diff --git a/internal/ceres/compressed_col_sparse_matrix_utils_test.cc b/internal/ceres/compressed_col_sparse_matrix_utils_test.cc
new file mode 100644
index 0000000..7efa0e3
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+++ b/internal/ceres/compressed_col_sparse_matrix_utils_test.cc
@@ -0,0 +1,196 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2013 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 <algorithm>
+#include "ceres/compressed_col_sparse_matrix_utils.h"
+#include "ceres/internal/port.h"
+#include "ceres/suitesparse.h"
+#include "ceres/triplet_sparse_matrix.h"
+#include "glog/logging.h"
+#include "gtest/gtest.h"
+
+namespace ceres {
+namespace internal {
+
+TEST(_, BlockPermutationToScalarPermutation) {
+  vector<int> blocks;
+  //  Block structure
+  //  0  --1-  ---2---  ---3---  4
+  // [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
+  blocks.push_back(1);
+  blocks.push_back(2);
+  blocks.push_back(3);
+  blocks.push_back(3);
+  blocks.push_back(1);
+
+  // Block ordering
+  // [1, 0, 2, 4, 5]
+  vector<int> block_ordering;
+  block_ordering.push_back(1);
+  block_ordering.push_back(0);
+  block_ordering.push_back(2);
+  block_ordering.push_back(4);
+  block_ordering.push_back(3);
+
+  // Expected ordering
+  // [1, 2, 0, 3, 4, 5, 9, 6, 7, 8]
+  vector<int> expected_scalar_ordering;
+  expected_scalar_ordering.push_back(1);
+  expected_scalar_ordering.push_back(2);
+  expected_scalar_ordering.push_back(0);
+  expected_scalar_ordering.push_back(3);
+  expected_scalar_ordering.push_back(4);
+  expected_scalar_ordering.push_back(5);
+  expected_scalar_ordering.push_back(9);
+  expected_scalar_ordering.push_back(6);
+  expected_scalar_ordering.push_back(7);
+  expected_scalar_ordering.push_back(8);
+
+  vector<int> scalar_ordering;
+  BlockOrderingToScalarOrdering(blocks,
+                                block_ordering,
+                                &scalar_ordering);
+  EXPECT_EQ(scalar_ordering.size(), expected_scalar_ordering.size());
+  for (int i = 0; i < expected_scalar_ordering.size(); ++i) {
+    EXPECT_EQ(scalar_ordering[i], expected_scalar_ordering[i]);
+  }
+}
+
+// Helper function to fill the sparsity pattern of a TripletSparseMatrix.
+int FillBlock(const vector<int>& row_blocks,
+              const vector<int>& col_blocks,
+              const int row_block_id,
+              const int col_block_id,
+              int* rows,
+              int* cols) {
+  int row_pos = 0;
+  for (int i = 0; i < row_block_id; ++i) {
+    row_pos += row_blocks[i];
+  }
+
+  int col_pos = 0;
+  for (int i = 0; i < col_block_id; ++i) {
+    col_pos += col_blocks[i];
+  }
+
+  int offset = 0;
+  for (int r = 0; r < row_blocks[row_block_id]; ++r) {
+    for (int c = 0; c < col_blocks[col_block_id]; ++c, ++offset) {
+      rows[offset] = row_pos + r;
+      cols[offset] = col_pos + c;
+    }
+  }
+  return offset;
+}
+
+TEST(_, ScalarMatrixToBlockMatrix) {
+  // Block sparsity.
+  //
+  //     [1 2 3 2]
+  // [1]  x   x
+  // [2]    x   x
+  // [2]  x x
+  // num_nonzeros = 1 + 3 + 4 + 4 + 1 + 2 = 15
+
+  vector<int> col_blocks;
+  col_blocks.push_back(1);
+  col_blocks.push_back(2);
+  col_blocks.push_back(3);
+  col_blocks.push_back(2);
+
+  vector<int> row_blocks;
+  row_blocks.push_back(1);
+  row_blocks.push_back(2);
+  row_blocks.push_back(2);
+
+  TripletSparseMatrix tsm(5, 8, 18);
+  int* rows = tsm.mutable_rows();
+  int* cols = tsm.mutable_cols();
+  fill(tsm.mutable_values(), tsm.mutable_values() + 18, 1.0);
+  int offset = 0;
+
+#define CERES_TEST_FILL_BLOCK(row_block_id, col_block_id) \
+  offset += FillBlock(row_blocks, col_blocks, \
+                      row_block_id, col_block_id, \
+                      rows + offset, cols + offset);
+
+  CERES_TEST_FILL_BLOCK(0, 0);
+  CERES_TEST_FILL_BLOCK(2, 0);
+  CERES_TEST_FILL_BLOCK(1, 1);
+  CERES_TEST_FILL_BLOCK(2, 1);
+  CERES_TEST_FILL_BLOCK(0, 2);
+  CERES_TEST_FILL_BLOCK(1, 3);
+#undef CERES_TEST_FILL_BLOCK
+
+  tsm.set_num_nonzeros(offset);
+
+  SuiteSparse ss;
+  scoped_ptr<cholmod_sparse> ccsm(ss.CreateSparseMatrix(&tsm));
+
+  vector<int> expected_block_rows;
+  expected_block_rows.push_back(0);
+  expected_block_rows.push_back(2);
+  expected_block_rows.push_back(1);
+  expected_block_rows.push_back(2);
+  expected_block_rows.push_back(0);
+  expected_block_rows.push_back(1);
+
+  vector<int> expected_block_cols;
+  expected_block_cols.push_back(0);
+  expected_block_cols.push_back(2);
+  expected_block_cols.push_back(4);
+  expected_block_cols.push_back(5);
+  expected_block_cols.push_back(6);
+
+  vector<int> block_rows;
+  vector<int> block_cols;
+  CompressedColumnScalarMatrixToBlockMatrix(reinterpret_cast<const int*>(ccsm->i),
+                                            reinterpret_cast<const int*>(ccsm->p),
+                                            row_blocks,
+                                            col_blocks,
+                                            &block_rows,
+                                            &block_cols);
+
+  EXPECT_EQ(block_cols.size(), expected_block_cols.size());
+  EXPECT_EQ(block_rows.size(), expected_block_rows.size());
+
+  for (int i = 0; i < expected_block_cols.size(); ++i) {
+    EXPECT_EQ(block_cols[i], expected_block_cols[i]);
+  }
+
+  for (int i = 0; i < expected_block_rows.size(); ++i) {
+    EXPECT_EQ(block_rows[i], expected_block_rows[i]);
+  }
+
+  ss.Free(ccsm.release());
+}
+
+}  // namespace internal
+}  // namespace ceres