diff --git a/src/assembly.jl b/src/assembly.jl
index 57907bb..692a2f6 100644
--- a/src/assembly.jl
+++ b/src/assembly.jl
@@ -113,52 +113,3 @@ function assemble!(problem::Problem, time::Real, ::Type{Val{:mass_matrix}}; dens
     end
 end
 
-# Static condensation routines
-
-function eliminate_interior_dofs(K::SparseMatrixCSC, f::SparseMatrixCSC, B::Vector{Int64}, I::Vector{Int64}; F=nothing, chunk_size=100000)
-
-    dim = size(K, 1)
-    Kib = K[I,B]
-
-    if F == nothing
-        F = cholfact(1/2*(K + K')[I,I])
-    end
-
-    if dim < chunk_size
-        # for small problems we don't need to care about memory usage
-        Kd = Kib' * (F \ Kib)
-    else
-        # for larger problems calculate schur complement in pieces
-        nb = length(B)
-        p = nb > 10 ? round(Int, nb/10) : nb
-        Kd = zeros(nb, nb)
-        for bi in 1:nb
-            done = round(Int, bi/nb*100)
-            mod(bi, p) == 0 && info("Static condensation: $done % done")
-            C = full(F \ Kib[:, bi])
-            for bj in bi:nb
-                d = Kib[:, bj]
-                @inbounds Kd[bj,bi] = dot(C[rowvals(d)], nonzeros(d))
-            end
-        end
-        Kd += tril(Kd, -1)'
-    end
-
-    Kc = spzeros(dim, dim)
-    Kc[B,B] = K[B,B] - Kd
-
-    fc = spzeros(dim, 1)
-    fc[B] = f[B] - Kib' * (F \ f[I])
-
-    return Kc, fc
-end
-
-#=
-function reconstruct!(ca::CAssembly, x::SparseMatrixCSC)
-    if isa(ca.F, Factorization)
-        x[ca.interior_dofs] = ca.F \ (ca.fi - ca.Kib*x[ca.boundary_dofs])
-    else  # normal inverse of matrix
-        x[ca.interior_dofs] = ca.F * (ca.fi - ca.Kib*x[ca.boundary_dofs])
-    end
-end
-=#
diff --git a/test/test_assembly.jl b/test/test_assembly.jl
deleted file mode 100644
index 7fc9085..0000000
--- a/test/test_assembly.jl
+++ /dev/null
@@ -1,49 +0,0 @@
-# This file is a part of JuliaFEM.
-# License is MIT: see https://github.com/JuliaFEM/JuliaFEM.jl/blob/master/LICENSE.md
-
-using JuliaFEM
-using JuliaFEM.Testing
-
-@testset "test static condensation" begin
-
-    K = sparse([
-      4.0  -1.0  -2.0  -1.0
-     -1.0   4.0  -1.0  -2.0
-     -2.0  -1.0   4.0  -1.0
-     -1.0  -2.0  -1.0   4.0])
-
-    f = sparse([6.0, 6.0, 3.0, 3.0])
-
-    I = [1, 2]
-    B = [3, 4]
-
-    Kc, fc = eliminate_interior_dofs(K, f, B, I)
-    Kc = full(Kc)
-    fc = full(fc)
-    dump(Kc)
-    dump(fc)
-
-    Kc_expected = [
-        0.0 0.0  0.0  0.0
-        0.0 0.0  0.0  0.0
-        0.0 0.0  2.4 -2.4
-        0.0 0.0 -2.4  2.4]
-   fc_expected = [0.0, 0.0, 9.0, 9.0]
-
-   # TODO: needs to check numbers
-   @test isapprox(Kc, Kc_expected)
-   @test isapprox(fc, fc_expected)
-
-   #=
-   x = sparse(zeros(4))'
-   la = sparse(zeros(4))'
-   la[3] = la[4] = 24.0
-   reconstruct!(cass, x)
-   x = full(x)
-   info(la)
-   info(x)
-   @test isapprox(x[1], 1.0)
-   @test isapprox(x[2], 1.0)
-   =#
-end
-