diff --git a/internal/ceres/dynamic_autodiff_cost_function_test.cc b/internal/ceres/dynamic_autodiff_cost_function_test.cc
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+++ b/internal/ceres/dynamic_autodiff_cost_function_test.cc
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+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 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: thadh@gmail.com (Thad Hughes)
+//         mierle@gmail.com (Keir Mierle)
+//         sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/dynamic_autodiff_cost_function.h"
+
+#include <cstddef>
+
+#include "gtest/gtest.h"
+
+namespace ceres {
+namespace internal {
+
+// Takes 2 parameter blocks:
+//     parameters[0] is size 10.
+//     parameters[1] is size 5.
+// Emits 21 residuals:
+//     A: i - parameters[0][i], for i in [0,10)  -- this is 10 residuals
+//     B: parameters[0][i] - i, for i in [0,10)  -- this is another 10.
+//     C: sum(parameters[0][i]^2 - 8*parameters[0][i]) + sum(parameters[1][i])
+class MyCostFunctor {
+ public:
+  template <typename T>
+  bool operator()(T const* const* parameters, T* residuals) const {
+    const T* params0 = parameters[0];
+    int r = 0;
+    for (int i = 0; i < 10; ++i) {
+      residuals[r++] = T(i) - params0[i];
+      residuals[r++] = params0[i] - T(i);
+    }
+
+    T c_residual(0.0);
+    for (int i = 0; i < 10; ++i) {
+      c_residual += pow(params0[i], 2) - T(8) * params0[i];
+    }
+
+    const T* params1 = parameters[1];
+    for (int i = 0; i < 5; ++i) {
+      c_residual += params1[i];
+    }
+    residuals[r++] = c_residual;
+    return true;
+  }
+};
+
+TEST(DynamicAutodiffCostFunctionTest, TestResiduals) {
+  vector<double> param_block_0(10, 0.0);
+  vector<double> param_block_1(5, 0.0);
+  DynamicAutoDiffCostFunction<MyCostFunctor, 3> cost_function(
+      new MyCostFunctor());
+  cost_function.AddParameterBlock(param_block_0.size());
+  cost_function.AddParameterBlock(param_block_1.size());
+  cost_function.SetNumResiduals(21);
+
+  // Test residual computation.
+  vector<double> residuals(21, -100000);
+  vector<double*> parameter_blocks(2);
+  parameter_blocks[0] = &param_block_0[0];
+  parameter_blocks[1] = &param_block_1[0];
+  EXPECT_TRUE(cost_function.Evaluate(&parameter_blocks[0],
+                                     residuals.data(),
+                                     NULL));
+  for (int r = 0; r < 10; ++r) {
+    EXPECT_EQ(1.0 * r, residuals.at(r * 2));
+    EXPECT_EQ(-1.0 * r, residuals.at(r * 2 + 1));
+  }
+  EXPECT_EQ(0, residuals.at(20));
+}
+
+TEST(DynamicAutodiffCostFunctionTest, TestJacobian) {
+  // Test the residual counting.
+  vector<double> param_block_0(10, 0.0);
+  for (int i = 0; i < 10; ++i) {
+    param_block_0[i] = 2 * i;
+  }
+  vector<double> param_block_1(5, 0.0);
+  DynamicAutoDiffCostFunction<MyCostFunctor, 3> cost_function(
+      new MyCostFunctor());
+  cost_function.AddParameterBlock(param_block_0.size());
+  cost_function.AddParameterBlock(param_block_1.size());
+  cost_function.SetNumResiduals(21);
+
+  // Prepare the residuals.
+  vector<double> residuals(21, -100000);
+
+  // Prepare the parameters.
+  vector<double*> parameter_blocks(2);
+  parameter_blocks[0] = &param_block_0[0];
+  parameter_blocks[1] = &param_block_1[0];
+
+  // Prepare the jacobian.
+  vector<vector<double> > jacobian_vect(2);
+  jacobian_vect[0].resize(21 * 10, -100000);
+  jacobian_vect[1].resize(21 * 5, -100000);
+  vector<double*> jacobian;
+  jacobian.push_back(jacobian_vect[0].data());
+  jacobian.push_back(jacobian_vect[1].data());
+
+  // Test jacobian computation.
+  EXPECT_TRUE(cost_function.Evaluate(parameter_blocks.data(),
+                                     residuals.data(),
+                                     jacobian.data()));
+
+  for (int r = 0; r < 10; ++r) {
+    EXPECT_EQ(-1.0 * r, residuals.at(r * 2));
+    EXPECT_EQ(+1.0 * r, residuals.at(r * 2 + 1));
+  }
+  EXPECT_EQ(420, residuals.at(20));
+  for (int p = 0; p < 10; ++p) {
+    // Check "A" Jacobian.
+    EXPECT_EQ(-1.0, jacobian_vect[0][2*p * 10 + p]);
+    // Check "B" Jacobian.
+    EXPECT_EQ(+1.0, jacobian_vect[0][(2*p+1) * 10 + p]);
+    jacobian_vect[0][2*p * 10 + p] = 0.0;
+    jacobian_vect[0][(2*p+1) * 10 + p] = 0.0;
+  }
+
+  // Check "C" Jacobian for first parameter block.
+  for (int p = 0; p < 10; ++p) {
+    EXPECT_EQ(4 * p - 8, jacobian_vect[0][20 * 10 + p]);
+    jacobian_vect[0][20 * 10 + p] = 0.0;
+  }
+  for (int i = 0; i < jacobian_vect[0].size(); ++i) {
+    EXPECT_EQ(0.0, jacobian_vect[0][i]);
+  }
+
+  // Check "C" Jacobian for second parameter block.
+  for (int p = 0; p < 5; ++p) {
+    EXPECT_EQ(1.0, jacobian_vect[1][20 * 5 + p]);
+    jacobian_vect[1][20 * 5 + p] = 0.0;
+  }
+  for (int i = 0; i < jacobian_vect[1].size(); ++i) {
+    EXPECT_EQ(0.0, jacobian_vect[1][i]);
+  }
+}
+
+}  // namespace internal
+}  // namespace ceres