diff --git a/internal/ceres/block_sparse_matrix_test.cc b/internal/ceres/block_sparse_matrix_test.cc
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+++ b/internal/ceres/block_sparse_matrix_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/block_sparse_matrix.h"
+
+#include <string>
+#include <glog/logging.h>
+#include "gtest/gtest.h"
+#include "ceres/casts.h"
+#include "ceres/linear_least_squares_problems.h"
+#include "ceres/matrix_proto.h"
+#include "ceres/triplet_sparse_matrix.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/internal/scoped_ptr.h"
+
+namespace ceres {
+namespace internal {
+
+class BlockSparseMatrixTest : public ::testing::Test {
+ protected :
+  virtual void SetUp() {
+    scoped_ptr<LinearLeastSquaresProblem> problem(
+        CreateLinearLeastSquaresProblemFromId(2));
+    CHECK_NOTNULL(problem.get());
+    A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
+
+    problem.reset(CreateLinearLeastSquaresProblemFromId(1));
+    CHECK_NOTNULL(problem.get());
+    B_.reset(down_cast<TripletSparseMatrix*>(problem->A.release()));
+
+    CHECK_EQ(A_->num_rows(), B_->num_rows());
+    CHECK_EQ(A_->num_cols(), B_->num_cols());
+    CHECK_EQ(A_->num_nonzeros(), B_->num_nonzeros());
+  }
+
+  scoped_ptr<BlockSparseMatrix> A_;
+  scoped_ptr<TripletSparseMatrix> B_;
+};
+
+TEST_F(BlockSparseMatrixTest, SetZeroTest) {
+  A_->SetZero();
+  EXPECT_EQ(13, A_->num_nonzeros());
+}
+
+TEST_F(BlockSparseMatrixTest, RightMultiplyTest) {
+  Vector y_a = Vector::Zero(A_->num_rows());
+  Vector y_b = Vector::Zero(A_->num_rows());
+  for (int i = 0; i < A_->num_cols(); ++i) {
+    Vector x = Vector::Zero(A_->num_cols());
+    x[i] = 1.0;
+    A_->RightMultiply(x.data(), y_a.data());
+    B_->RightMultiply(x.data(), y_b.data());
+    EXPECT_LT((y_a - y_b).norm(), 1e-12);
+  }
+}
+
+TEST_F(BlockSparseMatrixTest, LeftMultiplyTest) {
+  Vector y_a = Vector::Zero(A_->num_cols());
+  Vector y_b = Vector::Zero(A_->num_cols());
+  for (int i = 0; i < A_->num_rows(); ++i) {
+    Vector x = Vector::Zero(A_->num_rows());
+    x[i] = 1.0;
+    A_->LeftMultiply(x.data(), y_a.data());
+    B_->LeftMultiply(x.data(), y_b.data());
+    EXPECT_LT((y_a - y_b).norm(), 1e-12);
+  }
+}
+
+TEST_F(BlockSparseMatrixTest, SquaredColumnNormTest) {
+  Vector y_a = Vector::Zero(A_->num_cols());
+  Vector y_b = Vector::Zero(A_->num_cols());
+  A_->SquaredColumnNorm(y_a.data());
+  B_->SquaredColumnNorm(y_b.data());
+  EXPECT_LT((y_a - y_b).norm(), 1e-12);
+}
+
+TEST_F(BlockSparseMatrixTest, ToDenseMatrixTest) {
+  Matrix m_a;
+  Matrix m_b;
+  A_->ToDenseMatrix(&m_a);
+  B_->ToDenseMatrix(&m_b);
+  EXPECT_LT((m_a - m_b).norm(), 1e-12);
+}
+
+#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+TEST_F(BlockSparseMatrixTest, Serialization) {
+  // Roundtrip through serialization and check for equality.
+  SparseMatrixProto proto;
+  A_->ToProto(&proto);
+
+  LOG(INFO) << proto.DebugString();
+
+  BlockSparseMatrix A2(proto);
+
+  Matrix m_a;
+  Matrix m_b;
+  A_->ToDenseMatrix(&m_a);
+  A2.ToDenseMatrix(&m_b);
+
+  LOG(INFO) << "\n" << m_a;
+  LOG(INFO) << "\n" << m_b;
+
+  EXPECT_LT((m_a - m_b).norm(), 1e-12);
+}
+#endif
+
+}  // namespace internal
+}  // namespace ceres