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diff --git a/eigen/test/sparse_product.cpp b/eigen/test/sparse_product.cpp
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+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "sparse.h"
+
+template<typename SparseMatrixType, typename DenseMatrix, bool IsRowMajor=SparseMatrixType::IsRowMajor> struct test_outer;
+
+template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,false> {
+  static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
+    typedef typename SparseMatrixType::Index Index;
+    Index c  = internal::random<Index>(0,m2.cols()-1);
+    Index c1 = internal::random<Index>(0,m2.cols()-1);
+    VERIFY_IS_APPROX(m4=m2.col(c)*refMat2.col(c1).transpose(), refMat4=refMat2.col(c)*refMat2.col(c1).transpose());
+    VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.col(c).transpose(), refMat4=refMat2.col(c1)*refMat2.col(c).transpose());
+  }
+};
+
+template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,true> {
+  static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
+    typedef typename SparseMatrixType::Index Index;
+    Index r  = internal::random<Index>(0,m2.rows()-1);
+    Index c1 = internal::random<Index>(0,m2.cols()-1);
+    VERIFY_IS_APPROX(m4=m2.row(r).transpose()*refMat2.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*refMat2.col(c1).transpose());
+    VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.row(r), refMat4=refMat2.col(c1)*refMat2.row(r));
+  }
+};
+
+// (m2,m4,refMat2,refMat4,dv1);
+//     VERIFY_IS_APPROX(m4=m2.innerVector(c)*dv1.transpose(), refMat4=refMat2.colVector(c)*dv1.transpose());
+//     VERIFY_IS_APPROX(m4=dv1*mcm.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose());
+
+template<typename SparseMatrixType> void sparse_product()
+{
+  typedef typename SparseMatrixType::Index Index;
+  Index n = 100;
+  const Index rows  = internal::random<Index>(1,n);
+  const Index cols  = internal::random<Index>(1,n);
+  const Index depth = internal::random<Index>(1,n);
+  typedef typename SparseMatrixType::Scalar Scalar;
+  enum { Flags = SparseMatrixType::Flags };
+
+  double density = (std::max)(8./(rows*cols), 0.1);
+  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
+  typedef Matrix<Scalar,Dynamic,1> DenseVector;
+  typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
+  typedef SparseVector<Scalar,0,Index> ColSpVector;
+  typedef SparseVector<Scalar,RowMajor,Index> RowSpVector;
+
+  Scalar s1 = internal::random<Scalar>();
+  Scalar s2 = internal::random<Scalar>();
+
+  // test matrix-matrix product
+  {
+    DenseMatrix refMat2  = DenseMatrix::Zero(rows, depth);
+    DenseMatrix refMat2t = DenseMatrix::Zero(depth, rows);
+    DenseMatrix refMat3  = DenseMatrix::Zero(depth, cols);
+    DenseMatrix refMat3t = DenseMatrix::Zero(cols, depth);
+    DenseMatrix refMat4  = DenseMatrix::Zero(rows, cols);
+    DenseMatrix refMat4t = DenseMatrix::Zero(cols, rows);
+    DenseMatrix refMat5  = DenseMatrix::Random(depth, cols);
+    DenseMatrix refMat6  = DenseMatrix::Random(rows, rows);
+    DenseMatrix dm4 = DenseMatrix::Zero(rows, rows);
+//     DenseVector dv1 = DenseVector::Random(rows);
+    SparseMatrixType m2 (rows, depth);
+    SparseMatrixType m2t(depth, rows);
+    SparseMatrixType m3 (depth, cols);
+    SparseMatrixType m3t(cols, depth);
+    SparseMatrixType m4 (rows, cols);
+    SparseMatrixType m4t(cols, rows);
+    SparseMatrixType m6(rows, rows);
+    initSparse(density, refMat2,  m2);
+    initSparse(density, refMat2t, m2t);
+    initSparse(density, refMat3,  m3);
+    initSparse(density, refMat3t, m3t);
+    initSparse(density, refMat4,  m4);
+    initSparse(density, refMat4t, m4t);
+    initSparse(density, refMat6, m6);
+
+//     int c = internal::random<int>(0,depth-1);
+
+    // sparse * sparse
+    VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(m4=m2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
+    VERIFY_IS_APPROX(m4=m2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
+    VERIFY_IS_APPROX(m4=m2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
+
+    VERIFY_IS_APPROX(m4 = m2*m3/s1, refMat4 = refMat2*refMat3/s1);
+    VERIFY_IS_APPROX(m4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1);
+    VERIFY_IS_APPROX(m4 = s2*m2*m3*s1, refMat4 = s2*refMat2*refMat3*s1);
+
+    VERIFY_IS_APPROX(m4=(m2*m3).pruned(0), refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(m4=(m2t.transpose()*m3).pruned(0), refMat4=refMat2t.transpose()*refMat3);
+    VERIFY_IS_APPROX(m4=(m2t.transpose()*m3t.transpose()).pruned(0), refMat4=refMat2t.transpose()*refMat3t.transpose());
+    VERIFY_IS_APPROX(m4=(m2*m3t.transpose()).pruned(0), refMat4=refMat2*refMat3t.transpose());
+
+    // test aliasing
+    m4 = m2; refMat4 = refMat2;
+    VERIFY_IS_APPROX(m4=m4*m3, refMat4=refMat4*refMat3);
+
+    // sparse * dense
+    VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4=m2*refMat3t.transpose(), refMat4=refMat2*refMat3t.transpose());
+    VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3, refMat4=refMat2t.transpose()*refMat3);
+    VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
+
+    VERIFY_IS_APPROX(dm4=m2*(refMat3+refMat3), refMat4=refMat2*(refMat3+refMat3));
+    VERIFY_IS_APPROX(dm4=m2t.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2t.transpose()*(refMat3+refMat5)*0.5);
+
+    // dense * sparse
+    VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4=refMat2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
+    VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
+    VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
+
+    // sparse * dense and dense * sparse outer product
+    test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4);
+
+    VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6);
+    
+    // sparse matrix * sparse vector
+    ColSpVector cv0(cols), cv1;
+    DenseVector dcv0(cols), dcv1;
+    initSparse(2*density,dcv0, cv0);
+    
+    RowSpVector rv0(depth), rv1;
+    RowDenseVector drv0(depth), drv1(rv1);
+    initSparse(2*density,drv0, rv0);
+    
+    VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3);
+    VERIFY_IS_APPROX(rv1=rv0*m3, drv1=drv0*refMat3);
+    VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0);
+    VERIFY_IS_APPROX(cv1=m3t.adjoint()*cv0, dcv1=refMat3t.adjoint()*dcv0);
+    VERIFY_IS_APPROX(rv1=m3*cv0, drv1=refMat3*dcv0);
+  }
+  
+  // test matrix - diagonal product
+  {
+    DenseMatrix refM2 = DenseMatrix::Zero(rows, cols);
+    DenseMatrix refM3 = DenseMatrix::Zero(rows, cols);
+    DenseMatrix d3 = DenseMatrix::Zero(rows, cols);
+    DiagonalMatrix<Scalar,Dynamic> d1(DenseVector::Random(cols));
+    DiagonalMatrix<Scalar,Dynamic> d2(DenseVector::Random(rows));
+    SparseMatrixType m2(rows, cols);
+    SparseMatrixType m3(rows, cols);
+    initSparse<Scalar>(density, refM2, m2);
+    initSparse<Scalar>(density, refM3, m3);
+    VERIFY_IS_APPROX(m3=m2*d1, refM3=refM2*d1);
+    VERIFY_IS_APPROX(m3=m2.transpose()*d2, refM3=refM2.transpose()*d2);
+    VERIFY_IS_APPROX(m3=d2*m2, refM3=d2*refM2);
+    VERIFY_IS_APPROX(m3=d1*m2.transpose(), refM3=d1*refM2.transpose());
+    
+    // also check with a SparseWrapper:
+    DenseVector v1 = DenseVector::Random(cols);
+    DenseVector v2 = DenseVector::Random(rows);
+    VERIFY_IS_APPROX(m3=m2*v1.asDiagonal(), refM3=refM2*v1.asDiagonal());
+    VERIFY_IS_APPROX(m3=m2.transpose()*v2.asDiagonal(), refM3=refM2.transpose()*v2.asDiagonal());
+    VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2, refM3=v2.asDiagonal()*refM2);
+    VERIFY_IS_APPROX(m3=v1.asDiagonal()*m2.transpose(), refM3=v1.asDiagonal()*refM2.transpose());
+    
+    VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2*v1.asDiagonal(), refM3=v2.asDiagonal()*refM2*v1.asDiagonal());
+    
+    // evaluate to a dense matrix to check the .row() and .col() iterator functions
+    VERIFY_IS_APPROX(d3=m2*d1, refM3=refM2*d1);
+    VERIFY_IS_APPROX(d3=m2.transpose()*d2, refM3=refM2.transpose()*d2);
+    VERIFY_IS_APPROX(d3=d2*m2, refM3=d2*refM2);
+    VERIFY_IS_APPROX(d3=d1*m2.transpose(), refM3=d1*refM2.transpose());
+  }
+
+  // test self adjoint products
+  {
+    DenseMatrix b = DenseMatrix::Random(rows, rows);
+    DenseMatrix x = DenseMatrix::Random(rows, rows);
+    DenseMatrix refX = DenseMatrix::Random(rows, rows);
+    DenseMatrix refUp = DenseMatrix::Zero(rows, rows);
+    DenseMatrix refLo = DenseMatrix::Zero(rows, rows);
+    DenseMatrix refS = DenseMatrix::Zero(rows, rows);
+    SparseMatrixType mUp(rows, rows);
+    SparseMatrixType mLo(rows, rows);
+    SparseMatrixType mS(rows, rows);
+    do {
+      initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular);
+    } while (refUp.isZero());
+    refLo = refUp.adjoint();
+    mLo = mUp.adjoint();
+    refS = refUp + refLo;
+    refS.diagonal() *= 0.5;
+    mS = mUp + mLo;
+    // TODO be able to address the diagonal....
+    for (int k=0; k<mS.outerSize(); ++k)
+      for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
+        if (it.index() == k)
+          it.valueRef() *= 0.5;
+
+    VERIFY_IS_APPROX(refS.adjoint(), refS);
+    VERIFY_IS_APPROX(mS.adjoint(), mS);
+    VERIFY_IS_APPROX(mS, refS);
+    VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
+
+    VERIFY_IS_APPROX(x=mUp.template selfadjointView<Upper>()*b, refX=refS*b);
+    VERIFY_IS_APPROX(x=mLo.template selfadjointView<Lower>()*b, refX=refS*b);
+    VERIFY_IS_APPROX(x=mS.template selfadjointView<Upper|Lower>()*b, refX=refS*b);
+    
+    // sparse selfadjointView * sparse 
+    SparseMatrixType mSres(rows,rows);
+    VERIFY_IS_APPROX(mSres = mLo.template selfadjointView<Lower>()*mS,
+                     refX = refLo.template selfadjointView<Lower>()*refS);
+    // sparse * sparse selfadjointview
+    VERIFY_IS_APPROX(mSres = mS * mLo.template selfadjointView<Lower>(),
+                     refX = refS * refLo.template selfadjointView<Lower>());
+  }
+  
+}
+
+// New test for Bug in SparseTimeDenseProduct
+template<typename SparseMatrixType, typename DenseMatrixType> void sparse_product_regression_test()
+{
+  // This code does not compile with afflicted versions of the bug
+  SparseMatrixType sm1(3,2);
+  DenseMatrixType m2(2,2);
+  sm1.setZero();
+  m2.setZero();
+
+  DenseMatrixType m3 = sm1*m2;
+
+
+  // This code produces a segfault with afflicted versions of another SparseTimeDenseProduct
+  // bug
+
+  SparseMatrixType sm2(20000,2);
+  sm2.setZero();
+  DenseMatrixType m4(sm2*m2);
+
+  VERIFY_IS_APPROX( m4(0,0), 0.0 );
+}
+
+void test_sparse_product()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,ColMajor> >()) );
+    CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,RowMajor> >()) );
+    CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, ColMajor > >()) );
+    CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, RowMajor > >()) );
+    CALL_SUBTEST_3( (sparse_product<SparseMatrix<float,ColMajor,long int> >()) );
+    CALL_SUBTEST_4( (sparse_product_regression_test<SparseMatrix<double,RowMajor>, Matrix<double, Dynamic, Dynamic, RowMajor> >()) );
+  }
+}