diff --git a/internal/ceres/autodiff_cost_function_test.cc b/internal/ceres/autodiff_cost_function_test.cc
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+++ b/internal/ceres/autodiff_cost_function_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 "ceres/autodiff_cost_function.h"
+
+#include <cstddef>
+
+#include "gtest/gtest.h"
+#include "ceres/cost_function.h"
+
+namespace ceres {
+namespace internal {
+
+class BinaryScalarCost {
+ public:
+  explicit BinaryScalarCost(double a): a_(a) {}
+  template <typename T>
+  bool operator()(const T* const x, const T* const y,
+                  T* cost) const {
+    cost[0] =
+      x[0] * y[0] + x[1] * y[1]  - T(a_);
+    return true;
+  }
+ private:
+  double a_;
+};
+
+
+TEST(AutoDiffResidualAndJacobian, BilinearDifferentiationTest) {
+  CostFunction* cost_function  =
+    new AutoDiffCostFunction<BinaryScalarCost, 1, 2, 2>(
+        new BinaryScalarCost(1.0));
+
+  double** parameters = new double*[2];
+  parameters[0] = new double[2];
+  parameters[1] = new double[2];
+
+  parameters[0][0] = 1;
+  parameters[0][1] = 2;
+
+  parameters[1][0] = 3;
+  parameters[1][1] = 4;
+
+  double** jacobians = new double*[2];
+  jacobians[0] = new double[2];
+  jacobians[1] = new double[2];
+
+
+  double residuals = 0.0;
+
+  cost_function->Evaluate(parameters, &residuals, NULL);
+  EXPECT_EQ(residuals, 10);
+  cost_function->Evaluate(parameters, &residuals, jacobians);
+
+  EXPECT_EQ(jacobians[0][0], 3);
+  EXPECT_EQ(jacobians[0][1], 4);
+  EXPECT_EQ(jacobians[1][0], 1);
+  EXPECT_EQ(jacobians[1][1], 2);
+
+  delete []jacobians[0];
+  delete []jacobians[1];
+  delete []parameters[0];
+  delete []parameters[1];
+  delete []jacobians;
+  delete []parameters;
+  delete cost_function;
+}
+
+}  // namespace internal
+}  // namespace ceres