diff --git a/internal/ceres/system_test.cc b/internal/ceres/system_test.cc
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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2015 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// 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: keir@google.com (Keir Mierle)
+//         sameeragarwal@google.com (Sameer Agarwal)
+//
+// End-to-end tests for Ceres using Powell's function.
+
+#include <cmath>
+#include <cstdlib>
+
+#include "ceres/autodiff_cost_function.h"
+#include "ceres/problem.h"
+#include "ceres/solver.h"
+#include "ceres/test_util.h"
+#include "ceres/types.h"
+#include "glog/logging.h"
+#include "gtest/gtest.h"
+
+namespace ceres {
+namespace internal {
+
+// This class implements the SystemTestProblem interface and provides
+// access to an implementation of Powell's singular function.
+//
+//   F = 1/2 (f1^2 + f2^2 + f3^2 + f4^2)
+//
+//   f1 = x1 + 10*x2;
+//   f2 = sqrt(5) * (x3 - x4)
+//   f3 = (x2 - 2*x3)^2
+//   f4 = sqrt(10) * (x1 - x4)^2
+//
+// The starting values are x1 = 3, x2 = -1, x3 = 0, x4 = 1.
+// The minimum is 0 at (x1, x2, x3, x4) = 0.
+//
+// From: Testing Unconstrained Optimization Software by Jorge J. More, Burton S.
+// Garbow and Kenneth E. Hillstrom in ACM Transactions on Mathematical Software,
+// Vol 7(1), March 1981.
+class PowellsFunction {
+ public:
+  PowellsFunction() {
+    x_[0] =  3.0;
+    x_[1] = -1.0;
+    x_[2] =  0.0;
+    x_[3] =  1.0;
+
+    problem_.AddResidualBlock(
+        new AutoDiffCostFunction<F1, 1, 1, 1>(new F1), NULL, &x_[0], &x_[1]);
+    problem_.AddResidualBlock(
+        new AutoDiffCostFunction<F2, 1, 1, 1>(new F2), NULL, &x_[2], &x_[3]);
+    problem_.AddResidualBlock(
+        new AutoDiffCostFunction<F3, 1, 1, 1>(new F3), NULL, &x_[1], &x_[2]);
+    problem_.AddResidualBlock(
+        new AutoDiffCostFunction<F4, 1, 1, 1>(new F4), NULL, &x_[0], &x_[3]);
+
+    // Settings for the reference solution.
+    options_.linear_solver_type = ceres::DENSE_QR;
+    options_.max_num_iterations = 10;
+    options_.num_threads = 1;
+  }
+
+  Problem* mutable_problem() { return &problem_; }
+  Solver::Options* mutable_solver_options() { return &options_; }
+
+  static double kResidualTolerance;
+
+ private:
+  // Templated functions used for automatically differentiated cost
+  // functions.
+  class F1 {
+   public:
+    template <typename T> bool operator()(const T* const x1,
+                                          const T* const x2,
+                                          T* residual) const {
+      // f1 = x1 + 10 * x2;
+      *residual = *x1 + 10.0 * *x2;
+      return true;
+    }
+  };
+
+  class F2 {
+   public:
+    template <typename T> bool operator()(const T* const x3,
+                                          const T* const x4,
+                                          T* residual) const {
+      // f2 = sqrt(5) (x3 - x4)
+      *residual = sqrt(5.0) * (*x3 - *x4);
+      return true;
+    }
+  };
+
+  class F3 {
+   public:
+    template <typename T> bool operator()(const T* const x2,
+                                          const T* const x4,
+                                          T* residual) const {
+      // f3 = (x2 - 2 x3)^2
+      residual[0] = (x2[0] - 2.0 * x4[0]) * (x2[0] - 2.0 * x4[0]);
+      return true;
+    }
+  };
+
+  class F4 {
+   public:
+    template <typename T> bool operator()(const T* const x1,
+                                          const T* const x4,
+                                          T* residual) const {
+      // f4 = sqrt(10) (x1 - x4)^2
+      residual[0] = sqrt(10.0) * (x1[0] - x4[0]) * (x1[0] - x4[0]);
+      return true;
+    }
+  };
+
+  double x_[4];
+  Problem problem_;
+  Solver::Options options_;
+};
+
+double PowellsFunction::kResidualTolerance = 1e-8;
+
+typedef SystemTest<PowellsFunction> PowellTest;
+
+TEST_F(PowellTest, DenseQR) {
+  PowellsFunction powells_function;
+  Solver::Options* options = powells_function.mutable_solver_options();
+  options->linear_solver_type = DENSE_QR;
+  RunSolverForConfigAndExpectResidualsMatch(*options,
+                                            powells_function.mutable_problem());
+}
+
+TEST_F(PowellTest, DenseNormalCholesky) {
+  PowellsFunction powells_function;
+  Solver::Options* options = powells_function.mutable_solver_options();
+  options->linear_solver_type = DENSE_NORMAL_CHOLESKY;
+  RunSolverForConfigAndExpectResidualsMatch(*options,
+                                            powells_function.mutable_problem());
+}
+
+TEST_F(PowellTest, DenseSchur) {
+  PowellsFunction powells_function;
+  Solver::Options* options = powells_function.mutable_solver_options();
+  options->linear_solver_type = DENSE_SCHUR;
+  RunSolverForConfigAndExpectResidualsMatch(*options,
+                                            powells_function.mutable_problem());
+}
+
+TEST_F(PowellTest, IterativeSchurWithJacobi) {
+  PowellsFunction powells_function;
+  Solver::Options* options = powells_function.mutable_solver_options();
+  options->linear_solver_type = ITERATIVE_SCHUR;
+  options->sparse_linear_algebra_library_type = NO_SPARSE;
+  options->preconditioner_type = JACOBI;
+  RunSolverForConfigAndExpectResidualsMatch(*options,
+                                            powells_function.mutable_problem());
+}
+
+#ifndef CERES_NO_SUITESPARSE
+TEST_F(PowellTest, SparseNormalCholeskyUsingSuiteSparse) {
+  PowellsFunction powells_function;
+  Solver::Options* options = powells_function.mutable_solver_options();
+  options->linear_solver_type = SPARSE_NORMAL_CHOLESKY;
+  options->sparse_linear_algebra_library_type = SUITE_SPARSE;
+  RunSolverForConfigAndExpectResidualsMatch(*options,
+                                            powells_function.mutable_problem());
+}
+#endif  // CERES_NO_SUITESPARSE
+
+#ifndef CERES_NO_CXSPARSE
+TEST_F(PowellTest, SparseNormalCholeskyUsingCXSparse) {
+  PowellsFunction powells_function;
+  Solver::Options* options = powells_function.mutable_solver_options();
+  options->linear_solver_type = SPARSE_NORMAL_CHOLESKY;
+  options->sparse_linear_algebra_library_type = CX_SPARSE;
+  RunSolverForConfigAndExpectResidualsMatch(*options,
+                                            powells_function.mutable_problem());
+}
+#endif  // CERES_NO_CXSPARSE
+
+#ifndef CERES_NO_ACCELERATE_SPARSE
+TEST_F(PowellTest, SparseNormalCholeskyUsingAccelerateSparse) {
+  PowellsFunction powells_function;
+  Solver::Options* options = powells_function.mutable_solver_options();
+  options->linear_solver_type = SPARSE_NORMAL_CHOLESKY;
+  options->sparse_linear_algebra_library_type = ACCELERATE_SPARSE;
+  RunSolverForConfigAndExpectResidualsMatch(*options,
+                                            powells_function.mutable_problem());
+}
+#endif  // CERES_NO_ACCELERATE_SPARSE
+
+#ifdef CERES_USE_EIGEN_SPARSE
+TEST_F(PowellTest, SparseNormalCholeskyUsingEigenSparse) {
+  PowellsFunction powells_function;
+  Solver::Options* options = powells_function.mutable_solver_options();
+  options->linear_solver_type = SPARSE_NORMAL_CHOLESKY;
+  options->sparse_linear_algebra_library_type = EIGEN_SPARSE;
+  RunSolverForConfigAndExpectResidualsMatch(*options,
+                                            powells_function.mutable_problem());
+}
+#endif  // CERES_USE_EIGEN_SPARSE
+
+}  // namespace internal
+}  // namespace ceres