diff --git a/Eigen/src/OrderingMethods/Amd.h b/Eigen/src/OrderingMethods/Amd.h
index df4e01d6c..ec13077fe 100644
--- a/Eigen/src/OrderingMethods/Amd.h
+++ b/Eigen/src/OrderingMethods/Amd.h
@@ -106,6 +106,7 @@ Index cs_tdfs(Index j, Index k, Index *head, const Index *next, Index *post, Ind
 template<typename Scalar, typename Index>
 void minimum_degree_ordering(SparseMatrix<Scalar,ColMajor,Index>& C, PermutationMatrix<Dynamic,Dynamic,Index>& perm)
 {
+  using std::sqrt;
   typedef SparseMatrix<Scalar,ColMajor,Index> CCS;
   
   int d, dk, dext, lemax = 0, e, elenk, eln, i, j, k, k1,
@@ -114,7 +115,7 @@ void minimum_degree_ordering(SparseMatrix<Scalar,ColMajor,Index>& C, Permutation
   unsigned int h;
   
   Index n = C.cols();
-  dense = std::max<Index> (16, 10 * sqrt ((double) n));   /* find dense threshold */
+  dense = std::max<Index> (16, Index(10 * sqrt(double(n))));   /* find dense threshold */
   dense = std::min<Index> (n-2, dense);
   
   Index cnz = C.nonZeros();
diff --git a/test/sparse.h b/test/sparse.h
index 84cd695f2..860d9ad9c 100644
--- a/test/sparse.h
+++ b/test/sparse.h
@@ -79,7 +79,7 @@ initSparse(double density,
   enum { IsRowMajor = SparseMatrix<Scalar,Opt2,Index>::IsRowMajor };
   sparseMat.setZero();
   //sparseMat.reserve(int(refMat.rows()*refMat.cols()*density));
-  sparseMat.reserve(VectorXi::Constant(IsRowMajor ? refMat.rows() : refMat.cols(), (1.5*density)*(IsRowMajor?refMat.cols():refMat.rows())));
+  sparseMat.reserve(VectorXi::Constant(IsRowMajor ? refMat.rows() : refMat.cols(), int((1.5*density)*(IsRowMajor?refMat.cols():refMat.rows()))));
   
   for(int j=0; j<sparseMat.outerSize(); j++)
   {