diff --git a/internal/ceres/unsymmetric_linear_solver_test.cc b/internal/ceres/unsymmetric_linear_solver_test.cc
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+++ b/internal/ceres/unsymmetric_linear_solver_test.cc
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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// * Redistributions of source code must retain the above copyright notice,
+//   this list of conditions and the following disclaimer.
+// * Redistributions in binary form must reproduce the above copyright notice,
+//   this list of conditions and the following disclaimer in the documentation
+//   and/or other materials provided with the distribution.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+//   used to endorse or promote products derived from this software without
+//   specific prior written permission.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+// POSSIBILITY OF SUCH DAMAGE.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#include <glog/logging.h>
+#include "gtest/gtest.h"
+#include "ceres/casts.h"
+#include "ceres/compressed_row_sparse_matrix.h"
+#include "ceres/linear_least_squares_problems.h"
+#include "ceres/linear_solver.h"
+#include "ceres/triplet_sparse_matrix.h"
+#include "ceres/internal/scoped_ptr.h"
+#include "ceres/types.h"
+
+
+namespace ceres {
+namespace internal {
+
+class UnsymmetricLinearSolverTest : public ::testing::Test {
+ protected :
+  virtual void SetUp() {
+    scoped_ptr<LinearLeastSquaresProblem> problem(
+        CreateLinearLeastSquaresProblemFromId(0));
+
+    CHECK_NOTNULL(problem.get());
+    A_.reset(down_cast<TripletSparseMatrix*>(problem->A.release()));
+    b_.reset(problem->b.release());
+    D_.reset(problem->D.release());
+    sol1_.reset(problem->x.release());
+    sol2_.reset(problem->x_D.release());
+    x_.reset(new double[A_->num_cols()]);
+  }
+
+  void TestSolver(LinearSolverType linear_solver_type) {
+    LinearSolver::Options options;
+    options.type = linear_solver_type;
+    scoped_ptr<LinearSolver> solver(LinearSolver::Create(options));
+
+    LinearSolver::PerSolveOptions per_solve_options;
+
+    // Unregularized
+    LinearSolver::Summary summary =
+        solver->Solve(A_.get(), b_.get(), per_solve_options, x_.get());
+
+    EXPECT_EQ(summary.termination_type, TOLERANCE);
+
+    for (int i = 0; i < A_->num_cols(); ++i) {
+      EXPECT_NEAR(sol1_[i], x_[i], 1e-8);
+    }
+
+    // Regularized solution
+    per_solve_options.D = D_.get();
+    summary = solver->Solve(A_.get(), b_.get(), per_solve_options, x_.get());
+
+    EXPECT_EQ(summary.termination_type, TOLERANCE);
+
+    for (int i = 0; i < A_->num_cols(); ++i) {
+      EXPECT_NEAR(sol2_[i], x_[i], 1e-8);
+    }
+  }
+
+  scoped_ptr<TripletSparseMatrix> A_;
+  scoped_array<double> b_;
+  scoped_array<double> D_;
+  scoped_array<double> sol1_;
+  scoped_array<double> sol2_;
+
+  scoped_array<double> x_;
+};
+
+// TODO(keir): Reduce duplication.
+TEST_F(UnsymmetricLinearSolverTest, DenseQR) {
+  LinearSolver::Options options;
+  options.type = DENSE_QR;
+  scoped_ptr<LinearSolver> solver(LinearSolver::Create(options));
+
+  LinearSolver::PerSolveOptions per_solve_options;
+  DenseSparseMatrix A(*A_);
+
+  // Unregularized
+  LinearSolver::Summary summary =
+      solver->Solve(&A, b_.get(), per_solve_options, x_.get());
+
+  EXPECT_EQ(summary.termination_type, TOLERANCE);
+  for (int i = 0; i < A_->num_cols(); ++i) {
+    EXPECT_NEAR(sol1_[i], x_[i], 1e-8);
+  }
+
+  VectorRef x(x_.get(), A_->num_cols());
+  VectorRef b(b_.get(), A_->num_rows());
+  Vector r = A.matrix()*x - b;
+  LOG(INFO) << "r = A*x - b: \n" << r;
+
+  // Regularized solution
+  per_solve_options.D = D_.get();
+  summary = solver->Solve(&A, b_.get(), per_solve_options, x_.get());
+
+  EXPECT_EQ(summary.termination_type, TOLERANCE);
+  for (int i = 0; i < A_->num_cols(); ++i) {
+    EXPECT_NEAR(sol2_[i], x_[i], 1e-8);
+  }
+}
+
+#ifndef CERES_NO_SUITESPARSE
+TEST_F(UnsymmetricLinearSolverTest, SparseNormalCholesky) {
+  LinearSolver::Options options;
+  options.type = SPARSE_NORMAL_CHOLESKY;
+  scoped_ptr<LinearSolver>solver(LinearSolver::Create(options));
+
+  LinearSolver::PerSolveOptions per_solve_options;
+  CompressedRowSparseMatrix A(*A_);
+
+  // Unregularized
+  LinearSolver::Summary summary =
+      solver->Solve(&A, b_.get(), per_solve_options, x_.get());
+
+  EXPECT_EQ(summary.termination_type, TOLERANCE);
+  for (int i = 0; i < A_->num_cols(); ++i) {
+    EXPECT_NEAR(sol1_[i], x_[i], 1e-8);
+  }
+
+  // Regularized solution
+  per_solve_options.D = D_.get();
+  summary = solver->Solve(&A, b_.get(), per_solve_options, x_.get());
+
+  EXPECT_EQ(summary.termination_type, TOLERANCE);
+  for (int i = 0; i < A_->num_cols(); ++i) {
+    EXPECT_NEAR(sol2_[i], x_[i], 1e-8);
+  }
+}
+#endif  // CERES_NO_SUITESPARSE
+
+}  // namespace internal
+}  // namespace ceres