diff --git a/base/deprecated.jl b/base/deprecated.jl
index 2236f3c8081d76..3a110cfbbf8bfb 100644
--- a/base/deprecated.jl
+++ b/base/deprecated.jl
@@ -2056,6 +2056,13 @@ end
 # deprecate bits to bitstring (#24263, #24281)
 @deprecate bits bitstring
 
+# deprecate speye
+@deprecate speye(n::Integer)                                    sparse(1.0I, n)
+@deprecate speye(m::Integer, n::Integer)                        sparse(1.0I, m, n)
+@deprecate speye(::Type{T}, n::Integer) where {T}               sparse(UniformScaling(one(T)), n)
+@deprecate speye(::Type{T}, m::Integer, n::Integer) where {T}   sparse(UniformScaling(one(T)), m, n)
+@deprecate speye(S::SparseMatrixCSC{T}) where {T}               sparse(UniformScaling(one(T)), size(S)...)
+
 # issue #24167
 @deprecate EnvHash EnvDict
 
diff --git a/base/essentials.jl b/base/essentials.jl
index cc4e01f647709c..b76783dd40bce2 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);
 
 julia> typeof(x)
 SparseMatrixCSC{Float64,Int64}
diff --git a/base/exports.jl b/base/exports.jl
index cbebc40c25be45..d96162a8154fd6 100644
--- a/base/exports.jl
+++ b/base/exports.jl
@@ -1267,7 +1267,6 @@ export
     sparse,
     sparsevec,
     spdiagm,
-    speye,
     spones,
     sprand,
     sprandn,
diff --git a/base/linalg/arnoldi.jl b/base/linalg/arnoldi.jl
index 70e696c83eb669..7d575abb555ed6 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); 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 b9a4f05de6000d..831104f745e5b3 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(I, 3)
+3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:
+  [1, 1]  =  1
+  [2, 2]  =  1
+  [3, 3]  =  1
 
 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(I, 3)
+3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:
+  [1, 1]  =  1
+  [2, 2]  =  1
+  [3, 3]  =  1
 
 julia> nonzeros(A)
-3-element Array{Float64,1}:
- 1.0
- 1.0
- 1.0
+3-element Array{Int64,1}:
+ 1
+ 1
+ 1
 ```
 """
 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(I, 3)
+3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:
+  [1, 1]  =  1
+  [2, 2]  =  1
+  [3, 3]  =  1
 
 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))
@@ -1487,54 +1485,12 @@ 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} = speye_scaled(T, oneunit(T), m, n)
+eye(S::SparseMatrixCSC{T}) where {T} = sparse(UniformScaling{T}(one(T)), 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)
+    speye_scaled(one(T), m, m)
 end
 
 speye_scaled(diag, m::Integer, n::Integer) = speye_scaled(typeof(diag), diag, m, n)
@@ -3120,13 +3076,13 @@ 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(I, 3), sparse(2I, 2))
+5×5 SparseMatrixCSC{Int64,Int64} with 5 stored entries:
+  [1, 1]  =  1
+  [2, 2]  =  1
+  [3, 3]  =  1
+  [4, 4]  =  2
+  [5, 5]  =  2
 ```
 """
 function blkdiag(X::SparseMatrixCSC...)
@@ -3578,6 +3534,6 @@ 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..d1ebf3d7c1d12f 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)`](@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..4c38a4dade0637 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), 1) == [1 1 1]
 end
 
 @testset "single multidimensional index" begin
diff --git a/test/hashing.jl b/test/hashing.jl
index e2f277ab5b61ce..dfae4514496136 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),
     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 d8c4e032f42806..82d30898b799c8 100644
--- a/test/linalg/arnoldi.jl
+++ b/test/linalg/arnoldi.jl
@@ -163,7 +163,7 @@ 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), 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..cfe1bf9eeadc65 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)
     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 d3ce6677b4be9f..2c4e2cb3b98e9e 100644
--- a/test/linalg/uniformscaling.jl
+++ b/test/linalg/uniformscaling.jl
@@ -81,7 +81,7 @@ 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))
             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..47615a2d963945 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), kron(sparse(1.0I, n2), ddx(n1)))
+    D2 = kron(sparse(1.0I, n3), kron(ddx(n2), sparse(1.0I, n1)))
+    D3 = kron(ddx(n3), kron(sparse(1.0I, n2), sparse(1.0I, 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..1634da4698b65c 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), fdl1) + kron(fdl1, sparse(1.0I, N))
 end
 
 # get the list of boundary dof-indices
diff --git a/test/show.jl b/test/show.jl
index a3075d722ba16f..dd200810761712 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)
     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 48744801989bea..b1bf3b7a3d59aa 100644
--- a/test/sparse/cholmod.jl
+++ b/test/sparse/cholmod.jl
@@ -178,7 +178,7 @@ let # Issue 9160
 end
 
 # Issue #9915
-@test speye(2)\speye(2) == eye(2)
+@test sparse(1.0I, 2)\sparse(1.0I, 2) == eye(2) # having `foo == I` would be nice
 
 # test eltype
 @test eltype(Dense(ones(3))) == Float64
@@ -634,12 +634,12 @@ Fnew = deserialize(b)
 @test SparseArrays.CHOLMOD.Dense(ones(Complex{Float32}, 5, 2)) == ones(5, 2)
 
 # Further issue with promotion #14894
-@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))\ones(5) == ones(5)
+@test cholfact(Symmetric(sparse(Float16(1)I, 5)))\ones(5) == ones(5)
+@test cholfact(Hermitian(sparse(Complex{Float16}(1)I, 5)))\ones(5) == ones(Complex{Float64}, 5)
+@test_throws MethodError cholfact(sparse(BigFloat(1)I, 5))
+@test_throws MethodError cholfact(Symmetric(sparse(BigFloat(1)I, 5)))
+@test_throws MethodError cholfact(Hermitian(sparse(Complex{BigFloat}(1)I, 5)))
 
 # test \ for Factor and StridedVecOrMat
 let x = rand(5),
@@ -657,7 +657,7 @@ end
 # Make sure that ldltfact performs an LDLt (Issue #19032)
 let m = 400, n = 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))
@@ -702,11 +702,12 @@ 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)
+    @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
 
@@ -751,7 +752,7 @@ end
 
 @testset "Issue #22335" begin
     local A, F
-    A = speye(3)
+    A = sparse(1.0I, 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..cc718fb254a62e 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), 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 23689de033215d..32650c27c971e3 100644
--- a/test/sparse/sparse.jl
+++ b/test/sparse/sparse.jl
@@ -22,7 +22,7 @@ end
     @test sparse(Any[1,2,3], Any[1,2,3], Any[1,1,1], 5, 4) == sparse([1,2,3], [1,2,3], [1,1,1], 5, 4)
 end
 
-se33 = speye(3)
+se33 = sparse(1.0I, 3)
 do33 = ones(3)
 
 @testset "sparse binary operations" begin
@@ -45,7 +45,7 @@ do33 = ones(3)
 end
 
 @testset "concatenation tests" begin
-    sp33 = speye(3, 3)
+    sp33 = sparse(1.0I, 3)
 
     @testset "horizontal concatenation" begin
         @test all([se33 se33] == sparse([1, 2, 3, 1, 2, 3], [1, 2, 3, 4, 5, 6], ones(6)))
@@ -59,11 +59,11 @@ end
         @test length(([sp33; 0I]).nzval) == 3
     end
 
-    se44 = speye(4)
+    se44 = sparse(1.0I, 4)
     sz42 = spzeros(4, 2)
     sz41 = spzeros(4, 1)
     sz34 = spzeros(3, 4)
-    se77 = speye(7)
+    se77 = sparse(1.0I, 7)
     @testset "h+v concatenation" begin
         @test all([se44 sz42 sz41; sz34 se33] == se77)
         @test length(([sp33 0I; 1I 0I]).nzval) == 6
@@ -75,7 +75,7 @@ end
 
     @testset "concatenation promotion" begin
         sz41_f32 = spzeros(Float32, 4, 1)
-        se33_i32 = speye(Int32, 3, 3)
+        se33_i32 = sparse(UniformScaling{Int32}(1), 3) # hm
         @test all([se44 sz42 sz41_f32; sz34 se33_i32] == se77)
     end
 
@@ -151,7 +151,7 @@ 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)
@@ -174,7 +174,7 @@ 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())
@@ -183,7 +183,7 @@ 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())
@@ -192,7 +192,7 @@ 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())
@@ -201,7 +201,7 @@ 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())
@@ -210,7 +210,7 @@ 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())
@@ -219,7 +219,7 @@ 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())
@@ -229,10 +229,10 @@ 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())
 
@@ -493,7 +493,7 @@ end
 end
 
 @testset "issue described in https://groups.google.com/d/msg/julia-users/Yq4dh8NOWBQ/GU57L90FZ3EJ" begin
-    A = speye(Bool, 5)
+    A = sparse(UniformScaling{Bool}(true), 5) # hm
     @test find(A) == find(x -> x == true, A) == find(Array(A))
 end
 
@@ -808,7 +808,7 @@ end
     @test count(!iszero, A) == nA
     @test A == B
 
-    A = speye(Int, 5)
+    A = sparse(Int(1)I, 5)
     I=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]
@@ -823,7 +823,7 @@ end
     @test nnz(A) == 13
     @test count(!iszero, A) == 11
     @test A[I] == A[X] == c
-    A = speye(Int, 5)
+    A = sparse(Int(1)I, 5)
     A[I] = c
     @test nnz(A) == 12
     @test count(!iszero, A) == 11
@@ -1099,7 +1099,7 @@ for (tup, rval, rind) in [((1,), ["b"], [2])]
 end
 
 @testset "findn" begin
-    b = findn( speye(4) )
+    b = findn( sparse(1.0I, 4) )
     @test (length(b[1]) == 4)
     @test (length(b[2]) == 4)
 end
@@ -1118,7 +1118,7 @@ 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)
@@ -1261,7 +1261,7 @@ 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)
     @test_throws BoundsError x[-10:10]
 end
 
@@ -1273,7 +1273,7 @@ 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
@@ -1320,16 +1320,16 @@ 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)
 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)  == eye(A)
+    @test one(A)        == eye(A)
     @test_throws DimensionMismatch one(sprand(5, 6, 0.2))
-    @test eltype(speye(Real, 5, 5)) === Real
+    # presently: @test_throws MethodError SparseMatrixCSC{Real}(I, 5, 5)
+    # but want: @test eltype(SparseMatrixCSC{Real}(I, 5, 5)) === Real
 end
 
 @testset "istriu/istril" begin
@@ -1395,7 +1395,7 @@ end
 
 @testset "trace" begin
     @test_throws DimensionMismatch trace(sparse(ones(5,6)))
-    @test trace(speye(5)) == 5
+    @test trace(sparse(1.0I, 5)) == 5
 end
 
 @testset "spdiagm" begin
@@ -1435,7 +1435,7 @@ end
 end
 
 @testset "expandptr" begin
-    local A = speye(5)
+    local A = sparse(1.0I, 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]
@@ -1476,7 +1476,7 @@ end
 @testset "ishermitian/issymmetric" begin
     local A
     # real matrices
-    A = speye(5,5)
+    A = sparse(1.0I, 5)
     @test ishermitian(A) == true
     @test issymmetric(A) == true
     A[1,3] = 1.0
@@ -1487,14 +1487,14 @@ end
     @test issymmetric(A) == true
 
     # complex matrices
-    A = speye(5,5) + im*speye(5,5)
+    A = sparse((1.0 + 1.0im)I, 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)
     A[3,2] = 1.0 + im
     @test ishermitian(A) == false
     @test issymmetric(A) == false
@@ -1507,7 +1507,7 @@ end
     @test issymmetric(A) == true
 
     # explicit zeros
-    A = speye(Complex128, 5,5)
+    A = sparse(Complex128(1)I, 5)
     A[3,1] = 2
     A.nzval[2] = 0.0
     @test ishermitian(A) == true
@@ -1533,8 +1533,8 @@ end
 end
 
 @testset "equality ==" begin
-    A1 = speye(10)
-    A2 = speye(10)
+    A1 = sparse(1.0I, 10)
+    A2 = sparse(1.0I, 10)
     nonzeros(A1)[end]=0
     @test A1!=A2
     nonzeros(A1)[end]=1
@@ -1612,7 +1612,7 @@ 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)
     resize!(foo.nzval, 5)
     setindex!(foo.nzval, NaN, 5)
     @test vecnorm(foo) == 2.0
@@ -1688,7 +1688,7 @@ end
 end
 
 @testset "spones" begin
-    local A = 2. * speye(5, 5)
+    local A = sparse(2.0I, 5)
     @test Array(spones(A)) == eye(Array(A))
 end
 
@@ -1865,7 +1865,7 @@ end
 end
 
 @testset "issue #14398" begin
-    @test transpose(view(speye(10), 1:5, 1:5)) ≈ eye(5,5)
+    @test transpose(view(sparse(I, 10), 1:5, 1:5)) ≈ eye(5) # having `foo ≈ I` would be nice
 end
 
 @testset "dropstored issue #20513" begin
@@ -2034,7 +2034,7 @@ end
 end
 
 @testset "similar with type conversion" begin
-    local A = speye(5)
+    local A = sparse(1.0I, 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)
@@ -2044,7 +2044,7 @@ end
 end
 
 @testset "similar for SparseMatrixCSC" begin
-    local A = speye(5)
+    local A = sparse(1.0I, 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 f7f8bdb77bae7a..abc0fde0ccc67f 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 = eye(Int, m)*10m + rand(1:m, m, m)
         densefloatmat = eye(m) + randn(m, m)/(2m)
diff --git a/test/sparse/umfpack.jl b/test/sparse/umfpack.jl
index a99dac1c92413c..dd6906482e9664 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)
     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)
         @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)), 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)), aa, Base.SparseArrays.UMFPACK.UMFPACK_A)
     end
 
     @testset "Issues #18246,18244 - lufact sparse pivot" begin
-        A = speye(4)
+        A = sparse(1.0I, 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))