs.(a'b - Array(a)'b)) < 100*eps())
@@ -240,7 +240,7 @@ end
         @test (maximum(abs.(a'\b - Array(a')\b)) < 1000*eps())
         @test (maximum(abs.(a.'\b - Array(a.')\b)) < 1000*eps())
 
-        a = speye(5) + triu(0.1*sprandn(5, 5, 0.2) + 0.1*im*sprandn(5, 5, 0.2))
+        a = I + triu(0.1*sprandn(5, 5, 0.2) + 0.1*im*sprandn(5, 5, 0.2))
         b = randn(5,3)
         @test (maximum(abs.(a*b - Array(a)*b)) < 100*eps())
         @test (maximum(abs.(a'b - Array(a)'b)) < 100*eps())
@@ -249,7 +249,7 @@ end
         @test (maximum(abs.(a'\b - Array(a')\b)) < 1000*eps())
         @test (maximum(abs.(a.'\b - Array(a.')\b)) < 1000*eps())
 
-        a = speye(5) + triu(0.1*sprandn(5, 5, 0.2))
+        a = I + triu(0.1*sprandn(5, 5, 0.2))
         b = randn(5,3) + im*randn(5,3)
         @test (maximum(abs.(a*b - Array(a)*b)) < 100*eps())
         @test (maximum(abs.(a'b - Array(a)'b)) < 100*eps())
@@ -259,10 +259,10 @@ end
         @test (maximum(abs.(a.'\b - Array(a.')\b)) < 1000*eps())
 
         # UpperTriangular/LowerTriangular solve
-        a = UpperTriangular(speye(5) + triu(0.1*sprandn(5, 5, 0.2)))
+        a = UpperTriangular(I + triu(0.1*sprandn(5, 5, 0.2)))
         b = sprandn(5, 5, 0.2)
         @test (maximum(abs.(a\b - Array(a)\Array(b))) < 1000*eps())
-        a = LowerTriangular(speye(5) + tril(0.1*sprandn(5, 5, 0.2)))
+        a = LowerTriangular(I + tril(0.1*sprandn(5, 5, 0.2)))
         b = sprandn(5, 5, 0.2)
         @test (maximum(abs.(a\b - Array(a)\Array(b))) < 1000*eps())
 
@@ -523,7 +523,7 @@ end
 end
 
 @testset "issue described in https://groups.google.com/d/msg/julia-users/Yq4dh8NOWBQ/GU57L90FZ3EJ" begin
-    A = speye(Bool, 5)
+    A = sparse(I, 5, 5)
     @test find(A) == find(x -> x == true, A) == find(Array(A))
 end
 
@@ -838,66 +838,68 @@ end
     @test count(!iszero, A) == nA
     @test A == B
 
-    A = speye(Int, 5)
-    I=1:10
+    A = sparse(Int(1)I, 5, 5)
+    lininds = 1:10
     X=reshape([trues(10); falses(15)],5,5)
-    @test A[I] == A[X] == [1,0,0,0,0,0,1,0,0,0]
-    A[I] = [1:10;]
-    @test A[I] == A[X] == collect(1:10)
-    A[I] = zeros(Int, 10)
+    @test A[lininds] == A[X] == [1,0,0,0,0,0,1,0,0,0]
+    A[lininds] = [1:10;]
+    @test A[lininds] == A[X] == collect(1:10)
+    A[lininds] = zeros(Int, 10)
     @test nnz(A) == 13
     @test count(!iszero, A) == 3
-    @test A[I] == A[X] == zeros(Int, 10)
+    @test A[lininds] == A[X] == zeros(Int, 10)
     c = collect(11:20); c[1] = c[3] = 0
-    A[I] = c
+    A[lininds] = c
     @test nnz(A) == 13
     @test count(!iszero, A) == 11
-    @test A[I] == A[X] == c
-    A = speye(Int, 5)
-    A[I] = c
+    @test A[lininds] == A[X] == c
+    A = sparse(Int(1)I, 5)
+    A[lininds] = c
     @test nnz(A) == 12
     @test count(!iszero, A) == 11
-    @test A[I] == A[X] == c
-
-    S = sprand(50, 30, 0.5, x -> round.(Int, rand(x) * 100))
-    I = sprand(Bool, 50, 30, 0.2)
-    FS = Array(S)
-    FI = Array(I)
-    @test sparse(FS[FI]) == S[I] == S[FI]
-    @test sum(S[FI]) + sum(S[.!FI]) == sum(S)
-    @test count(!iszero, I) == count(I)
-
-    sumS1 = sum(S)
-    sumFI = sum(S[FI])
-    nnzS1 = nnz(S)
-    S[FI] = 0
-    sumS2 = sum(S)
-    cnzS2 = count(!iszero, S)
-    @test sum(S[FI]) == 0
-    @test nnz(S) == nnzS1
-    @test (sum(S) + sumFI) == sumS1
-
-    S[FI] = 10
-    nnzS3 = nnz(S)
-    @test sum(S) == sumS2 + 10*sum(FI)
-    S[FI] = 0
-    @test sum(S) == sumS2
-    @test nnz(S) == nnzS3
-    @test count(!iszero, S) == cnzS2
-
-    S[FI] = [1:sum(FI);]
-    @test sum(S) == sumS2 + sum(1:sum(FI))
-
-    S = sprand(50, 30, 0.5, x -> round.(Int, rand(x) * 100))
-    N = length(S) >> 2
-    I = randperm(N) .* 4
-    J = randperm(N)
-    sumS1 = sum(S)
-    sumS2 = sum(S[I])
-    S[I] = 0
-    @test sum(S) == (sumS1 - sumS2)
-    S[I] = J
-    @test sum(S) == (sumS1 - sumS2 + sum(J))
+    @test A[lininds] == A[X] == c
+
+    let # prevent assignment to I from overwriting UniformSampling in enclosing scope
+        S = sprand(50, 30, 0.5, x -> round.(Int, rand(x) * 100))
+        I = sprand(Bool, 50, 30, 0.2)
+        FS = Array(S)
+        FI = Array(I)
+        @test sparse(FS[FI]) == S[I] == S[FI]
+        @test sum(S[FI]) + sum(S[.!FI]) == sum(S)
+        @test count(!iszero, I) == count(I)
+
+        sumS1 = sum(S)
+        sumFI = sum(S[FI])
+        nnzS1 = nnz(S)
+        S[FI] = 0
+        sumS2 = sum(S)
+        cnzS2 = count(!iszero, S)
+        @test sum(S[FI]) == 0
+        @test nnz(S) == nnzS1
+        @test (sum(S) + sumFI) == sumS1
+
+        S[FI] = 10
+        nnzS3 = nnz(S)
+        @test sum(S) == sumS2 + 10*sum(FI)
+        S[FI] = 0
+        @test sum(S) == sumS2
+        @test nnz(S) == nnzS3
+        @test count(!iszero, S) == cnzS2
+
+        S[FI] = [1:sum(FI);]
+        @test sum(S) == sumS2 + sum(1:sum(FI))
+
+        S = sprand(50, 30, 0.5, x -> round.(Int, rand(x) * 100))
+        N = length(S) >> 2
+        I = randperm(N) .* 4
+        J = randperm(N)
+        sumS1 = sum(S)
+        sumS2 = sum(S[I])
+        S[I] = 0
+        @test sum(S) == (sumS1 - sumS2)
+        S[I] = J
+        @test sum(S) == (sumS1 - sumS2 + sum(J))
+    end
 end
 
 @testset "dropstored!" begin
@@ -1129,7 +1131,7 @@ for (tup, rval, rind) in [((1,), ["b"], [2])]
 end
 
 @testset "findn" begin
-    b = findn( speye(4) )
+    b = findn( sparse(1.0I, 4, 4) )
     @test (length(b[1]) == 4)
     @test (length(b[2]) == 4)
 end
@@ -1148,7 +1150,7 @@ end
 
     #ensure we have preserved the correct dimensions!
 
-    a = speye(3,5)
+    a = sparse(1.0I, 3, 5)
     @test size(rot180(a)) == (3,5)
     @test size(rotr90(a)) == (5,3)
     @test size(rotl90(a)) == (5,3)
@@ -1291,7 +1293,7 @@ end
     @test Array(sparse([])) == zeros(0)
     @test_throws BoundsError sparse([])[1]
     @test_throws BoundsError sparse([])[1] = 1
-    x = speye(100)
+    x = sparse(1.0I, 100, 100)
     @test_throws BoundsError x[-10:10]
 end
 
@@ -1303,7 +1305,7 @@ end
 @testset "issue #10411" begin
     for (m,n) in ((2,-2),(-2,2),(-2,-2))
         @test_throws ArgumentError spzeros(m,n)
-        @test_throws ArgumentError speye(m,n)
+        @test_throws ArgumentError sparse(1.0I, m, n)
         @test_throws ArgumentError sprand(m,n,0.2)
     end
 end
@@ -1350,16 +1352,15 @@ end
 @testset "sparse" begin
     local A = sparse(ones(5, 5))
     @test sparse(A) == A
-    @test sparse([1:5;], [1:5;], 1) == speye(5)
+    @test sparse([1:5;], [1:5;], 1) == sparse(1.0I, 5, 5)
 end
 
-@testset "speye and one" begin
+@testset "sparse(I, ...) and one" begin
     local A = sparse(ones(5, 5))
-    @test speye(A) == speye(5)
-    @test eye(A) == speye(5)
-    @test one(A) == speye(5)
+    @test sparse(I, 5, 5)  == eye(A)
+    @test one(A)        == eye(A)
     @test_throws DimensionMismatch one(sprand(5, 6, 0.2))
-    @test eltype(speye(Real, 5, 5)) === Real
+    @test eltype(SparseMatrixCSC{Real}(I, 5, 5)) === Real
 end
 
 @testset "istriu/istril" begin
@@ -1425,7 +1426,7 @@ end
 
 @testset "trace" begin
     @test_throws DimensionMismatch trace(sparse(ones(5,6)))
-    @test trace(speye(5)) == 5
+    @test trace(sparse(1.0I, 5, 5)) == 5
 end
 
 @testset "spdiagm" begin
@@ -1465,7 +1466,7 @@ end
 end
 
 @testset "expandptr" begin
-    local A = speye(5)
+    local A = sparse(1.0I, 5, 5)
     @test Base.SparseArrays.expandptr(A.colptr) == collect(1:5)
     A[1,2] = 1
     @test Base.SparseArrays.expandptr(A.colptr) == [1; 2; 2; 3; 4; 5]
@@ -1506,7 +1507,7 @@ end
 @testset "ishermitian/issymmetric" begin
     local A
     # real matrices
-    A = speye(5,5)
+    A = sparse(1.0I, 5, 5)
     @test ishermitian(A) == true
     @test issymmetric(A) == true
     A[1,3] = 1.0
@@ -1517,14 +1518,14 @@ end
     @test issymmetric(A) == true
 
     # complex matrices
-    A = speye(5,5) + im*speye(5,5)
+    A = sparse((1.0 + 1.0im)I, 5, 5)
     @test ishermitian(A) == false
     @test issymmetric(A) == true
     A[1,4] = 1.0 + im
     @test ishermitian(A) == false
     @test issymmetric(A) == false
 
-    A = speye(Complex128, 5,5)
+    A = sparse(Complex128(1)I, 5, 5)
     A[3,2] = 1.0 + im
     @test ishermitian(A) == false
     @test issymmetric(A) == false
@@ -1537,7 +1538,7 @@ end
     @test issymmetric(A) == true
 
     # explicit zeros
-    A = speye(Complex128, 5,5)
+    A = sparse(Complex128(1)I, 5, 5)
     A[3,1] = 2
     A.nzval[2] = 0.0
     @test ishermitian(A) == true
@@ -1563,8 +1564,8 @@ end
 end
 
 @testset "equality ==" begin
-    A1 = speye(10)
-    A2 = speye(10)
+    A1 = sparse(1.0I, 10, 10)
+    A2 = sparse(1.0I, 10, 10)
     nonzeros(A1)[end]=0
     @test A1!=A2
     nonzeros(A1)[end]=1
@@ -1642,7 +1643,7 @@ end
     # make certain entries in nzval beyond
     # the range specified in colptr do not
     # impact vecnorm of a sparse matrix
-    foo = speye(4)
+    foo = sparse(1.0I, 4, 4)
     resize!(foo.nzval, 5)
     setindex!(foo.nzval, NaN, 5)
     @test vecnorm(foo) == 2.0
@@ -1719,7 +1720,7 @@ end
 end
 
 @testset "spones" begin
-    local A = 2. * speye(5, 5)
+    local A = sparse(2.0I, 5, 5)
     @test Array(spones(A)) == eye(Array(A))
 end
 
@@ -1896,7 +1897,7 @@ end
 end
 
 @testset "issue #14398" begin
-    @test transpose(view(speye(10), 1:5, 1:5)) ≈ eye(5,5)
+    @test transpose(view(sparse(I, 10, 10), 1:5, 1:5)) ≈ eye(5)
 end
 
 @testset "dropstored issue #20513" begin
@@ -2065,7 +2066,7 @@ end
 end
 
 @testset "similar with type conversion" begin
-    local A = speye(5)
+    local A = sparse(1.0I, 5, 5)
     @test size(similar(A, Complex128, Int)) == (5, 5)
     @test typeof(similar(A, Complex128, Int)) == SparseMatrixCSC{Complex128, Int}
     @test size(similar(A, Complex128, Int8)) == (5, 5)
@@ -2075,7 +2076,7 @@ end
 end
 
 @testset "similar for SparseMatrixCSC" begin
-    local A = speye(5)
+    local A = sparse(1.0I, 5, 5)
     # test similar without specifications (preserves stored-entry structure)
     simA = similar(A)
     @test typeof(simA) == typeof(A)
diff --git a/test/sparse/sparsevector.jl b/test/sparse/sparsevector.jl
index c622a67bf83ef1..8e9e908eb075bf 100644
--- a/test/sparse/sparsevector.jl
+++ b/test/sparse/sparsevector.jl
@@ -904,9 +904,9 @@ end
         sparsecomplexvecs = SparseVector[SparseVector(m, sprvec.nzind, complex.(sprvec.nzval, sprvec.nzval)) for sprvec in sparsefloatvecs]
 
         sprmat = sprand(m, m, 0.2)
-        sparsefloatmat = speye(m) + sprmat/(2m)
-        sparsecomplexmat = speye(m) + SparseMatrixCSC(m, m, sprmat.colptr, sprmat.rowval, complex.(sprmat.nzval, sprmat.nzval)/(4m))
-        sparseintmat = speye(Int, m)*10m + SparseMatrixCSC(m, m, sprmat.colptr, sprmat.rowval, round.(Int, sprmat.nzval*10))
+        sparsefloatmat = I + sprmat/(2m)
+        sparsecomplexmat = I + SparseMatrixCSC(m, m, sprmat.colptr, sprmat.rowval, complex.(sprmat.nzval, sprmat.nzval)/(4m))
+        sparseintmat = 10m*I + SparseMatrixCSC(m, m, sprmat.colptr, sprmat.rowval, round.(Int, sprmat.nzval*10))
 
         denseintmat = I*10m + rand(1:m, m, m)
         densefloatmat = I + randn(m, m)/(2m)
diff --git a/test/sparse/umfpack.jl b/test/sparse/umfpack.jl
index a99dac1c92413c..fe4193f82cefb4 100644
--- a/test/sparse/umfpack.jl
+++ b/test/sparse/umfpack.jl
@@ -1,7 +1,7 @@
 # This file is a part of Julia. License is MIT: https://julialang.org/license
 
 @testset "UMFPACK wrappers" begin
-    se33 = speye(3)
+    se33 = sparse(1.0I, 3, 3)
     do33 = ones(3)
     @test isequal(se33 \ do33, do33)
 
@@ -98,7 +98,7 @@
     end
 
     @testset "Issue #4523 - complex sparse \\" begin
-        x = speye(2) + im * speye(2)
+        x = sparse((1.0 + 1.0im)I, 2, 2)
         @test (x*(lufact(x) \ ones(2))) ≈ ones(2)
 
         @test det(sparse([1,3,3,1], [1,1,3,3], [1,1,1,1])) == 0
@@ -142,13 +142,13 @@
 
     @testset "Test aliasing" begin
         a = rand(5)
-        @test_throws ArgumentError Base.SparseArrays.UMFPACK.solve!(a, lufact(speye(5,5)), a, Base.SparseArrays.UMFPACK.UMFPACK_A)
+        @test_throws ArgumentError Base.SparseArrays.UMFPACK.solve!(a, lufact(sparse(1.0I, 5, 5)), a, Base.SparseArrays.UMFPACK.UMFPACK_A)
         aa = complex(a)
-        @test_throws ArgumentError Base.SparseArrays.UMFPACK.solve!(aa, lufact(complex(speye(5,5))), aa, Base.SparseArrays.UMFPACK.UMFPACK_A)
+        @test_throws ArgumentError Base.SparseArrays.UMFPACK.solve!(aa, lufact(sparse((1.0im)I, 5, 5)), aa, Base.SparseArrays.UMFPACK.UMFPACK_A)
     end
 
     @testset "Issues #18246,18244 - lufact sparse pivot" begin
-        A = speye(4)
+        A = sparse(1.0I, 4, 4)
         A[1:2,1:2] = [-.01 -200; 200 .001]
         F = lufact(A)
         @test F[:p] == [3 ; 4 ; 2 ; 1]
@@ -157,7 +157,7 @@
     @testset "Test that A[c|t]_ldiv_B!{T<:Complex}(X::StridedMatrix{T}, lu::UmfpackLU{Float64}, B::StridedMatrix{T}) works as expected." begin
         N = 10
         p = 0.5
-        A = N*speye(N) + sprand(N, N, p)
+        A = N*I + sprand(N, N, p)
         X = zeros(Complex{Float64}, N, N)
         B = complex.(rand(N, N), rand(N, N))
         luA, lufA = lufact(A), lufact(Array(A))