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diff --git a/src/armadillo/include/armadillo_bits/glue_cov_meat.hpp b/src/armadillo/include/armadillo_bits/glue_cov_meat.hpp
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+++ b/src/armadillo/include/armadillo_bits/glue_cov_meat.hpp
@@ -0,0 +1,69 @@
+// SPDX-License-Identifier: Apache-2.0
+// 
+// Copyright 2008-2016 Conrad Sanderson (http://conradsanderson.id.au)
+// Copyright 2008-2016 National ICT Australia (NICTA)
+// 
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+// http://www.apache.org/licenses/LICENSE-2.0
+// 
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// ------------------------------------------------------------------------
+
+
+//! \addtogroup glue_cov
+//! @{
+
+
+
+template<typename T1, typename T2>
+inline
+void
+glue_cov::apply(Mat<typename T1::elem_type>& out, const Glue<T1,T2,glue_cov>& X)
+  {
+  arma_extra_debug_sigprint();
+  
+  typedef typename T1::elem_type eT;
+  
+  const uword norm_type = X.aux_uword;
+  
+  const unwrap<T1> UA(X.A);
+  const unwrap<T2> UB(X.B);
+  
+  const Mat<eT>& A = UA.M;
+  const Mat<eT>& B = UB.M;
+  
+  const Mat<eT>& AA = (A.n_rows == 1)
+                      ? Mat<eT>(const_cast<eT*>(A.memptr()), A.n_cols, A.n_rows, false, false)
+                      : Mat<eT>(const_cast<eT*>(A.memptr()), A.n_rows, A.n_cols, false, false);
+  
+  const Mat<eT>& BB = (B.n_rows == 1)
+                      ? Mat<eT>(const_cast<eT*>(B.memptr()), B.n_cols, B.n_rows, false, false)
+                      : Mat<eT>(const_cast<eT*>(B.memptr()), B.n_rows, B.n_cols, false, false);
+  
+  arma_debug_assert_mul_size(AA, BB, true, false, "cov()");
+  
+  if( (A.n_elem == 0) || (B.n_elem == 0) )
+    {
+    out.reset();
+    return;
+    }
+  
+  const uword N        = AA.n_rows;
+  const eT    norm_val = (norm_type == 0) ? ( (N > 1) ? eT(N-1) : eT(1) ) : eT(N);
+  
+  const Mat<eT> tmp1 = AA.each_row() - mean(AA,0);
+  const Mat<eT> tmp2 = BB.each_row() - mean(BB,0);
+  
+  out = tmp1.t() * tmp2;
+  out /= norm_val;
+  }
+
+
+
+//! @}