add test

Update reduce.jl

stdlib/SparseArrays/test/higherorderfns.jl

@@ -718,12 +718,12 @@ end
     @test extrema(A; dims=2) == extrema(B; dims=2)
     @test extrema(A; dims=(1,2)) == extrema(B; dims=(1,2))
     @test extrema(f, A; dims=1) == extrema(f, B; dims=1)
-    @test extrema(sparse(C); dims=1) == extrema(C; dims=1)
+    @test_throws ArgumentError extrema(sparse(C); dims=1) == extrema(C; dims=1) # empty reduction is not allowed anymore
     @test extrema(A; dims=[]) == extrema(B; dims=[])
     @test extrema(x; dims=:) == extrema(y; dims=:)
     @test extrema(x; dims=1) == extrema(y; dims=1)
     @test extrema(f, x; dims=1) == extrema(f, y; dims=1)
-    @test_throws BoundsError extrema(sparse(z); dims=1)
+    @test_throws ArgumentError extrema(sparse(z); dims=1) # empty reduction is not allowed anymore
     @test extrema(x; dims=[]) == extrema(y; dims=[])
 end
 

test/reduce.jl

@@ -378,6 +378,40 @@ A = circshift(reshape(1:24,2,3,4), (0,1,1))
 @test size(extrema(A,dims=(1,2,3))) == size(maximum(A,dims=(1,2,3)))
 @test extrema(x->div(x, 2), A, dims=(2,3)) == reshape([(0,11),(1,12)],2,1,1)
 
+# TODO: drop `a′` once `minimum` and `maximum` is fixed
+# (the following test_broken pass)
+function test_extrema(a, a′ = a; dims_test = ((), 1, 2, (1,2), 3))
+    for dims in dims_test
+        vext = extrema(a; dims)
+        vmin, vmax = minimum(a′; dims), maximum(a′; dims)
+        @test all(x -> isequal(x[1], x[2:3]), zip(vext,vmin,vmax)) || foreach(i -> display(i),(eltype(a), vext,vmin,vmax))
+    end
+end
+@test_broken minimum([missing BigInt(1)], dims = 2)[1] === missing
+@testset "0.0,-0.0 test for extrema with dims" begin
+    @test extrema([-0.0;0.0], dims = 1)[1] === (-0.0,0.0)
+    @test tuple(extrema([-0.0;0.0], dims = 2)...) === ((-0.0, -0.0), (0.0, 0.0))
+end
+@testset "NaN/missing test for extrema with dims #43599" begin
+    for sz = (3, 10, 100)
+        for T in (Int, BigInt, Float64, BigFloat)
+            Aₘ = Matrix{Union{Float64, Missing}}(rand(-sz:sz, sz, sz))
+            Aₘ[rand(1:sz*sz, sz)] .= missing
+            ATₘ = Matrix{Union{T, Missing}}(Aₘ)
+            test_extrema(ATₘ, Aₘ)
+            if T <: AbstractFloat
+                Aₙ = map(i -> ismissing(i) ? T(NaN) : i, Aₘ)
+                ATₙ = map(i -> ismissing(i) ? T(NaN) : i, ATₘ)
+                test_extrema(ATₙ, Aₙ)
+                p = rand(1:sz*sz, sz)
+                Aₘ[p] .= NaN
+                ATₘ[p] .= NaN
+                test_extrema(ATₘ, Aₘ)
+            end
+        end
+    end
+end
+
 @testset "maximum/minimum/extrema with missing values" begin
     for x in (Vector{Union{Int,Missing}}(missing, 10),
               Vector{Union{Int,Missing}}(missing, 257))