diff --git a/base/abstractarray.jl b/base/abstractarray.jl
index be993d85e66fd..aed86b92d0cf1 100644
--- a/base/abstractarray.jl
+++ b/base/abstractarray.jl
@@ -1727,7 +1727,7 @@ for all `i` and `j`.
 
 # Examples
 ```jldoctest
-julia> a = reshape(collect(1:16),(2,2,2,2))
+julia> a = reshape(Vector(1:16),(2,2,2,2))
 2×2×2×2 Array{Int64,4}:
 [:, :, 1, 1] =
  1  3
diff --git a/base/abstractarraymath.jl b/base/abstractarraymath.jl
index ee208780fffa2..d5343c922d4e3 100644
--- a/base/abstractarraymath.jl
+++ b/base/abstractarraymath.jl
@@ -51,7 +51,7 @@ Elements of `dims` must be unique and within the range `1:ndims(A)`.
 
 # Examples
 ```jldoctest
-julia> a = reshape(collect(1:4),(2,2,1,1))
+julia> a = reshape(Vector(1:4),(2,2,1,1))
 2×2×1×1 Array{Int64,4}:
 [:, :, 1, 1] =
  1  3
@@ -186,7 +186,7 @@ first dimension.
 
 # Examples
 ```jldoctest
-julia> b = reshape(collect(1:16), (4,4))
+julia> b = reshape(Vector(1:16), (4,4))
 4×4 Array{Int64,2}:
  1  5   9  13
  2  6  10  14
diff --git a/base/array.jl b/base/array.jl
index 980880fb1aea6..ad7fd65b547e0 100644
--- a/base/array.jl
+++ b/base/array.jl
@@ -1334,7 +1334,7 @@ for reverse-order iteration without making a copy.
 
 # Examples
 ```jldoctest
-julia> A = collect(1:5)
+julia> A = Vector(1:5)
 5-element Array{Int64,1}:
  1
  2
@@ -1392,7 +1392,7 @@ In-place version of [`reverse`](@ref).
 
 # Examples
 ```jldoctest
-julia> A = collect(1:5)
+julia> A = Vector(1:5)
 5-element Array{Int64,1}:
  1
  2
@@ -2117,7 +2117,7 @@ The function `f` is passed one argument.
 
 # Examples
 ```jldoctest
-julia> filter!(isodd, collect(1:10))
+julia> filter!(isodd, Vector(1:10))
 5-element Array{Int64,1}:
  1
  3
diff --git a/base/linalg/qr.jl b/base/linalg/qr.jl
index 21e5263dc3c87..c38695e8b3dcf 100644
--- a/base/linalg/qr.jl
+++ b/base/linalg/qr.jl
@@ -161,7 +161,7 @@ end
 
 function qrfactPivotedUnblocked!(A::StridedMatrix)
     m, n = size(A)
-    piv = collect(UnitRange{BlasInt}(1,n))
+    piv = Vector(UnitRange{BlasInt}(1,n))
     τ = Vector{eltype(A)}(uninitialized, min(m,n))
     for j = 1:min(m,n)
 
diff --git a/base/multidimensional.jl b/base/multidimensional.jl
index aa6a3cf5bf74d..03b64a9ea797e 100644
--- a/base/multidimensional.jl
+++ b/base/multidimensional.jl
@@ -31,7 +31,7 @@ module IteratorsMD
 
     # Examples
     ```jldoctest
-    julia> A = reshape(collect(1:16), (2, 2, 2, 2))
+    julia> A = reshape(Vector(1:16), (2, 2, 2, 2))
     2×2×2×2 Array{Int64,4}:
     [:, :, 1, 1] =
      1  3
@@ -1306,7 +1306,7 @@ arrays have overlapping indices, then on the domain of the overlap
 
 # Examples
 ```julia-repl
-julia> src = reshape(collect(1:16), (4,4))
+julia> src = reshape(Vector(1:16), (4,4))
 4×4 Array{Int64,2}:
  1  5   9  13
  2  6  10  14
@@ -1706,7 +1706,7 @@ Return unique regions of `A` along dimension `dim`.
 
 # Examples
 ```jldoctest
-julia> A = map(isodd, reshape(collect(1:8), (2,2,2)))
+julia> A = map(isodd, reshape(Vector(1:8), (2,2,2)))
 2×2×2 Array{Bool,3}:
 [:, :, 1] =
   true   true
@@ -1816,7 +1816,7 @@ Compute the minimum and maximum elements of an array over the given dimensions.
 
 # Examples
 ```jldoctest
-julia> A = reshape(collect(1:2:16), (2,2,2))
+julia> A = reshape(Vector(1:2:16), (2,2,2))
 2×2×2 Array{Int64,3}:
 [:, :, 1] =
  1  5
diff --git a/base/permuteddimsarray.jl b/base/permuteddimsarray.jl
index bf7c73f25071d..372d43d11bbdf 100644
--- a/base/permuteddimsarray.jl
+++ b/base/permuteddimsarray.jl
@@ -87,7 +87,7 @@ See also: [`PermutedDimsArray`](@ref).
 
 # Examples
 ```jldoctest
-julia> A = reshape(collect(1:8), (2,2,2))
+julia> A = reshape(Vector(1:8), (2,2,2))
 2×2×2 Array{Int64,3}:
 [:, :, 1] =
  1  3
diff --git a/base/random/misc.jl b/base/random/misc.jl
index 68abece65b197..7dac792e88bd0 100644
--- a/base/random/misc.jl
+++ b/base/random/misc.jl
@@ -158,7 +158,7 @@ optionally supplying the random-number generator `rng`.
 ```jldoctest
 julia> rng = MersenneTwister(1234);
 
-julia> shuffle!(rng, collect(1:16))
+julia> shuffle!(rng, Vector(1:16))
 16-element Array{Int64,1}:
   2
  15
@@ -204,7 +204,7 @@ indices, see [`randperm`](@ref).
 ```jldoctest
 julia> rng = MersenneTwister(1234);
 
-julia> shuffle(rng, collect(1:10))
+julia> shuffle(rng, Vector(1:10))
 10-element Array{Int64,1}:
   6
   1
diff --git a/base/reducedim.jl b/base/reducedim.jl
index 27ff8ecbe0ee5..e0a491e7c83ed 100644
--- a/base/reducedim.jl
+++ b/base/reducedim.jl
@@ -255,7 +255,7 @@ faster because the intermediate array is avoided.
 
 # Examples
 ```jldoctest
-julia> a = reshape(collect(1:16), (4,4))
+julia> a = reshape(Vector(1:16), (4,4))
 4×4 Array{Int64,2}:
  1  5   9  13
  2  6  10  14
@@ -289,7 +289,7 @@ associativity, e.g. left-to-right, you should write your own loop. See documenta
 
 # Examples
 ```jldoctest
-julia> a = reshape(collect(1:16), (4,4))
+julia> a = reshape(Vector(1:16), (4,4))
 4×4 Array{Int64,2}:
  1  5   9  13
  2  6  10  14
diff --git a/base/reshapedarray.jl b/base/reshapedarray.jl
index 005be471253b4..5c06c19ecda8b 100644
--- a/base/reshapedarray.jl
+++ b/base/reshapedarray.jl
@@ -52,7 +52,7 @@ the specified dimensions is equal to the length of the original array
 `A`. The total number of elements must not change.
 
 ```jldoctest
-julia> A = collect(1:16)
+julia> A = Vector(1:16)
 16-element Array{Int64,1}:
   1
   2
diff --git a/base/sparse/sparsematrix.jl b/base/sparse/sparsematrix.jl
index 7c5c27d49f443..eaec3b2b03e9c 100644
--- a/base/sparse/sparsematrix.jl
+++ b/base/sparse/sparsematrix.jl
@@ -729,7 +729,7 @@ end
 
 function sparse(D::Diagonal{T}) where T
     m = length(D.diag)
-    return SparseMatrixCSC(m, m, collect(1:(m+1)), collect(1:m), Vector{T}(D.diag))
+    return SparseMatrixCSC(m, m, Vector(1:(m+1)), Vector(1:m), Vector{T}(D.diag))
 end
 
 ## Transposition and permutation methods
diff --git a/base/sparse/sparsevector.jl b/base/sparse/sparsevector.jl
index 649b8252062ca..68c58ca03797f 100644
--- a/base/sparse/sparsevector.jl
+++ b/base/sparse/sparsevector.jl
@@ -188,7 +188,7 @@ function sparsevec(I::AbstractVector{<:Integer}, V::AbstractVector, combine::Fun
             len = i
         end
     end
-    _sparsevector!(collect(I), collect(V), len, combine)
+    _sparsevector!(Vector(I), Vector(V), len, combine)
 end
 
 function sparsevec(I::AbstractVector{<:Integer}, V::AbstractVector, len::Integer, combine::Function)
@@ -197,7 +197,7 @@ function sparsevec(I::AbstractVector{<:Integer}, V::AbstractVector, len::Integer
     for i in I
         1 <= i <= len || throw(ArgumentError("An index is out of bound."))
     end
-    _sparsevector!(collect(I), collect(V), len, combine)
+    _sparsevector!(Vector(I), Vector(V), len, combine)
 end
 
 sparsevec(I::AbstractVector, V::Union{Number, AbstractVector}, args...) =
@@ -849,8 +849,8 @@ function SparseMatrixCSC{Tv,Ti}(x::AbstractSparseVector) where {Tv,Ti}
     colptr = Ti[1, m+1]
     # Note that this *cannot* share data like normal array conversions, since
     # modifying one would put the other in an inconsistent state
-    rowval = collect(Ti, xnzind)
-    nzval = collect(Tv, xnzval)
+    rowval = Vector{Ti}(xnzind)
+    nzval = Vector{Tv}(xnzval)
     SparseMatrixCSC(n, 1, colptr, rowval, nzval)
 end
 
@@ -1934,7 +1934,7 @@ function sort(x::SparseVector{Tv,Ti}; kws...) where {Tv,Ti}
     sinds = sortperm(allvals;kws...)
     n,k = length(x),length(allvals)
     z = findfirst(equalto(k),sinds)
-    newnzind = collect(Ti,1:k-1)
+    newnzind = Vector{Ti}(1:k-1)
     newnzind[z:end] .+= n-k+1
     newnzvals = allvals[deleteat!(sinds[1:k],z)]
     SparseVector(n,newnzind,newnzvals)
diff --git a/stdlib/Dates/src/arithmetic.jl b/stdlib/Dates/src/arithmetic.jl
index c1c1a623533b7..f1ca82e71c087 100644
--- a/stdlib/Dates/src/arithmetic.jl
+++ b/stdlib/Dates/src/arithmetic.jl
@@ -95,5 +95,5 @@ end
 (-)(y::T, x::AbstractArray{T}) where {T<:TimeType} = y .- x
 
 # AbstractArray{TimeType}, AbstractArray{TimeType}
-(-)(x::OrdinalRange{T}, y::OrdinalRange{T}) where {T<:TimeType} = collect(x) - collect(y)
-(-)(x::AbstractRange{T}, y::AbstractRange{T}) where {T<:TimeType} = collect(x) - collect(y)
+(-)(x::OrdinalRange{T}, y::OrdinalRange{T}) where {T<:TimeType} = Vector(x) - Vector(y)
+(-)(x::AbstractRange{T}, y::AbstractRange{T}) where {T<:TimeType} = Vector(x) - Vector(y)
diff --git a/stdlib/Distributed/test/topology.jl b/stdlib/Distributed/test/topology.jl
index 32b868e5e1d81..2de3791bfcf4a 100644
--- a/stdlib/Distributed/test/topology.jl
+++ b/stdlib/Distributed/test/topology.jl
@@ -51,7 +51,7 @@ function launch(manager::TopoTestManager, params::Dict, launched::Array, c::Cond
         wconfig.process = io
         wconfig.io = io.out
         wconfig.ident = i
-        wconfig.connect_idents = collect(i+2:2:manager.np)
+        wconfig.connect_idents = Vector(i+2:2:manager.np)
         push!(launched, wconfig)
     end
 
diff --git a/test/abstractarray.jl b/test/abstractarray.jl
index 910372bf4a077..fba67fb5d168b 100644
--- a/test/abstractarray.jl
+++ b/test/abstractarray.jl
@@ -157,7 +157,7 @@ end
             @test CartesianIndices(0:3,3:5,-101:-100)[l] == CartesianIndex(i-1, j+2, k-102)
         end
 
-        local A = reshape(collect(1:9), (3,3))
+        local A = reshape(Vector(1:9), (3,3))
         @test CartesianIndices(size(A))[6] == CartesianIndex(3,2)
         @test LinearIndices(size(A))[3, 2] == 6
         @test CartesianIndices(A)[6] == CartesianIndex(3,2)
@@ -256,7 +256,7 @@ Base.setindex!(A::TSlow{T,5}, v, i1::Int, i2::Int, i3::Int, i4::Int, i5::Int) wh
 const can_inline = Base.JLOptions().can_inline != 0
 function test_scalar_indexing(::Type{T}, shape, ::Type{TestAbstractArray}) where T
     N = prod(shape)
-    A = reshape(collect(1:N), shape)
+    A = reshape(Vector(1:N), shape)
     B = T(A)
     @test A == B
     # Test indexing up to 5 dimensions
@@ -379,7 +379,7 @@ end
 function test_vector_indexing(::Type{T}, shape, ::Type{TestAbstractArray}) where T
     @testset "test_vector_indexing{$(T)}" begin
         N = prod(shape)
-        A = reshape(collect(1:N), shape)
+        A = reshape(Vector(1:N), shape)
         B = T(A)
         trailing5 = CartesianIndex(ntuple(x->1, max(ndims(B)-5, 0)))
         trailing4 = CartesianIndex(ntuple(x->1, max(ndims(B)-4, 0)))
@@ -425,7 +425,7 @@ end
 
 function test_primitives(::Type{T}, shape, ::Type{TestAbstractArray}) where T
     N = prod(shape)
-    A = reshape(collect(1:N), shape)
+    A = reshape(Vector(1:N), shape)
     B = T(A)
 
     # last(a)
@@ -489,7 +489,7 @@ mutable struct UnimplementedArray{T, N} <: AbstractArray{T, N} end
 
 function test_getindex_internals(::Type{T}, shape, ::Type{TestAbstractArray}) where T
     N = prod(shape)
-    A = reshape(collect(1:N), shape)
+    A = reshape(Vector(1:N), shape)
     B = T(A)
 
     @test getindex(A, 1) == 1
@@ -509,7 +509,7 @@ end
 
 function test_setindex!_internals(::Type{T}, shape, ::Type{TestAbstractArray}) where T
     N = prod(shape)
-    A = reshape(collect(1:N), shape)
+    A = reshape(Vector(1:N), shape)
     B = T(A)
 
     Base.unsafe_setindex!(B, 2, 1)
@@ -610,7 +610,7 @@ function test_ind2sub(::Type{TestAbstractArray})
     n = rand(2:5)
     dims = tuple(rand(1:5, n)...)
     len = prod(dims)
-    A = reshape(collect(1:len), dims...)
+    A = reshape(Vector(1:len), dims...)
     I = CartesianIndices(dims)
     for i in 1:len
         @test A[I[i]] == A[i]
@@ -791,7 +791,7 @@ for A in (rand(2), rand(2,3))
     for (i, v) in pairs(A)
         @test A[i] == v
     end
-    @test collect(values(A)) == collect(A)
+    @test Array(values(A)) == A
 end
 
 # nextind
@@ -807,7 +807,7 @@ end
 
 @testset "zero-dimensional copy" begin
     Z = Array{Int,0}(uninitialized); Z[] = 17
-    @test Z == collect(Z) == copy(Z)
+    @test Z == Array(Z) == copy(Z)
 end
 
 @testset "empty" begin
diff --git a/test/arrayops.jl b/test/arrayops.jl
index 402ae878e062a..c6207b4d283d3 100644
--- a/test/arrayops.jl
+++ b/test/arrayops.jl
@@ -94,7 +94,7 @@ using Main.TestHelpers.OAs
     @test Vector(a) !== a
 end
 @testset "reshaping SubArrays" begin
-    a = collect(reshape(1:5, 1, 5))
+    a = Array(reshape(1:5, 1, 5))
     @testset "linearfast" begin
         s = view(a, :, 2:4)
         r = reshape(s, (length(s),))
@@ -195,7 +195,7 @@ end
 end
 
 @testset "operations with IndexLinear ReshapedArray" begin
-    b = collect(1:12)
+    b = Vector(1:12)
     a = Base.ReshapedArray(b, (4,3), ())
     @test a[3,2] == 7
     @test a[6] == 6
@@ -276,8 +276,8 @@ end
     @test find(occursin(Int[]), a) == Int[]
     @test find(occursin(a), Int[]) == Int[]
 
-    a = collect(1:3:15)
-    b = collect(2:4:10)
+    a = Vector(1:3:15)
+    b = Vector(2:4:10)
     @test find(occursin(b), a) == [4]
     @test find(occursin(b), [a[1:4]; a[4:end]]) == [4,5]
 
@@ -468,7 +468,7 @@ end
     @test find(c -> c == 'l', s) == [3]
     g = Base.Unicode.graphemes("日本語")
     @test find(isascii, g) == Int[]
-    @test find(!iszero, (i % 2 for i in 1:10)) == collect(1:2:9)
+    @test find(!iszero, (i % 2 for i in 1:10)) == 1:2:9
 end
 @testset "findn" begin
     b = findn(fill(1,2,2,2,2))
@@ -570,7 +570,7 @@ end
     @test pointer(cp) == pointer(c)
     @test_throws ArgumentError pointer(cp, 2)
     @test strides(cp) == (9,3,1)
-    ap = PermutedDimsArray(collect(a), (2,1,3))
+    ap = PermutedDimsArray(Array(a), (2,1,3))
     @test strides(ap) == (3,1,12)
 
     for A in [rand(1,2,3,4),rand(2,2,2,2),rand(5,6,5,6),rand(1,1,1,1)]
@@ -1137,7 +1137,7 @@ end
 
 @testset "filter!" begin
     # base case w/ Vector
-    a = collect(1:10)
+    a = Vector(1:10)
     filter!(x -> x > 5, a)
     @test a == 6:10
 
@@ -1153,9 +1153,9 @@ end
     @test isempty(ea)
 
     # non-1-indexed array
-    oa = OffsetArray(collect(1:10), -5)
+    oa = OffsetArray(Vector(1:10), -5)
     filter!(x -> x > 5, oa)
-    @test oa == OffsetArray(collect(6:10), -5)
+    @test oa == OffsetArray(Vector(6:10), -5)
 
     # empty non-1-indexed array
     eoa = OffsetArray([], -5)
@@ -1227,7 +1227,7 @@ end
     A14 = [11 13; 12 14]
     R = CartesianIndices(axes(A14))
     @test [a for (a,b) in pairs(IndexLinear(),    A14)] == [1,2,3,4]
-    @test [a for (a,b) in pairs(IndexCartesian(), A14)] == vec(collect(R))
+    @test [a for (a,b) in pairs(IndexCartesian(), A14)] == vec(Array(R))
     @test [b for (a,b) in pairs(IndexLinear(),    A14)] == [11,12,13,14]
     @test [b for (a,b) in pairs(IndexCartesian(), A14)] == [11,12,13,14]
 end
@@ -1591,7 +1591,7 @@ end
     @test eltype(R) <: CartesianIndex{2}
     @test eltype(typeof(R)) <: CartesianIndex{2}
     @test eltype(CartesianIndices{2}) <: CartesianIndex{2}
-    indices = collect(R)
+    indices = Array(R)
     @test indices[1] == CartesianIndex{2}(2,3)
     @test indices[2] == CartesianIndex{2}(3,3)
     @test indices[4] == CartesianIndex{2}(5,3)
@@ -1631,7 +1631,7 @@ end
     val, state = next(itr, state)
     @test done(itr, state)
     @test r[val] == 3
-    r = sparse(collect(2:3:8))
+    r = sparse(2:3:8)
     itr = eachindex(r)
     state = start(itr)
     @test !done(itr, state)
@@ -1770,7 +1770,7 @@ end
 @test (1:5) + (1.5:5.5) == 2.5:2.0:10.5
 
 @testset "slicedim" begin
-    for A in (reshape(collect(1:20), 4, 5),
+    for A in (reshape(Vector(1:20), 4, 5),
               reshape(1:20, 4, 5))
         local A
         @test slicedim(A, 1, 2) == 2:4:20
@@ -1778,7 +1778,7 @@ end
         @test_throws ArgumentError slicedim(A,0,1)
         @test slicedim(A, 3, 1) == A
         @test_throws BoundsError slicedim(A, 3, 2)
-        @test @inferred(slicedim(A, 1, 2:2)) == collect(2:4:20)'
+        @test @inferred(slicedim(A, 1, 2:2)) == Vector(2:4:20)'
     end
 end
 
diff --git a/test/functional.jl b/test/functional.jl
index d7b9026ea61cb..400ff89def3f6 100644
--- a/test/functional.jl
+++ b/test/functional.jl
@@ -111,7 +111,7 @@ let gen = (x for x in 1:10)
 end
 
 let gen = (x * y for x in 1:10, y in 1:10)
-    @test collect(gen) == collect(1:10) .* collect(1:10)'
+    @test collect(gen) == Vector(1:10) .* Vector(1:10)'
     @test first(gen) == 1
     @test collect(gen)[1:10] == 1:10
 end
diff --git a/test/hashing.jl b/test/hashing.jl
index b414c05c52ceb..782d9eb618d05 100644
--- a/test/hashing.jl
+++ b/test/hashing.jl
@@ -96,7 +96,7 @@ vals = Any[
 for a in vals, b in vals
     @test isequal(a,b) == (hash(a)==hash(b))
     if a isa AbstractArray
-        @test hash(a) == hash(collect(a)) == hash(collect(Any, a))
+        @test hash(a) == hash(Array(a)) == hash(Array{Any}(a))
     end
 end
 
@@ -166,7 +166,7 @@ vals = Any[
 ]
 
 for a in vals
-    @test hash(collect(a)) == hash(a)
+    @test hash(Array(a)) == hash(a)
 end
 
 @test hash(SubString("--hello--",3,7)) == hash("hello")
diff --git a/test/linalg/diagonal.jl b/test/linalg/diagonal.jl
index 2c8fb4cab6539..4eca24ff7afee 100644
--- a/test/linalg/diagonal.jl
+++ b/test/linalg/diagonal.jl
@@ -117,7 +117,7 @@ srand(1)
                 b = sparse(b)
                 @test ldiv!(D, copy(b)) ≈ Array(D)\Array(b)
                 @test_throws SingularException ldiv!(Diagonal(zeros(elty, n)), copy(b))
-                b = view(rand(elty, n), collect(1:n))
+                b = view(rand(elty, n), Vector(1:n))
                 b2 = copy(b)
                 c = ldiv!(D, b)
                 d = Array(D)\b2
@@ -126,7 +126,7 @@ srand(1)
                 b = rand(elty, n+1, n+1)
                 b = sparse(b)
                 @test_throws DimensionMismatch ldiv!(D, copy(b))
-                b = view(rand(elty, n+1), collect(1:n+1))
+                b = view(rand(elty, n+1), Vector(1:n+1))
                 @test_throws DimensionMismatch ldiv!(D, b)
             end
         end
diff --git a/test/linalg/generic.jl b/test/linalg/generic.jl
index 6e3ed0f8a6a57..a6c20f4e858da 100644
--- a/test/linalg/generic.jl
+++ b/test/linalg/generic.jl
@@ -163,10 +163,10 @@ end
     α, β = 'f', 'g'
     @test_throws DimensionMismatch Base.LinAlg.axpy!(α,x,['g'])
     @test_throws DimensionMismatch Base.LinAlg.axpby!(α,x,β,['g'])
-    @test_throws BoundsError Base.LinAlg.axpy!(α,x,collect(-1:5),y,collect(1:7))
-    @test_throws BoundsError Base.LinAlg.axpy!(α,x,collect(1:7),y,collect(-1:5))
-    @test_throws BoundsError Base.LinAlg.axpy!(α,x,collect(1:7),y,collect(1:7))
-    @test_throws DimensionMismatch Base.LinAlg.axpy!(α,x,collect(1:3),y,collect(1:5))
+    @test_throws BoundsError Base.LinAlg.axpy!(α,x,Vector(-1:5),y,Vector(1:7))
+    @test_throws BoundsError Base.LinAlg.axpy!(α,x,Vector(1:7),y,Vector(-1:5))
+    @test_throws BoundsError Base.LinAlg.axpy!(α,x,Vector(1:7),y,Vector(1:7))
+    @test_throws DimensionMismatch Base.LinAlg.axpy!(α,x,Vector(1:3),y,Vector(1:5))
 end
 
 @test !issymmetric(fill(1,5,3))
diff --git a/test/linalg/qr.jl b/test/linalg/qr.jl
index 5757c6f44b4eb..0054173a65fed 100644
--- a/test/linalg/qr.jl
+++ b/test/linalg/qr.jl
@@ -188,7 +188,7 @@ end
     @test Base.LinAlg.qr!(Int[1]) == (Int[1],1)
 
     B = rand(7,2)
-    @test (1:7)\B ≈ collect(1:7)\B
+    @test (1:7)\B ≈ Vector(1:7)\B
 end
 
 @testset "Issue 16520" begin
@@ -204,7 +204,7 @@ end
 
 @testset "Issue 24107" begin
     A = rand(200,2)
-    @test A \ linspace(0,1,200) == A \ collect(linspace(0,1,200))
+    @test A \ linspace(0,1,200) == A \ Vector(linspace(0,1,200))
 end
 
 @testset "Issue #24589. Promotion of rational matrices" begin
diff --git a/test/offsetarray.jl b/test/offsetarray.jl
index f27a59983eb3b..61b45c48adfea 100644
--- a/test/offsetarray.jl
+++ b/test/offsetarray.jl
@@ -32,12 +32,12 @@ S = OffsetArray(view(A0, 1:2, 1:2), (-1,2))   # IndexCartesian
 @test_throws BoundsError A[0,3,2]
 @test_throws BoundsError S[0,3,2]
 # partial indexing
-S3 = OffsetArray(view(reshape(collect(1:4*3*1), 4, 3, 1), 1:3, 1:2, :), (-1,-2,1))
+S3 = OffsetArray(view(reshape(Vector(1:4*3*1), 4, 3, 1), 1:3, 1:2, :), (-1,-2,1))
 @test S3[1,-1] == 2
 @test S3[1,0] == 6
 @test_throws BoundsError S3[1,1]
 @test_throws BoundsError S3[1,-2]
-S4 = OffsetArray(view(reshape(collect(1:4*3*2), 4, 3, 2), 1:3, 1:2, :), (-1,-2,1))
+S4 = OffsetArray(view(reshape(Vector(1:4*3*2), 4, 3, 2), 1:3, 1:2, :), (-1,-2,1))
 @test S4[1,-1,2] == 2
 @test S4[1,0,2] == 6
 @test_throws BoundsError S4[1,1,2]
@@ -123,16 +123,16 @@ S = view(A, :, :)
 @test_throws BoundsError S[1,1]
 @test axes(S) === (0:1, 3:4)
 # https://github.com/JuliaArrays/OffsetArrays.jl/issues/27
-g = OffsetArray(collect(-2:3), (-3,))
+g = OffsetArray(Vector(-2:3), (-3,))
 gv = view(g, -1:2)
 @test axes(gv, 1) === Base.OneTo(4)
-@test collect(gv) == collect(-1:2)
+@test collect(gv) == -1:2
 gv = view(g, OffsetArray(-1:2, (-2,)))
 @test axes(gv, 1) === -1:2
-@test collect(gv) == collect(-1:2)
+@test collect(gv) == -1:2
 gv = view(g, OffsetArray(-1:2, (-1,)))
 @test axes(gv, 1) === 0:3
-@test collect(gv) == collect(-1:2)
+@test collect(gv) == -1:2
 
 # iteration
 for (a,d) in zip(A, A0)
@@ -430,7 +430,7 @@ v = OffsetArray(rand(8), (-2,))
 
 @test circshift(A, (-1,2)) == OffsetArray(circshift(parent(A), (-1,2)), A.offsets)
 
-src = reshape(collect(1:16), (4,4))
+src = reshape(Vector(1:16), (4,4))
 dest = OffsetArray(Matrix{Int}(uninitialized, 4,4), (-1,1))
 circcopy!(dest, src)
 @test parent(dest) == [8 12 16 4; 5 9 13 1; 6 10 14 2; 7 11 15 3]
diff --git a/test/perf/sparse/getindex.jl b/test/perf/sparse/getindex.jl
index 03d6a6f36b267..64595ea50dbdf 100644
--- a/test/perf/sparse/getindex.jl
+++ b/test/perf/sparse/getindex.jl
@@ -57,7 +57,7 @@ function sparse_getindex_perf()
     intinds = nothing
     logicalinds = nothing # needs to be generated for a specific matrix size.
     rangeinds = 121:237
-    orderedinds = collect(rangeinds)
+    orderedinds = Vector(rangeinds)
     disorderedinds = orderedinds[randperm(length(orderedinds))]
 
     inds = [(intinds, "integers"), (logicalinds, "logical array"), (rangeinds, "a range"),
diff --git a/test/random.jl b/test/random.jl
index e36d04c519ac1..b687d66de15a2 100644
--- a/test/random.jl
+++ b/test/random.jl
@@ -483,9 +483,9 @@ let mta = MersenneTwister(42), mtb = MersenneTwister(42)
     @test randsubseq(mta,1:10,0.4) == randsubseq(mtb,1:10,0.4)
     @test randsubseq!(mta,Int[],1:10,0.4) == randsubseq!(mtb,Int[],1:10,0.4)
 
-    @test shuffle(mta,collect(1:10)) == shuffle(mtb,collect(1:10))
-    @test shuffle!(mta,collect(1:10)) == shuffle!(mtb,collect(1:10))
-    @test shuffle(mta,collect(2:11)) == shuffle(mtb,2:11)
+    @test shuffle(mta,Vector(1:10)) == shuffle(mtb,Vector(1:10))
+    @test shuffle!(mta,Vector(1:10)) == shuffle!(mtb,Vector(1:10))
+    @test shuffle(mta,Vector(2:11)) == shuffle(mtb,2:11)
     @test shuffle!(mta, rand(mta, 2, 3)) == shuffle!(mtb, rand(mtb, 2, 3))
     @test shuffle(mta, rand(mta, 2, 3)) == shuffle(mtb, rand(mtb, 2, 3))
 
diff --git a/test/ranges.jl b/test/ranges.jl
index c12bb55473aa1..4df601e4e981b 100644
--- a/test/ranges.jl
+++ b/test/ranges.jl
@@ -251,7 +251,7 @@ end
         @test length(1:2:0) == 0
     end
     @testset "find(::OccursIn, ::Array)" begin
-        @test find(occursin(3:20), [5.2, 3.3]) == find(occursin(collect(3:20)), [5.2, 3.3])
+        @test find(occursin(3:20), [5.2, 3.3]) == find(occursin(Vector(3:20)), [5.2, 3.3])
 
         let span = 5:20,
             r = -7:3:42
@@ -505,8 +505,8 @@ end
                                     (0, 1, 5, 0), (0, -10, 5, 0), (0, -10, 0, 1),
                                     (0, -1, 1, 0), (0, 1, -1, 0), (0, -1, -10, 11))
         r = start/10:step/10:stop/10
-        a = collect(start:step:stop)./10
-        ra = collect(r)
+        a = Vector(start:step:stop)./10
+        ra = Vector(r)
 
         @test r == a
         @test isequal(r, a)
@@ -519,7 +519,7 @@ end
 
         if len > 0
             l = linspace(start/10, stop/10, len)
-            la = collect(l)
+            la = Vector(l)
 
             @test a == l
             @test r == l
@@ -536,8 +536,8 @@ end
 
     @test 1.0:1/49:27.0 == linspace(1.0,27.0,1275) == [49:1323;]./49
     @test isequal(1.0:1/49:27.0, linspace(1.0,27.0,1275))
-    @test isequal(1.0:1/49:27.0, collect(49:1323)./49)
-    @test hash(1.0:1/49:27.0) == hash(linspace(1.0,27.0,1275)) == hash(collect(49:1323)./49)
+    @test isequal(1.0:1/49:27.0, Vector(49:1323)./49)
+    @test hash(1.0:1/49:27.0) == hash(linspace(1.0,27.0,1275)) == hash(Vector(49:1323)./49)
 
     @test [prevfloat(0.1):0.1:0.3;] == [prevfloat(0.1), 0.2, 0.3]
     @test [nextfloat(0.1):0.1:0.3;] == [nextfloat(0.1), 0.2]
@@ -691,12 +691,12 @@ end
                        linspace(0, 1, 20), map(Float32, linspace(0, 1, 20))]
     for r in Rs
         local r
-        ar = collect(r)
+        ar = Vector(r)
         @test r == ar
         @test isequal(r,ar)
         @test hash(r) == hash(ar)
         for s in Rs
-            as = collect(s)
+            as = Vector(s)
             @test isequal(r,s) == (hash(r)==hash(s))
             @test (r==s) == (ar==as)
         end
@@ -950,15 +950,15 @@ end
 
     function test_linspace_identity(r::AbstractRange{T}, mr) where T
         @test -r == mr
-        @test -collect(r) == collect(mr)
+        @test -Vector(r) == Vector(mr)
         @test isa(-r, typeof(r))
 
         @test broadcast(+, broadcast(+, 1, r), -1) == r
-        @test 1 .+ collect(r) == collect(1 .+ r) == collect(r .+ 1)
+        @test 1 .+ Vector(r) == Vector(1 .+ r) == Vector(r .+ 1)
         @test isa(broadcast(+, broadcast(+, 1, r), -1), typeof(r))
         @test broadcast(-, broadcast(-, 1, r), 1) == mr
-        @test 1 .- collect(r) == collect(1 .- r) == collect(1 .+ mr)
-        @test collect(r) .- 1 == collect(r .- 1) == -collect(mr .+ 1)
+        @test 1 .- Vector(r) == Vector(1 .- r) == Vector(1 .+ mr)
+        @test Vector(r) .- 1 == Vector(r .- 1) == -Vector(mr .+ 1)
         @test isa(broadcast(-, broadcast(-, 1, r), 1), typeof(r))
 
         @test 1 * r * 1 == r
@@ -969,9 +969,9 @@ end
         @test r / T(0.5) * T(0.5) == r
         @test isa(r / 1, typeof(r))
 
-        @test (2 * collect(r) == collect(r * 2) == collect(2 * r) ==
-               collect(r * T(2.0)) == collect(T(2.0) * r) ==
-               collect(r / T(0.5)) == -collect(mr * T(2.0)))
+        @test (2 * Vector(r) == Vector(r * 2) == Vector(2 * r) ==
+               Vector(r * T(2.0)) == Vector(T(2.0) * r) ==
+               Vector(r / T(0.5)) == -Vector(mr * T(2.0)))
     end
 
     test_linspace_identity(linspace(1.0, 27.0, 10), linspace(-1.0, -27.0, 10))
@@ -1024,10 +1024,10 @@ end
         @test r1 - r2 == r_diff
         @test r2 - r1 == -r_diff
 
-        @test collect(r1) + collect(r2) == collect(r_sum)
-        @test collect(r2) + collect(r1) == collect(r_sum)
-        @test collect(r1) - collect(r2) == collect(r_diff)
-        @test collect(r2) - collect(r1) == collect(-r_diff)
+        @test Vector(r1) + Vector(r2) == Vector(r_sum)
+        @test Vector(r2) + Vector(r1) == Vector(r_sum)
+        @test Vector(r1) - Vector(r2) == Vector(r_diff)
+        @test Vector(r2) - Vector(r1) == Vector(-r_diff)
     end
 
     test_range_sum_diff(1:5, 0:2:8, 1:3:13, 1:-1:-3)
@@ -1196,11 +1196,11 @@ Base.isless(x, y::NotReal) = isless(x, y.val)
 isdefined(Main, :TestHelpers) || @eval Main include("TestHelpers.jl")
 using Main.TestHelpers: Furlong
 @testset "dimensional correctness" begin
-    @test length(collect(Furlong(2):Furlong(10))) == 9
+    @test length(Vector(Furlong(2):Furlong(10))) == 9
     @test length(range(Furlong(2), 9)) == 9
-    @test collect(Furlong(2):Furlong(1):Furlong(10)) == collect(range(Furlong(2),Furlong(1),9)) == Furlong.(2:10)
-    @test collect(Furlong(1.0):Furlong(0.5):Furlong(10.0)) ==
-          collect(Furlong(1):Furlong(0.5):Furlong(10)) == Furlong.(1:0.5:10)
+    @test Vector(Furlong(2):Furlong(1):Furlong(10)) == Vector(range(Furlong(2),Furlong(1),9)) == Furlong.(2:10)
+    @test Vector(Furlong(1.0):Furlong(0.5):Furlong(10.0)) ==
+          Vector(Furlong(1):Furlong(0.5):Furlong(10)) == Furlong.(1:0.5:10)
 end
 
 @testset "issue #22270" begin
diff --git a/test/reduce.jl b/test/reduce.jl
index 67b7160304155..546f29218a0bd 100644
--- a/test/reduce.jl
+++ b/test/reduce.jl
@@ -43,7 +43,7 @@
 @test mapreduce(-, +, [-10]) == 10
 @test mapreduce(abs2, +, [-9, -3]) == 81 + 9
 @test mapreduce(-, +, [-9, -3, -4, 8, -2]) == (9 + 3 + 4 - 8 + 2)
-@test mapreduce(-, +, collect(linspace(1.0, 10000.0, 10000))) == -50005000.0
+@test mapreduce(-, +, Vector(linspace(1.0, 10000.0, 10000))) == -50005000.0
 # empty mr
 @test mapreduce(abs2, +, Float64[]) === 0.0
 @test mapreduce(abs2, Base.scalarmax, Float64[]) === 0.0
@@ -209,7 +209,7 @@ prod2(itr) = invoke(prod, Tuple{Any}, itr)
 @test minimum(abs2, 3:7) == 9
 
 @test maximum(Int16[1]) === Int16(1)
-@test maximum(collect(Int16(1):Int16(100))) === Int16(100)
+@test maximum(Vector(Int16(1):Int16(100))) === Int16(100)
 @test maximum(Int32[1,2]) === Int32(2)
 
 A = circshift(reshape(1:24,2,3,4), (0,1,1))
@@ -357,8 +357,8 @@ let es = sum(BigFloat.(z)), es2 = sum(BigFloat.(z[1:10^5]))
     @test (es2 - cs[10^5]) < es2 * 1e-13
 end
 
-@test sum(collect(map(UInt8,0:255))) == 32640
-@test sum(collect(map(UInt8,254:255))) == 509
+@test sum(Vector(map(UInt8,0:255))) == 32640
+@test sum(Vector(map(UInt8,254:255))) == 509
 
 A = reshape(map(UInt8, 101:109), (3,3))
 @test @inferred(sum(A)) == 945
@@ -374,7 +374,7 @@ A = reshape(map(UInt8, 1:100), (10,10))
 @test prod([-0.0, -0.0]) === 0.0
 
 #contains
-let A = collect(1:10)
+let A = Vector(1:10)
     @test A ∋ 5
     @test A ∌ 11
     @test any(y->y==6,A)
diff --git a/test/show.jl b/test/show.jl
index b852e512f0afe..fd8a025478e1e 100644
--- a/test/show.jl
+++ b/test/show.jl
@@ -586,8 +586,8 @@ end
 # This fits on screen:
 @test replstr(Matrix(1.0I, 10, 10)) == "10×10 Array{Float64,2}:\n 1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n 0.0  1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n 0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n 0.0  0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0  0.0\n 0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0\n 0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  0.0\n 0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0\n 0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0\n 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0\n 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0"
 # an array too long vertically to fit on screen, and too long horizontally:
-@test replstr(collect(1.:100.)) == "100-element Array{Float64,1}:\n   1.0\n   2.0\n   3.0\n   4.0\n   5.0\n   6.0\n   7.0\n   8.0\n   9.0\n  10.0\n   ⋮  \n  92.0\n  93.0\n  94.0\n  95.0\n  96.0\n  97.0\n  98.0\n  99.0\n 100.0"
-@test replstr(collect(1.:100.)') == "1×100 Adjoint{Float64,Array{Float64,1}}:\n 1.0  2.0  3.0  4.0  5.0  6.0  7.0  …  95.0  96.0  97.0  98.0  99.0  100.0"
+@test replstr(Vector(1.:100.)) == "100-element Array{Float64,1}:\n   1.0\n   2.0\n   3.0\n   4.0\n   5.0\n   6.0\n   7.0\n   8.0\n   9.0\n  10.0\n   ⋮  \n  92.0\n  93.0\n  94.0\n  95.0\n  96.0\n  97.0\n  98.0\n  99.0\n 100.0"
+@test replstr(Vector(1.:100.)') == "1×100 Adjoint{Float64,Array{Float64,1}}:\n 1.0  2.0  3.0  4.0  5.0  6.0  7.0  …  95.0  96.0  97.0  98.0  99.0  100.0"
 # too big in both directions to fit on screen:
 @test replstr((1.:100.)*(1:100)') == "100×100 Array{Float64,2}:\n   1.0    2.0    3.0    4.0    5.0    6.0  …    97.0    98.0    99.0    100.0\n   2.0    4.0    6.0    8.0   10.0   12.0      194.0   196.0   198.0    200.0\n   3.0    6.0    9.0   12.0   15.0   18.0      291.0   294.0   297.0    300.0\n   4.0    8.0   12.0   16.0   20.0   24.0      388.0   392.0   396.0    400.0\n   5.0   10.0   15.0   20.0   25.0   30.0      485.0   490.0   495.0    500.0\n   6.0   12.0   18.0   24.0   30.0   36.0  …   582.0   588.0   594.0    600.0\n   7.0   14.0   21.0   28.0   35.0   42.0      679.0   686.0   693.0    700.0\n   8.0   16.0   24.0   32.0   40.0   48.0      776.0   784.0   792.0    800.0\n   9.0   18.0   27.0   36.0   45.0   54.0      873.0   882.0   891.0    900.0\n  10.0   20.0   30.0   40.0   50.0   60.0      970.0   980.0   990.0   1000.0\n   ⋮                                  ⋮    ⋱                                 \n  92.0  184.0  276.0  368.0  460.0  552.0     8924.0  9016.0  9108.0   9200.0\n  93.0  186.0  279.0  372.0  465.0  558.0     9021.0  9114.0  9207.0   9300.0\n  94.0  188.0  282.0  376.0  470.0  564.0     9118.0  9212.0  9306.0   9400.0\n  95.0  190.0  285.0  380.0  475.0  570.0     9215.0  9310.0  9405.0   9500.0\n  96.0  192.0  288.0  384.0  480.0  576.0  …  9312.0  9408.0  9504.0   9600.0\n  97.0  194.0  291.0  388.0  485.0  582.0     9409.0  9506.0  9603.0   9700.0\n  98.0  196.0  294.0  392.0  490.0  588.0     9506.0  9604.0  9702.0   9800.0\n  99.0  198.0  297.0  396.0  495.0  594.0     9603.0  9702.0  9801.0   9900.0\n 100.0  200.0  300.0  400.0  500.0  600.0     9700.0  9800.0  9900.0  10000.0"
 
@@ -1031,7 +1031,7 @@ let x = TypeVar(:_), y = TypeVar(:_)
 end
 
 @testset "showarg" begin
-    A = reshape(collect(Int16(1):Int16(2*3*5)), 2, 3, 5)
+    A = reshape(Vector(Int16(1):Int16(2*3*5)), 2, 3, 5)
     @test summary(A) == "2×3×5 Array{Int16,3}"
     v = view(A, :, 3, 2:5)
     @test summary(v) == "2×4 view(::Array{Int16,3}, :, 3, 2:5) with eltype Int16"
diff --git a/test/simdloop.jl b/test/simdloop.jl
index 4909101cc108d..72513a1311d3b 100644
--- a/test/simdloop.jl
+++ b/test/simdloop.jl
@@ -144,5 +144,5 @@ function simd_sum_over_array(a)
     end
     s
 end
-@test 2001000 == simd_sum_over_array(collect(1:2000))
+@test 2001000 == simd_sum_over_array(Vector(1:2000))
 @test 2001000 == simd_sum_over_array(Float32[i+j*500 for i=1:500, j=0:3])
diff --git a/test/sorting.jl b/test/sorting.jl
index 7d969627b0ca9..e8fc91ce94a5d 100644
--- a/test/sorting.jl
+++ b/test/sorting.jl
@@ -20,7 +20,7 @@ end
 @test partialsort([3,6,30,1,9],3) == 6
 @test partialsort([3,6,30,1,9],3:4) == [6,9]
 @test partialsortperm([3,6,30,1,9], 3:4) == [2,5]
-@test partialsortperm!(collect(1:5), [3,6,30,1,9], 3:4) == [2,5]
+@test partialsortperm!(Vector(1:5), [3,6,30,1,9], 3:4) == [2,5]
 let a=[1:10;]
     for r in Any[2:4, 1:2, 10:10, 4:2, 2:1, 4:-1:2, 2:-1:1, 10:-1:10, 4:1:3, 1:2:8, 10:-3:1]
         @test partialsort(a, r) == [r;]
diff --git a/test/sparse/sparse.jl b/test/sparse/sparse.jl
index 4727949818754..a40ed7aaabe4c 100644
--- a/test/sparse/sparse.jl
+++ b/test/sparse/sparse.jl
@@ -867,7 +867,7 @@ end
     @test nnz(A) == 13
     @test count(!iszero, A) == 3
     @test A[lininds] == A[X] == zeros(Int, 10)
-    c = collect(11:20); c[1] = c[3] = 0
+    c = Vector(11:20); c[1] = c[3] = 0
     A[lininds] = c
     @test nnz(A) == 13
     @test count(!iszero, A) == 11
@@ -1707,8 +1707,8 @@ end
 end
 
 @testset "issue #13008" begin
-    @test_throws ArgumentError sparse(collect(1:100), collect(1:100), fill(5,100), 5, 5)
-    @test_throws ArgumentError sparse(Int[], collect(1:5), collect(1:5))
+    @test_throws ArgumentError sparse(Vector(1:100), Vector(1:100), fill(5,100), 5, 5)
+    @test_throws ArgumentError sparse(Int[], Vector(1:5), Vector(1:5))
 end
 
 @testset "issue #13024" begin
@@ -1864,7 +1864,7 @@ end
 # are called. (Issue #18705.) EDIT: #19239 unified broadcast over a single sparse matrix,
 # eliminating the former operation classes.
 @testset "issue #18705" begin
-    S = sparse(Diagonal(collect(1.0:5.0)))
+    S = sparse(Diagonal(1.0:5.0))
     @test isa(sin.(S), SparseMatrixCSC)
 end
 
@@ -1906,7 +1906,7 @@ end
 # Check that `broadcast` methods specialized for unary operations over
 # `SparseMatrixCSC`s determine a reasonable return type.
 @testset "issue #18974" begin
-    S = sparse(Diagonal(collect(Int64(1):Int64(4))))
+    S = sparse(Diagonal(Int64(1):Int64(4)))
     @test eltype(sin.(S)) == Float64
 end
 
diff --git a/test/sparse/sparsevector.jl b/test/sparse/sparsevector.jl
index d2a822cd03226..da1d471508f61 100644
--- a/test/sparse/sparsevector.jl
+++ b/test/sparse/sparsevector.jl
@@ -1083,7 +1083,7 @@ sv[1] = 0
     # Compare stored zero semantics between SparseVector and SparseMatrixCSC
     let S = SparseMatrixCSC(10,1,[1,6],[1,3,5,6,7],[0,1,2,0,3]), x = SparseVector(10,[1,3,5,6,7],[0,1,2,0,3])
         @test nnz(S) == nnz(x) == 5
-        for I = (:, 1:10, collect(1:10))
+        for I = (:, 1:10, Vector(1:10))
             @test S[I,1] == S[I] == x[I] == x
             @test nnz(S[I,1]) == nnz(S[I]) == nnz(x[I]) == nnz(x)
         end
@@ -1112,19 +1112,19 @@ end
 @testset "Issue 14589" begin
     # test vectors with no zero elements
     let x = sparsevec(1:7, [3., 2., -1., 1., -2., -3., 3.], 7)
-        @test collect(sort(x)) == sort(collect(x))
+        @test Vector(sort(x)) == sort(Vector(x))
     end
     # test vectors with all zero elements
     let x = sparsevec(Int64[], Float64[], 7)
-        @test collect(sort(x)) == sort(collect(x))
+        @test Vector(sort(x)) == sort(Vector(x))
     end
     # test vector with sparsity approx 1/2
     let x = sparsevec(1:7, [3., 2., -1., 1., -2., -3., 3.], 15)
-        @test collect(sort(x)) == sort(collect(x))
+        @test Vector(sort(x)) == sort(Vector(x))
         # apply three distinct tranformations where zeros sort into start/middle/end
-        @test collect(sort(x, by=abs)) == sort(collect(x), by=abs)
-        @test collect(sort(x, by=sign)) == sort(collect(x), by=sign)
-        @test collect(sort(x, by=inv)) == sort(collect(x), by=inv)
+        @test Vector(sort(x, by=abs)) == sort(Vector(x), by=abs)
+        @test Vector(sort(x, by=sign)) == sort(Vector(x), by=sign)
+        @test Vector(sort(x, by=inv)) == sort(Vector(x), by=inv)
     end
 end
 @testset "fill!" begin
diff --git a/test/statistics.jl b/test/statistics.jl
index 5b6154260fb2f..86f00340c833d 100644
--- a/test/statistics.jl
+++ b/test/statistics.jl
@@ -107,19 +107,19 @@ end
     @test var([1], 1; mean=[2], corrected=false) ≈ [1.0]
 
     @test var(1:8) == 6.
-    @test varm(1:8,1) == varm(collect(1:8),1)
+    @test varm(1:8,1) == varm(Vector(1:8),1)
     @test isnan(varm(1:1,1))
     @test isnan(var(1:1))
     @test isnan(var(1:-1))
 
     @test @inferred(var(1.0:8.0)) == 6.
-    @test varm(1.0:8.0,1.0) == varm(collect(1.0:8.0),1)
+    @test varm(1.0:8.0,1.0) == varm(Vector(1.0:8.0),1)
     @test isnan(varm(1.0:1.0,1.0))
     @test isnan(var(1.0:1.0))
     @test isnan(var(1.0:-1.0))
 
     @test @inferred(var(1.0f0:8.0f0)) === 6.f0
-    @test varm(1.0f0:8.0f0,1.0f0) == varm(collect(1.0f0:8.0f0),1)
+    @test varm(1.0f0:8.0f0,1.0f0) == varm(Vector(1.0f0:8.0f0),1)
     @test isnan(varm(1.0f0:1.0f0,1.0f0))
     @test isnan(var(1.0f0:1.0f0))
     @test isnan(var(1.0f0:-1.0f0))
@@ -328,7 +328,7 @@ end
     @test cor(1:17, 1:17) <= 1.0
     @test cor(1:17, 18:34) <= 1.0
     let tmp = linspace(1, 85, 100)
-        tmp2 = collect(tmp)
+        tmp2 = Vector(tmp)
         @test cor(tmp, tmp) <= 1.0
         @test cor(tmp, tmp2) <= 1.0
     end
@@ -338,9 +338,9 @@ end
     @test quantile([1,2,3,4],0.5) == 2.5
     @test quantile([1,2,3,4],[0.5]) == [2.5]
     @test quantile([1., 3],[.25,.5,.75])[2] == median([1., 3])
-    @test quantile(100.0:-1.0:0.0, 0.0:0.1:1.0) == collect(0.0:10.0:100.0)
-    @test quantile(0.0:100.0, 0.0:0.1:1.0, sorted=true) == collect(0.0:10.0:100.0)
-    @test quantile(100f0:-1f0:0.0, 0.0:0.1:1.0) == collect(0f0:10f0:100f0)
+    @test quantile(100.0:-1.0:0.0, 0.0:0.1:1.0) == 0.0:10.0:100.0
+    @test quantile(0.0:100.0, 0.0:0.1:1.0, sorted=true) == 0.0:10.0:100.0
+    @test quantile(100f0:-1f0:0.0, 0.0:0.1:1.0) == 0f0:10f0:100f0
     @test quantile([Inf,Inf],0.5) == Inf
     @test quantile([-Inf,1],0.5) == -Inf
     @test quantile([0,1],1e-18) == 1e-18
@@ -417,7 +417,7 @@ isdefined(Main, :TestHelpers) || @eval Main include("TestHelpers.jl")
 using Main.TestHelpers: Furlong
 @testset "Unitful elements" begin
     r = Furlong(1):Furlong(1):Furlong(2)
-    a = collect(r)
+    a = Vector(r)
     @test sum(r) == sum(a) == Furlong(3)
     @test cumsum(r) == Furlong.([1,3])
     @test mean(r) == mean(a) == median(a) == median(r) == Furlong(1.5)
diff --git a/test/subarray.jl b/test/subarray.jl
index b23a267fc80ec..3a1917ac9367c 100644
--- a/test/subarray.jl
+++ b/test/subarray.jl
@@ -486,12 +486,12 @@ end
 # issue #15168
 let A = rand(10), sA = view(copy(A), :)
     @test sA[Int16(1)] === sA[Int32(1)] === sA[Int64(1)] === A[1]
-    permute!(sA, collect(Int16, 1:10))
+    permute!(sA, Vector{Int16}(1:10))
     @test A == sA
 end
 
 # the following segfaults with LLVM 3.8 on Windows, ref #15417
-@test collect(view(view(reshape(1:13^3, 13, 13, 13), 3:7, 6:6, :), 1:2:5, :, 1:2:5)) ==
+@test Array(view(view(reshape(1:13^3, 13, 13, 13), 3:7, 6:6, :), 1:2:5, :, 1:2:5)) ==
     cat(3,[68,70,72],[406,408,410],[744,746,748])
 
 # tests @view (and replace_ref_end!)