diff --git a/test/array.cpp b/test/array.cpp
index 8006531..df1e1b4 100644
--- a/test/array.cpp
+++ b/test/array.cpp
@@ -127,9 +127,12 @@
 
   // count
   VERIFY(((m1.abs()+1)>RealScalar(0.1)).count() == rows*cols);
+
+  typedef Array<typename ArrayType::Index, Dynamic, 1> ArrayOfIndices;
+  
   // TODO allows colwise/rowwise for array
-  VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayXi::Constant(cols,rows).transpose());
-  VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).rowwise().count(), ArrayXi::Constant(rows, cols));
+  VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayOfIndices::Constant(cols,rows).transpose());
+  VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).rowwise().count(), ArrayOfIndices::Constant(rows, cols));
 }
 
 template<typename ArrayType> void array_real(const ArrayType& m)
diff --git a/test/array_for_matrix.cpp b/test/array_for_matrix.cpp
index 516c040..477d178 100644
--- a/test/array_for_matrix.cpp
+++ b/test/array_for_matrix.cpp
@@ -124,9 +124,12 @@
 
   // count
   VERIFY(((m1.array().abs()+1)>RealScalar(0.1)).count() == rows*cols);
+
+  typedef Matrix<typename MatrixType::Index, Dynamic, 1> VectorOfIndices;
+
   // TODO allows colwise/rowwise for array
-  VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), RowVectorXi::Constant(cols,rows));
-  VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().rowwise().count(), VectorXi::Constant(rows, cols));
+  VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), VectorOfIndices::Constant(cols,rows).transpose());
+  VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().rowwise().count(), VectorOfIndices::Constant(rows, cols));
 }
 
 template<typename VectorType> void lpNorm(const VectorType& v)
diff --git a/test/nomalloc.cpp b/test/nomalloc.cpp
index a80145f..9eb8d13 100644
--- a/test/nomalloc.cpp
+++ b/test/nomalloc.cpp
@@ -133,7 +133,7 @@
 void test_nomalloc()
 {
   // check that our operator new is indeed called:
-  VERIFY_RAISES_ASSERT(MatrixXd dummy = MatrixXd::Random(3,3));
+  VERIFY_RAISES_ASSERT(MatrixXd dummy(MatrixXd::Random(3,3)));
   CALL_SUBTEST_1(nomalloc(Matrix<float, 1, 1>()) );
   CALL_SUBTEST_2(nomalloc(Matrix4d()) );
   CALL_SUBTEST_3(nomalloc(Matrix<float,32,32>()) );
diff --git a/test/qr_colpivoting.cpp b/test/qr_colpivoting.cpp
index a34feed..7064bc2 100644
--- a/test/qr_colpivoting.cpp
+++ b/test/qr_colpivoting.cpp
@@ -38,7 +38,7 @@
   MatrixType m1;
   createRandomPIMatrixOfRank(rank,rows,cols,m1);
   ColPivHouseholderQR<MatrixType> qr(m1);
-  VERIFY_IS_APPROX(rank, qr.rank());
+  VERIFY(rank == qr.rank());
   VERIFY(cols - qr.rank() == qr.dimensionOfKernel());
   VERIFY(!qr.isInjective());
   VERIFY(!qr.isInvertible());
@@ -66,7 +66,7 @@
   Matrix<Scalar,Rows,Cols> m1;
   createRandomPIMatrixOfRank(rank,Rows,Cols,m1);
   ColPivHouseholderQR<Matrix<Scalar,Rows,Cols> > qr(m1);
-  VERIFY_IS_APPROX(rank, qr.rank());
+  VERIFY(rank == qr.rank());
   VERIFY(Cols - qr.rank() == qr.dimensionOfKernel());
   VERIFY(qr.isInjective() == (rank == Rows));
   VERIFY(qr.isSurjective() == (rank == Cols));
diff --git a/test/qr_fullpivoting.cpp b/test/qr_fullpivoting.cpp
index 82c42c7..33350ce 100644
--- a/test/qr_fullpivoting.cpp
+++ b/test/qr_fullpivoting.cpp
@@ -37,7 +37,7 @@
   MatrixType m1;
   createRandomPIMatrixOfRank(rank,rows,cols,m1);
   FullPivHouseholderQR<MatrixType> qr(m1);
-  VERIFY_IS_APPROX(rank, qr.rank());
+  VERIFY(rank == qr.rank());
   VERIFY(cols - qr.rank() == qr.dimensionOfKernel());
   VERIFY(!qr.isInjective());
   VERIFY(!qr.isInvertible());
diff --git a/test/sizeof.cpp b/test/sizeof.cpp
index a724359..779f3b5 100644
--- a/test/sizeof.cpp
+++ b/test/sizeof.cpp
@@ -30,7 +30,7 @@
   if (MatrixType::RowsAtCompileTime!=Dynamic && MatrixType::ColsAtCompileTime!=Dynamic)
     VERIFY(sizeof(MatrixType)==sizeof(Scalar)*MatrixType::SizeAtCompileTime);
   else
-    VERIFY(sizeof(MatrixType)==sizeof(Scalar*) + 2 * sizeof(int));
+    VERIFY(sizeof(MatrixType)==sizeof(Scalar*) + 2 * sizeof(typename MatrixType::Index));
 }
 
 void test_sizeof()
diff --git a/test/visitor.cpp b/test/visitor.cpp
index 65ee60b..1ddabc6 100644
--- a/test/visitor.cpp
+++ b/test/visitor.cpp
@@ -27,22 +27,23 @@
 template<typename MatrixType> void matrixVisitor(const MatrixType& p)
 {
   typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::Index Index;
 
-  int rows = p.rows();
-  int cols = p.cols();
+  Index rows = p.rows();
+  Index cols = p.cols();
 
   // construct a random matrix where all coefficients are different
   MatrixType m;
   m = MatrixType::Random(rows, cols);
-  for(int i = 0; i < m.size(); i++)
-    for(int i2 = 0; i2 < i; i2++)
+  for(Index i = 0; i < m.size(); i++)
+    for(Index i2 = 0; i2 < i; i2++)
       while(m(i) == m(i2)) // yes, ==
         m(i) = ei_random<Scalar>();
   
   Scalar minc = Scalar(1000), maxc = Scalar(-1000);
-  int minrow=0,mincol=0,maxrow=0,maxcol=0;
-  for(int j = 0; j < cols; j++)
-  for(int i = 0; i < rows; i++)
+  Index minrow=0,mincol=0,maxrow=0,maxcol=0;
+  for(Index j = 0; j < cols; j++)
+  for(Index i = 0; i < rows; i++)
   {
     if(m(i,j) < minc)
     {
@@ -57,7 +58,7 @@
       maxcol = j;
     }
   }
-  int eigen_minrow, eigen_mincol, eigen_maxrow, eigen_maxcol;
+  Index eigen_minrow, eigen_mincol, eigen_maxrow, eigen_maxcol;
   Scalar eigen_minc, eigen_maxc;
   eigen_minc = m.minCoeff(&eigen_minrow,&eigen_mincol);
   eigen_maxc = m.maxCoeff(&eigen_maxrow,&eigen_maxcol);
@@ -74,20 +75,21 @@
 template<typename VectorType> void vectorVisitor(const VectorType& w)
 {
   typedef typename VectorType::Scalar Scalar;
+  typedef typename VectorType::Index Index;
 
-  int size = w.size();
+  Index size = w.size();
 
   // construct a random vector where all coefficients are different
   VectorType v;
   v = VectorType::Random(size);
-  for(int i = 0; i < size; i++)
-    for(int i2 = 0; i2 < i; i2++)
+  for(Index i = 0; i < size; i++)
+    for(Index i2 = 0; i2 < i; i2++)
       while(v(i) == v(i2)) // yes, ==
         v(i) = ei_random<Scalar>();
   
   Scalar minc = Scalar(1000), maxc = Scalar(-1000);
-  int minidx=0,maxidx=0;
-  for(int i = 0; i < size; i++)
+  Index minidx=0,maxidx=0;
+  for(Index i = 0; i < size; i++)
   {
     if(v(i) < minc)
     {
@@ -100,7 +102,7 @@
       maxidx = i;
     }
   }
-  int eigen_minidx, eigen_maxidx;
+  Index eigen_minidx, eigen_maxidx;
   Scalar eigen_minc, eigen_maxc;
   eigen_minc = v.minCoeff(&eigen_minidx);
   eigen_maxc = v.maxCoeff(&eigen_maxidx);