diff --git a/internal/ceres/array_utils.h b/internal/ceres/array_utils.h
index 99cc8d8..742f439 100644
--- a/internal/ceres/array_utils.h
+++ b/internal/ceres/array_utils.h
@@ -28,7 +28,7 @@
 //
 // Author: sameeragarwal@google.com (Sameer Agarwal)
 //
-// Utility routines for validating arrays. 
+// Utility routines for validating arrays.
 //
 // These are useful for detecting two common class of errors.
 //
diff --git a/internal/ceres/autodiff_test.cc b/internal/ceres/autodiff_test.cc
index 1c56c22..23f9e9d 100644
--- a/internal/ceres/autodiff_test.cc
+++ b/internal/ceres/autodiff_test.cc
@@ -372,7 +372,8 @@
     const double kTolerance = 1e-14;
     for (int i = 0; i < num_residuals; ++i) {
       EXPECT_NEAR(J_x[2 * i + 0], i * x[1] * x[1], kTolerance) << "i: " << i;
-      EXPECT_NEAR(J_x[2 * i + 1], 2 * i * x[0] * x[1], kTolerance) << "i: " << i;
+      EXPECT_NEAR(J_x[2 * i + 1], 2 * i * x[0] * x[1], kTolerance)
+          << "i: " << i;
     }
   }
 }
diff --git a/internal/ceres/block_jacobi_preconditioner.cc b/internal/ceres/block_jacobi_preconditioner.cc
index 5785e5d..1d5f9d7 100644
--- a/internal/ceres/block_jacobi_preconditioner.cc
+++ b/internal/ceres/block_jacobi_preconditioner.cc
@@ -40,7 +40,8 @@
 namespace ceres {
 namespace internal {
 
-BlockJacobiPreconditioner::BlockJacobiPreconditioner(const BlockSparseMatrixBase& A)
+BlockJacobiPreconditioner::BlockJacobiPreconditioner(
+    const BlockSparseMatrixBase& A)
     : num_rows_(A.num_rows()),
       block_structure_(*A.block_structure()) {
   // Calculate the amount of storage needed.
@@ -65,7 +66,8 @@
 
 BlockJacobiPreconditioner::~BlockJacobiPreconditioner() {}
 
-bool BlockJacobiPreconditioner::Update(const BlockSparseMatrixBase& A, const double* D) {
+bool BlockJacobiPreconditioner::Update(const BlockSparseMatrixBase& A,
+                                       const double* D) {
   const CompressedRowBlockStructure* bs = A.block_structure();
 
   // Compute the diagonal blocks by block inner products.
@@ -104,7 +106,8 @@
     MatrixRef block(blocks_[c], size, size);
 
     if (D != NULL) {
-      block.diagonal() += ConstVectorRef(D + position, size).array().square().matrix();
+      block.diagonal() +=
+          ConstVectorRef(D + position, size).array().square().matrix();
     }
 
     block = block.selfadjointView<Eigen::Upper>()
@@ -114,7 +117,8 @@
   return true;
 }
 
-void BlockJacobiPreconditioner::RightMultiply(const double* x, double* y) const {
+void BlockJacobiPreconditioner::RightMultiply(const double* x,
+                                              double* y) const {
   for (int c = 0; c < block_structure_.cols.size(); ++c) {
     const int size = block_structure_.cols[c].size;
     const int position = block_structure_.cols[c].position;
diff --git a/internal/ceres/canonical_views_clustering.h b/internal/ceres/canonical_views_clustering.h
index 171ac55..5f8e4e3 100644
--- a/internal/ceres/canonical_views_clustering.h
+++ b/internal/ceres/canonical_views_clustering.h
@@ -43,11 +43,11 @@
 
 #include <vector>
 
-#include <glog/logging.h>
 #include "ceres/collections_port.h"
 #include "ceres/graph.h"
-#include "ceres/map_util.h"
 #include "ceres/internal/macros.h"
+#include "ceres/map_util.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/internal/ceres/cgnr_solver.h b/internal/ceres/cgnr_solver.h
index f61c8d1..d560a9d 100644
--- a/internal/ceres/cgnr_solver.h
+++ b/internal/ceres/cgnr_solver.h
@@ -51,10 +51,11 @@
 class CgnrSolver : public BlockSparseMatrixBaseSolver {
  public:
   explicit CgnrSolver(const LinearSolver::Options& options);
-  virtual Summary SolveImpl(BlockSparseMatrixBase* A,
-                            const double* b,
-                            const LinearSolver::PerSolveOptions& per_solve_options,
-                            double* x);
+  virtual Summary SolveImpl(
+      BlockSparseMatrixBase* A,
+      const double* b,
+      const LinearSolver::PerSolveOptions& per_solve_options,
+      double* x);
 
  private:
   const LinearSolver::Options options_;
diff --git a/internal/ceres/compressed_row_jacobian_writer.cc b/internal/ceres/compressed_row_jacobian_writer.cc
index 912c484..bbadb77 100644
--- a/internal/ceres/compressed_row_jacobian_writer.cc
+++ b/internal/ceres/compressed_row_jacobian_writer.cc
@@ -135,7 +135,8 @@
   // Populate the row and column block vectors for use by block
   // oriented ordering algorithms. This is useful when
   // Solver::Options::use_block_amd = true.
-  const vector<ParameterBlock*>& parameter_blocks = program_->parameter_blocks();
+  const vector<ParameterBlock*>& parameter_blocks =
+      program_->parameter_blocks();
   vector<int>& col_blocks = *(jacobian->mutable_col_blocks());
   col_blocks.resize(parameter_blocks.size());
   for (int i = 0; i <  parameter_blocks.size(); ++i) {
diff --git a/internal/ceres/compressed_row_sparse_matrix.h b/internal/ceres/compressed_row_sparse_matrix.h
index 10f96c0..c9c904b 100644
--- a/internal/ceres/compressed_row_sparse_matrix.h
+++ b/internal/ceres/compressed_row_sparse_matrix.h
@@ -32,13 +32,14 @@
 #define CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_
 
 #include <vector>
-#include <glog/logging.h>
-#include "ceres/sparse_matrix.h"
-#include "ceres/triplet_sparse_matrix.h"
+
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/macros.h"
 #include "ceres/internal/port.h"
+#include "ceres/sparse_matrix.h"
+#include "ceres/triplet_sparse_matrix.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 
diff --git a/internal/ceres/coordinate_descent_minimizer.cc b/internal/ceres/coordinate_descent_minimizer.cc
index 5ce110c..c4da987 100644
--- a/internal/ceres/coordinate_descent_minimizer.cc
+++ b/internal/ceres/coordinate_descent_minimizer.cc
@@ -129,7 +129,8 @@
     parameter_block->SetConstant();
   }
 
-  scoped_array<LinearSolver*> linear_solvers(new LinearSolver*[options.num_threads]);
+  scoped_array<LinearSolver*> linear_solvers(
+      new LinearSolver*[options.num_threads]);
 
   LinearSolver::Options linear_solver_options;
   linear_solver_options.type = DENSE_QR;
diff --git a/internal/ceres/coordinate_descent_minimizer.h b/internal/ceres/coordinate_descent_minimizer.h
index fb96b3c..3dcf8fa 100644
--- a/internal/ceres/coordinate_descent_minimizer.h
+++ b/internal/ceres/coordinate_descent_minimizer.h
@@ -31,6 +31,8 @@
 #ifndef CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_
 #define CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_
 
+#include <vector>
+
 #include "ceres/evaluator.h"
 #include "ceres/minimizer.h"
 #include "ceres/problem_impl.h"
diff --git a/internal/ceres/cost_function_to_functor_test.cc b/internal/ceres/cost_function_to_functor_test.cc
index 8ee02bd..90ccc82 100644
--- a/internal/ceres/cost_function_to_functor_test.cc
+++ b/internal/ceres/cost_function_to_functor_test.cc
@@ -1,3 +1,33 @@
+// 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 "ceres/cost_function_to_functor.h"
 #include "ceres/autodiff_cost_function.h"
 #include "gtest/gtest.h"
@@ -9,11 +39,15 @@
 
 void ExpectCostFunctionsAreEqual(const CostFunction& cost_function,
                                  const CostFunction& actual_cost_function) {
-  EXPECT_EQ(cost_function.num_residuals(), actual_cost_function.num_residuals());
+  EXPECT_EQ(cost_function.num_residuals(),
+            actual_cost_function.num_residuals());
   const int num_residuals = cost_function.num_residuals();
-  const vector<int16>& parameter_block_sizes = cost_function.parameter_block_sizes();
-  const vector<int16>& actual_parameter_block_sizes  = actual_cost_function.parameter_block_sizes();
-  EXPECT_EQ(parameter_block_sizes.size(), actual_parameter_block_sizes.size());
+  const vector<int16>& parameter_block_sizes =
+      cost_function.parameter_block_sizes();
+  const vector<int16>& actual_parameter_block_sizes =
+      actual_cost_function.parameter_block_sizes();
+  EXPECT_EQ(parameter_block_sizes.size(),
+            actual_parameter_block_sizes.size());
 
   int num_parameters = 0;
   for (int i = 0; i < parameter_block_sizes.size(); ++i) {
@@ -30,22 +64,29 @@
   scoped_array<double> jacobians(new double[num_parameters * num_residuals]);
 
   scoped_array<double> actual_residuals(new double[num_residuals]);
-  scoped_array<double> actual_jacobians(new double[num_parameters * num_residuals]);
+  scoped_array<double> actual_jacobians
+      (new double[num_parameters * num_residuals]);
 
-  scoped_array<double*> parameter_blocks(new double*[parameter_block_sizes.size()]);
-  scoped_array<double*> jacobian_blocks(new double*[parameter_block_sizes.size()]);
-  scoped_array<double*> actual_jacobian_blocks(new double*[parameter_block_sizes.size()]);
+  scoped_array<double*> parameter_blocks(
+      new double*[parameter_block_sizes.size()]);
+  scoped_array<double*> jacobian_blocks(
+      new double*[parameter_block_sizes.size()]);
+  scoped_array<double*> actual_jacobian_blocks(
+      new double*[parameter_block_sizes.size()]);
 
   num_parameters = 0;
   for (int i = 0; i < parameter_block_sizes.size(); ++i) {
     parameter_blocks[i] = parameters.get() + num_parameters;
     jacobian_blocks[i] = jacobians.get() + num_parameters * num_residuals;
-    actual_jacobian_blocks[i] = actual_jacobians.get() + num_parameters * num_residuals;
+    actual_jacobian_blocks[i] =
+        actual_jacobians.get() + num_parameters * num_residuals;
     num_parameters += parameter_block_sizes[i];
   }
 
-  EXPECT_TRUE(cost_function.Evaluate(parameter_blocks.get(), residuals.get(), NULL));
-  EXPECT_TRUE(actual_cost_function.Evaluate(parameter_blocks.get(), actual_residuals.get(), NULL));
+  EXPECT_TRUE(cost_function.Evaluate(parameter_blocks.get(),
+                                     residuals.get(), NULL));
+  EXPECT_TRUE(actual_cost_function.Evaluate(parameter_blocks.get(),
+                                            actual_residuals.get(), NULL));
   for (int i = 0; i < num_residuals; ++i) {
     EXPECT_NEAR(residuals[i], actual_residuals[i], kTolerance)
         << "residual id: " << i;
@@ -65,7 +106,8 @@
 
   for (int i = 0; i < num_residuals * num_parameters; ++i) {
     EXPECT_NEAR(jacobians[i], actual_jacobians[i], kTolerance)
-        << "jacobian : " << i << " " << jacobians[i] << " " << actual_jacobians[i];
+        << "jacobian : " << i << " "
+        << jacobians[i] << " " << actual_jacobians[i];
   }
 };
 
@@ -200,7 +242,7 @@
 };
 
 #define TEST_BODY(NAME)                                                 \
-  TEST(CostFunctionToFunctor, NAME){                                    \
+  TEST(CostFunctionToFunctor, NAME) {                                   \
     scoped_ptr<CostFunction> cost_function(                             \
         new AutoDiffCostFunction<                                       \
             CostFunctionToFunctor<2, PARAMETER_BLOCK_SIZES >,           \
diff --git a/internal/ceres/dense_qr_solver.cc b/internal/ceres/dense_qr_solver.cc
index 21b6b15..1fb9709 100644
--- a/internal/ceres/dense_qr_solver.cc
+++ b/internal/ceres/dense_qr_solver.cc
@@ -63,7 +63,8 @@
   }
 
   // rhs = [b;0] to account for the additional rows in the lhs.
-  const int augmented_num_rows = num_rows + ((per_solve_options.D != NULL) ? num_cols : 0);
+  const int augmented_num_rows =
+      num_rows + ((per_solve_options.D != NULL) ? num_cols : 0);
   if (rhs_.rows() != augmented_num_rows) {
     rhs_.resize(augmented_num_rows);
     rhs_.setZero();
diff --git a/internal/ceres/dense_sparse_matrix.cc b/internal/ceres/dense_sparse_matrix.cc
index e18a507..978ac6a 100644
--- a/internal/ceres/dense_sparse_matrix.cc
+++ b/internal/ceres/dense_sparse_matrix.cc
@@ -47,7 +47,9 @@
   m_.setZero();
 }
 
-DenseSparseMatrix::DenseSparseMatrix(int num_rows, int num_cols, bool reserve_diagonal)
+DenseSparseMatrix::DenseSparseMatrix(int num_rows,
+                                     int num_cols,
+                                     bool reserve_diagonal)
     : has_diagonal_appended_(false),
       has_diagonal_reserved_(reserve_diagonal) {
   // Allocate enough space for the diagonal.
diff --git a/internal/ceres/dogleg_strategy.cc b/internal/ceres/dogleg_strategy.cc
index da861fe..a330ad2 100644
--- a/internal/ceres/dogleg_strategy.cc
+++ b/internal/ceres/dogleg_strategy.cc
@@ -87,7 +87,7 @@
     // Gauss-Newton and gradient vectors are always available, only a
     // new interpolant need to be computed. For the subspace case,
     // the subspace and the two-dimensional model are also still valid.
-    switch(dogleg_type_) {
+    switch (dogleg_type_) {
       case TRADITIONAL_DOGLEG:
         ComputeTraditionalDoglegStep(step);
         break;
@@ -135,7 +135,7 @@
   summary.termination_type = linear_solver_summary.termination_type;
 
   if (linear_solver_summary.termination_type != FAILURE) {
-    switch(dogleg_type_) {
+    switch (dogleg_type_) {
       // Interpolate the Cauchy point and the Gauss-Newton step.
       case TRADITIONAL_DOGLEG:
         ComputeTraditionalDoglegStep(step);
@@ -415,15 +415,15 @@
   const double trB = subspace_B_.trace();
   const double r2 = radius_ * radius_;
   Matrix2d B_adj;
-  B_adj <<  subspace_B_(1,1) , -subspace_B_(0,1),
-            -subspace_B_(1,0) ,  subspace_B_(0,0);
+  B_adj <<  subspace_B_(1, 1) , -subspace_B_(0, 1),
+            -subspace_B_(1, 0) ,  subspace_B_(0, 0);
 
   Vector polynomial(5);
   polynomial(0) = r2;
   polynomial(1) = 2.0 * r2 * trB;
-  polynomial(2) = r2 * ( trB * trB + 2.0 * detB ) - subspace_g_.squaredNorm();
-  polynomial(3) = -2.0 * ( subspace_g_.transpose() * B_adj * subspace_g_
-      - r2 * detB * trB );
+  polynomial(2) = r2 * (trB * trB + 2.0 * detB) - subspace_g_.squaredNorm();
+  polynomial(3) = -2.0 * (subspace_g_.transpose() * B_adj * subspace_g_
+      - r2 * detB * trB);
   polynomial(4) = r2 * detB * detB - (B_adj * subspace_g_).squaredNorm();
 
   return polynomial;
@@ -598,7 +598,7 @@
   // Reduce the regularization multiplier, in the hope that whatever
   // was causing the rank deficiency has gone away and we can return
   // to doing a pure Gauss-Newton solve.
-  mu_ = max(min_mu_, 2.0 * mu_ / mu_increase_factor_ );
+  mu_ = max(min_mu_, 2.0 * mu_ / mu_increase_factor_);
   reuse_ = false;
 }
 
diff --git a/internal/ceres/dogleg_strategy.h b/internal/ceres/dogleg_strategy.h
index bff1689..7131467 100644
--- a/internal/ceres/dogleg_strategy.h
+++ b/internal/ceres/dogleg_strategy.h
@@ -53,8 +53,8 @@
 // This finds the exact optimum over the two-dimensional subspace
 // spanned by the two Dogleg vectors.
 class DoglegStrategy : public TrustRegionStrategy {
-public:
-  DoglegStrategy(const TrustRegionStrategy::Options& options);
+ public:
+  explicit DoglegStrategy(const TrustRegionStrategy::Options& options);
   virtual ~DoglegStrategy() {}
 
   // TrustRegionStrategy interface
diff --git a/internal/ceres/dogleg_strategy_test.cc b/internal/ceres/dogleg_strategy_test.cc
index 24c526e..caa397e 100644
--- a/internal/ceres/dogleg_strategy_test.cc
+++ b/internal/ceres/dogleg_strategy_test.cc
@@ -129,9 +129,9 @@
   scoped_ptr<LinearSolver> linear_solver(
       new DenseQRSolver(LinearSolver::Options()));
   options_.linear_solver = linear_solver.get();
-  // The global minimum is at (1, 1, ..., 1), so the distance to it is sqrt(6.0).
-  // By restricting the trust region to a radius of 2.0, we test if the trust
-  // region is actually obeyed.
+  // The global minimum is at (1, 1, ..., 1), so the distance to it is
+  // sqrt(6.0).  By restricting the trust region to a radius of 2.0,
+  // we test if the trust region is actually obeyed.
   options_.dogleg_type = TRADITIONAL_DOGLEG;
   options_.initial_radius = 2.0;
   options_.max_radius = 2.0;
diff --git a/internal/ceres/evaluator.h b/internal/ceres/evaluator.h
index 76cf1e0..14a8818 100644
--- a/internal/ceres/evaluator.h
+++ b/internal/ceres/evaluator.h
@@ -32,6 +32,7 @@
 #ifndef CERES_INTERNAL_EVALUATOR_H_
 #define CERES_INTERNAL_EVALUATOR_H_
 
+#include <map>
 #include <string>
 #include <vector>
 
diff --git a/internal/ceres/evaluator_test.cc b/internal/ceres/evaluator_test.cc
index a4e7b25..9e9d31b 100644
--- a/internal/ceres/evaluator_test.cc
+++ b/internal/ceres/evaluator_test.cc
@@ -833,7 +833,11 @@
                          (i & 4) ? expected.jacobian  : NULL);
     }
 
-
+    // The Evaluate call should only depend on the parameter block
+    // values in the user provided pointers, and the current state of
+    // the parameter block should not matter. So, create a new
+    // parameters vector, and update the parameter block states with
+    // it. The results from the Evaluate call should not change.
     double new_parameters[6];
     for (int i = 0; i < 6; ++i) {
       new_parameters[i] = 0.0;
diff --git a/internal/ceres/execution_summary.h b/internal/ceres/execution_summary.h
index 2eb3c1a..29bdc69 100644
--- a/internal/ceres/execution_summary.h
+++ b/internal/ceres/execution_summary.h
@@ -56,8 +56,8 @@
     calls_[name] += 1;
   }
 
-  const map<string, double>& times() const { return times_; };
-  const map<string, int>& calls() const { return calls_; };
+  const map<string, double>& times() const { return times_; }
+  const map<string, int>& calls() const { return calls_; }
 
  private:
   Mutex times_mutex_;
diff --git a/internal/ceres/gradient_checker_test.cc b/internal/ceres/gradient_checker_test.cc
index cf7ee20..fa0d841 100644
--- a/internal/ceres/gradient_checker_test.cc
+++ b/internal/ceres/gradient_checker_test.cc
@@ -34,11 +34,11 @@
 
 #include <cmath>
 #include <cstdlib>
-#include <glog/logging.h>
 #include <vector>
 
 #include "ceres/cost_function.h"
 #include "ceres/random.h"
+#include "glog/logging.h"
 #include "gtest/gtest.h"
 
 namespace ceres {
diff --git a/internal/ceres/graph.h b/internal/ceres/graph.h
index e080489..5f92d4d 100644
--- a/internal/ceres/graph.h
+++ b/internal/ceres/graph.h
@@ -32,12 +32,13 @@
 #define CERES_INTERNAL_GRAPH_H_
 
 #include <limits>
-#include <glog/logging.h>
+#include <utility>
 #include "ceres/integral_types.h"
 #include "ceres/map_util.h"
 #include "ceres/collections_port.h"
 #include "ceres/internal/macros.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/internal/ceres/graph_algorithms.h b/internal/ceres/graph_algorithms.h
index 3b42d93..2e6eec0 100644
--- a/internal/ceres/graph_algorithms.h
+++ b/internal/ceres/graph_algorithms.h
@@ -33,10 +33,12 @@
 #ifndef CERES_INTERNAL_GRAPH_ALGORITHMS_H_
 #define CERES_INTERNAL_GRAPH_ALGORITHMS_H_
 
+#include <algorithm>
 #include <vector>
-#include <glog/logging.h>
+#include <utility>
 #include "ceres/collections_port.h"
 #include "ceres/graph.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/internal/ceres/graph_algorithms_test.cc b/internal/ceres/graph_algorithms_test.cc
index d5d4843..78a0452 100644
--- a/internal/ceres/graph_algorithms_test.cc
+++ b/internal/ceres/graph_algorithms_test.cc
@@ -181,7 +181,7 @@
   VertexDegreeLessThan<int> less_than(graph);
 
   for (int i = 0; i < 4; ++i) {
-    EXPECT_FALSE(less_than(i,i)) << "Failing vertex: " << i;
+    EXPECT_FALSE(less_than(i, i)) << "Failing vertex: " << i;
     for (int j = 0; j < 4; ++j) {
       if (i != j) {
         EXPECT_TRUE(less_than(i, j) ^ less_than(j, i))
diff --git a/internal/ceres/iterative_schur_complement_solver.cc b/internal/ceres/iterative_schur_complement_solver.cc
index d352d02..cf5562a 100644
--- a/internal/ceres/iterative_schur_complement_solver.cc
+++ b/internal/ceres/iterative_schur_complement_solver.cc
@@ -117,14 +117,16 @@
     case SCHUR_JACOBI:
       if (preconditioner_.get() == NULL) {
         preconditioner_.reset(
-            new SchurJacobiPreconditioner(*A->block_structure(), preconditioner_options));
+            new SchurJacobiPreconditioner(
+                *A->block_structure(), preconditioner_options));
       }
       break;
     case CLUSTER_JACOBI:
     case CLUSTER_TRIDIAGONAL:
       if (preconditioner_.get() == NULL) {
         preconditioner_.reset(
-            new VisibilityBasedPreconditioner(*A->block_structure(), preconditioner_options));
+            new VisibilityBasedPreconditioner(
+                *A->block_structure(), preconditioner_options));
       }
       break;
     default:
diff --git a/internal/ceres/levenberg_marquardt_strategy.h b/internal/ceres/levenberg_marquardt_strategy.h
index 90c2178..344e328 100644
--- a/internal/ceres/levenberg_marquardt_strategy.h
+++ b/internal/ceres/levenberg_marquardt_strategy.h
@@ -43,8 +43,9 @@
 //
 // http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf
 class LevenbergMarquardtStrategy : public TrustRegionStrategy {
-public:
-  LevenbergMarquardtStrategy(const TrustRegionStrategy::Options& options);
+ public:
+  explicit LevenbergMarquardtStrategy(
+      const TrustRegionStrategy::Options& options);
   virtual ~LevenbergMarquardtStrategy();
 
   // TrustRegionStrategy interface
diff --git a/internal/ceres/levenberg_marquardt_strategy_test.cc b/internal/ceres/levenberg_marquardt_strategy_test.cc
index 0ce44c4..a5ce6a0 100644
--- a/internal/ceres/levenberg_marquardt_strategy_test.cc
+++ b/internal/ceres/levenberg_marquardt_strategy_test.cc
@@ -58,7 +58,7 @@
         diagonal_(diagonal) {
   }
 
-  virtual ~RegularizationCheckingLinearSolver(){}
+  virtual ~RegularizationCheckingLinearSolver() {}
 
  private:
   virtual LinearSolver::Summary SolveImpl(
@@ -111,12 +111,12 @@
 }
 
 TEST(LevenbergMarquardtStrategy, CorrectDiagonalToLinearSolver) {
-  Matrix jacobian(2,3);
+  Matrix jacobian(2, 3);
   jacobian.setZero();
-  jacobian(0,0) = 0.0;
-  jacobian(0,1) = 1.0;
-  jacobian(1,1) = 1.0;
-  jacobian(0,2) = 100.0;
+  jacobian(0, 0) = 0.0;
+  jacobian(0, 1) = 1.0;
+  jacobian(1, 1) = 1.0;
+  jacobian(0, 2) = 100.0;
 
   double residual = 1.0;
   double x[3];
@@ -148,7 +148,8 @@
     EXPECT_CALL(log, Log(WARNING, _,
                          HasSubstr("Failed to compute a finite step.")));
 
-    TrustRegionStrategy::Summary summary = lms.ComputeStep(pso, &dsm, &residual, x);
+    TrustRegionStrategy::Summary summary =
+        lms.ComputeStep(pso, &dsm, &residual, x);
     EXPECT_EQ(summary.termination_type, FAILURE);
   }
 }
diff --git a/internal/ceres/line_search_direction.cc b/internal/ceres/line_search_direction.cc
index f441607..2f27a78 100644
--- a/internal/ceres/line_search_direction.cc
+++ b/internal/ceres/line_search_direction.cc
@@ -80,7 +80,8 @@
     }
 
     *search_direction =  -current.gradient + beta * previous.search_direction;
-    const double directional_derivative = current. gradient.dot(*search_direction);
+    const double directional_derivative =
+        current. gradient.dot(*search_direction);
     if (directional_derivative > -function_tolerance_) {
       LOG(WARNING) << "Restarting non-linear conjugate gradients: "
                    << directional_derivative;
@@ -120,7 +121,7 @@
 };
 
 LineSearchDirection*
-LineSearchDirection::Create(LineSearchDirection::Options& options) {
+LineSearchDirection::Create(const LineSearchDirection::Options& options) {
   if (options.type == STEEPEST_DESCENT) {
     return new SteepestDescent;
   }
diff --git a/internal/ceres/line_search_direction.h b/internal/ceres/line_search_direction.h
index d92c362..71063ab 100644
--- a/internal/ceres/line_search_direction.h
+++ b/internal/ceres/line_search_direction.h
@@ -56,16 +56,15 @@
     int max_lbfgs_rank;
   };
 
-  static LineSearchDirection* Create(Options& options);
+  static LineSearchDirection* Create(const Options& options);
 
   virtual ~LineSearchDirection() {}
   virtual bool NextDirection(const LineSearchMinimizer::State& previous,
                              const LineSearchMinimizer::State& current,
                              Vector* search_direction) = 0;
-
 };
 
 }  // namespace internal
 }  // namespace ceres
 
-#endif // CERES_INTERNAL_LINE_SEARCH_DIRECTION_H_
+#endif  // CERES_INTERNAL_LINE_SEARCH_DIRECTION_H_
diff --git a/internal/ceres/linear_least_squares_problems.cc b/internal/ceres/linear_least_squares_problems.cc
index 3e3bcd0..bc6ff00 100644
--- a/internal/ceres/linear_least_squares_problems.cc
+++ b/internal/ceres/linear_least_squares_problems.cc
@@ -734,7 +734,7 @@
 }
 
 bool DumpLinearLeastSquaresProblem(const string& directory,
-                              	   int iteration,
+                                   int iteration,
                                    DumpFormatType dump_format_type,
                                    const SparseMatrix* A,
                                    const double* D,
@@ -742,18 +742,18 @@
                                    const double* x,
                                    int num_eliminate_blocks) {
   switch (dump_format_type) {
-    case (CONSOLE):
+    case CONSOLE:
       return DumpLinearLeastSquaresProblemToConsole(directory,
                                                     iteration,
                                                     A, D, b, x,
                                                     num_eliminate_blocks);
-    case (PROTOBUF):
+    case PROTOBUF:
       return DumpLinearLeastSquaresProblemToProtocolBuffer(
           directory,
           iteration,
           A, D, b, x,
           num_eliminate_blocks);
-    case (TEXTFILE):
+    case TEXTFILE:
       return DumpLinearLeastSquaresProblemToTextFile(directory,
                                                      iteration,
                                                      A, D, b, x,
diff --git a/internal/ceres/linear_least_squares_problems.h b/internal/ceres/linear_least_squares_problems.h
index 553cc0d..c76ae91 100644
--- a/internal/ceres/linear_least_squares_problems.h
+++ b/internal/ceres/linear_least_squares_problems.h
@@ -74,7 +74,7 @@
 // Write the linear least squares problem to disk. The exact format
 // depends on dump_format_type.
 bool DumpLinearLeastSquaresProblem(const string& directory,
-                              	   int iteration,
+                                   int iteration,
                                    DumpFormatType dump_format_type,
                                    const SparseMatrix* A,
                                    const double* D,
diff --git a/internal/ceres/linear_solver.h b/internal/ceres/linear_solver.h
index 219939e..a980514 100644
--- a/internal/ceres/linear_solver.h
+++ b/internal/ceres/linear_solver.h
@@ -35,17 +35,16 @@
 #define CERES_INTERNAL_LINEAR_SOLVER_H_
 
 #include <cstddef>
+#include <map>
 #include <vector>
-
-#include <glog/logging.h>
 #include "ceres/block_sparse_matrix.h"
 #include "ceres/casts.h"
 #include "ceres/compressed_row_sparse_matrix.h"
 #include "ceres/dense_sparse_matrix.h"
 #include "ceres/execution_summary.h"
-#include "ceres/execution_summary.h"
 #include "ceres/triplet_sparse_matrix.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/internal/ceres/low_rank_inverse_hessian.h b/internal/ceres/low_rank_inverse_hessian.h
index 5d59c14..6f3fc0c 100644
--- a/internal/ceres/low_rank_inverse_hessian.h
+++ b/internal/ceres/low_rank_inverse_hessian.h
@@ -78,7 +78,7 @@
   // LinearOperator interface
   virtual void RightMultiply(const double* x, double* y) const;
   virtual void LeftMultiply(const double* x, double* y) const {
-    RightMultiply(x,y);
+    RightMultiply(x, y);
   }
   virtual int num_rows() const { return num_parameters_; }
   virtual int num_cols() const { return num_parameters_; }
diff --git a/internal/ceres/map_util.h b/internal/ceres/map_util.h
index ddf1252..929c6b3 100644
--- a/internal/ceres/map_util.h
+++ b/internal/ceres/map_util.h
@@ -35,6 +35,7 @@
 
 #include <utility>
 #include "ceres/internal/port.h"
+#include "glog/logging.h"
 
 namespace ceres {
 
diff --git a/internal/ceres/minimizer.cc b/internal/ceres/minimizer.cc
index 912ac99..2e2c15a 100644
--- a/internal/ceres/minimizer.cc
+++ b/internal/ceres/minimizer.cc
@@ -35,7 +35,7 @@
 namespace ceres {
 namespace internal {
 
-Minimizer::~Minimizer() {};
+Minimizer::~Minimizer() {}
 
 bool Minimizer::RunCallbacks(const vector<IterationCallback*> callbacks,
                              const IterationSummary& iteration_summary,
diff --git a/internal/ceres/numeric_diff_functor_test.cc b/internal/ceres/numeric_diff_functor_test.cc
index a37ceaf..acd7ff9 100644
--- a/internal/ceres/numeric_diff_functor_test.cc
+++ b/internal/ceres/numeric_diff_functor_test.cc
@@ -46,7 +46,8 @@
 namespace internal {
 
 TEST(NumericDiffCostFunction, EasyCaseCentralDifferences) {
-  typedef NumericDiffFunctor<EasyFunctor, CENTRAL, 3, 5, 5> NumericDiffEasyFunctor;
+  typedef NumericDiffFunctor<EasyFunctor, CENTRAL, 3, 5, 5>
+      NumericDiffEasyFunctor;
 
   internal::scoped_ptr<CostFunction> cost_function;
   EasyFunctor functor;
@@ -64,7 +65,8 @@
 }
 
 TEST(NumericDiffCostFunction, EasyCaseForwardDifferences) {
-  typedef NumericDiffFunctor<EasyFunctor, FORWARD, 3, 5, 5> NumericDiffEasyFunctor;
+  typedef NumericDiffFunctor<EasyFunctor, FORWARD, 3, 5, 5>
+      NumericDiffEasyFunctor;
 
   internal::scoped_ptr<CostFunction> cost_function;
   EasyFunctor functor;
diff --git a/internal/ceres/numeric_diff_test_utils.cc b/internal/ceres/numeric_diff_test_utils.cc
index 6786ac9..3572afa 100644
--- a/internal/ceres/numeric_diff_test_utils.cc
+++ b/internal/ceres/numeric_diff_test_utils.cc
@@ -1,3 +1,33 @@
+// 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 "ceres/numeric_diff_test_utils.h"
 
 #include <algorithm>
diff --git a/internal/ceres/numeric_diff_test_utils.h b/internal/ceres/numeric_diff_test_utils.h
index 1a43df2..dd5f21e 100644
--- a/internal/ceres/numeric_diff_test_utils.h
+++ b/internal/ceres/numeric_diff_test_utils.h
@@ -1,3 +1,36 @@
+// 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)
+
+#ifndef CERES_INTERNAL_NUMERIC_DIFF_TEST_UTILS_H_
+#define CERES_INTERNAL_NUMERIC_DIFF_TEST_UTILS_H_
+
 #include "ceres/cost_function.h"
 #include "ceres/sized_cost_function.h"
 #include "ceres/types.h"
@@ -54,3 +87,5 @@
 
 }  // namespace internal
 }  // namespace ceres
+
+#endif  // CERES_INTERNAL_NUMERIC_DIFF_TEST_UTILS_H_
diff --git a/internal/ceres/polynomial_test.cc b/internal/ceres/polynomial_test.cc
index 7c992fa..3339973 100644
--- a/internal/ceres/polynomial_test.cc
+++ b/internal/ceres/polynomial_test.cc
@@ -342,8 +342,8 @@
 
 TEST(Polynomial, QuadraticInterpolatingPolynomial) {
   // p(x) = 2x^2 + 3x + 2
-   Vector true_polynomial(3);
-   true_polynomial << 2.0, 3.0, 2.0;
+  Vector true_polynomial(3);
+  true_polynomial << 2.0, 3.0, 2.0;
 
   vector<FunctionSample> samples;
   {
@@ -401,10 +401,10 @@
 
 TEST(Polynomial, CubicInterpolatingPolynomialFromValues) {
   // p(x) = x^3 + 2x^2 + 3x + 2
- Vector true_polynomial(4);
- true_polynomial << 1.0, 2.0, 3.0, 2.0;
+  Vector true_polynomial(4);
+  true_polynomial << 1.0, 2.0, 3.0, 2.0;
 
- vector<FunctionSample> samples;
+  vector<FunctionSample> samples;
   {
     FunctionSample sample;
     sample.x = 1.0;
@@ -443,11 +443,11 @@
 
 TEST(Polynomial, CubicInterpolatingPolynomialFromValuesAndOneGradient) {
   // p(x) = x^3 + 2x^2 + 3x + 2
- Vector true_polynomial(4);
- true_polynomial << 1.0, 2.0, 3.0, 2.0;
- Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);
+  Vector true_polynomial(4);
+  true_polynomial << 1.0, 2.0, 3.0, 2.0;
+  Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);
 
- vector<FunctionSample> samples;
+  vector<FunctionSample> samples;
   {
     FunctionSample sample;
     sample.x = 1.0;
@@ -480,11 +480,11 @@
 
 TEST(Polynomial, CubicInterpolatingPolynomialFromValuesAndGradients) {
   // p(x) = x^3 + 2x^2 + 3x + 2
- Vector true_polynomial(4);
- true_polynomial << 1.0, 2.0, 3.0, 2.0;
- Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);
+  Vector true_polynomial(4);
+  true_polynomial << 1.0, 2.0, 3.0, 2.0;
+  Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);
 
- vector<FunctionSample> samples;
+  vector<FunctionSample> samples;
   {
     FunctionSample sample;
     sample.x = -3.0;
diff --git a/internal/ceres/problem.cc b/internal/ceres/problem.cc
index c8f4a21..43e7883 100644
--- a/internal/ceres/problem.cc
+++ b/internal/ceres/problem.cc
@@ -32,6 +32,7 @@
 #include "ceres/problem.h"
 
 #include <vector>
+#include "ceres/crs_matrix.h"
 #include "ceres/problem_impl.h"
 
 namespace ceres {
@@ -139,9 +140,10 @@
     LossFunction* loss_function,
     double* x0, double* x1, double* x2, double* x3, double* x4, double* x5,
     double* x6, double* x7, double* x8, double* x9) {
-  return problem_impl_->AddResidualBlock(cost_function,
-                                         loss_function,
-                                         x0, x1, x2, x3, x4, x5, x6, x7, x8, x9);
+  return problem_impl_->AddResidualBlock(
+      cost_function,
+      loss_function,
+      x0, x1, x2, x3, x4, x5, x6, x7, x8, x9);
 }
 
 void Problem::AddParameterBlock(double* values, int size) {
@@ -176,6 +178,18 @@
   problem_impl_->SetParameterization(values, local_parameterization);
 }
 
+bool Problem::Evaluate(const EvaluateOptions& evaluate_options,
+                       double* cost,
+                       vector<double>* residuals,
+                       vector<double>* gradient,
+                       CRSMatrix* jacobian) {
+  return problem_impl_->Evaluate(evaluate_options,
+                                 cost,
+                                 residuals,
+                                 gradient,
+                                 jacobian);
+}
+
 int Problem::NumParameterBlocks() const {
   return problem_impl_->NumParameterBlocks();
 }
diff --git a/internal/ceres/problem_impl.cc b/internal/ceres/problem_impl.cc
index ae4e7ed..bc378aa 100644
--- a/internal/ceres/problem_impl.cc
+++ b/internal/ceres/problem_impl.cc
@@ -37,7 +37,11 @@
 #include <string>
 #include <utility>
 #include <vector>
+#include "ceres/casts.h"
+#include "ceres/compressed_row_sparse_matrix.h"
 #include "ceres/cost_function.h"
+#include "ceres/crs_matrix.h"
+#include "ceres/evaluator.h"
 #include "ceres/loss_function.h"
 #include "ceres/map_util.h"
 #include "ceres/parameter_block.h"
@@ -224,7 +228,7 @@
     if (duplicate_items != sorted_parameter_blocks.end()) {
       string blocks;
       for (int i = 0; i < parameter_blocks.size(); ++i) {
-        blocks += internal::StringPrintf(" %p ", parameter_blocks[i]);
+        blocks += StringPrintf(" %p ", parameter_blocks[i]);
       }
 
       LOG(FATAL) << "Duplicate parameter blocks in a residual parameter "
@@ -513,6 +517,164 @@
       ->SetParameterization(local_parameterization);
 }
 
+bool ProblemImpl::Evaluate(const Problem::EvaluateOptions& evaluate_options,
+                           double* cost,
+                           vector<double>* residuals,
+                           vector<double>* gradient,
+                           CRSMatrix* jacobian) {
+  if (cost == NULL &&
+      residuals == NULL &&
+      gradient == NULL &&
+      jacobian == NULL) {
+    LOG(INFO) << "Nothing to do.";
+    return true;
+  }
+
+  // If the user supplied residual blocks, then use them, otherwise
+  // take the residual blocks from the underlying program.
+  Program program;
+  *program.mutable_residual_blocks() =
+      ((evaluate_options.residual_blocks.size() > 0)
+       ? evaluate_options.residual_blocks : program_->residual_blocks());
+
+  const vector<double*>& parameter_block_ptrs =
+      evaluate_options.parameter_blocks;
+
+  vector<ParameterBlock*> variable_parameter_blocks;
+  vector<ParameterBlock*>& parameter_blocks =
+      *program.mutable_parameter_blocks();
+
+  if (parameter_block_ptrs.size() == 0) {
+    // The user did not provide any parameter blocks, so default to
+    // using all the parameter blocks in the order that they are in
+    // the underlying program object.
+    parameter_blocks = program_->parameter_blocks();
+  } else {
+    // The user supplied a vector of parameter blocks. Using this list
+    // requires a number of steps.
+
+    // 1. Convert double* into ParameterBlock*
+    parameter_blocks.resize(parameter_block_ptrs.size());
+    for (int i = 0; i < parameter_block_ptrs.size(); ++i) {
+      parameter_blocks[i] =
+          FindOrDie(parameter_block_map_, parameter_block_ptrs[i]);
+    }
+
+    // 2. The user may have only supplied a subset of parameter
+    // blocks, so identify the ones that are not supplied by the user
+    // and are NOT constant. These parameter blocks are stored in
+    // variable_parameter_blocks.
+    //
+    // To ensure that the parameter blocks are not included in the
+    // columns of the jacobian, we need to make sure that they are
+    // constant during evaluation and then make them variable again
+    // after we are done.
+    vector<ParameterBlock*> all_parameter_blocks(program_->parameter_blocks());
+    vector<ParameterBlock*> included_parameter_blocks(
+        program.parameter_blocks());
+
+    vector<ParameterBlock*> excluded_parameter_blocks;
+    sort(all_parameter_blocks.begin(), all_parameter_blocks.end());
+    sort(included_parameter_blocks.begin(), included_parameter_blocks.end());
+    set_difference(all_parameter_blocks.begin(),
+                   all_parameter_blocks.end(),
+                   included_parameter_blocks.begin(),
+                   included_parameter_blocks.end(),
+                   back_inserter(excluded_parameter_blocks));
+
+    variable_parameter_blocks.reserve(excluded_parameter_blocks.size());
+    for (int i = 0; i < excluded_parameter_blocks.size(); ++i) {
+      ParameterBlock* parameter_block = excluded_parameter_blocks[i];
+      if (!parameter_block->IsConstant()) {
+        variable_parameter_blocks.push_back(parameter_block);
+        parameter_block->SetConstant();
+      }
+    }
+  }
+
+  // Setup the Parameter indices and offsets before an evaluator can
+  // be constructed and used.
+  program.SetParameterOffsetsAndIndex();
+
+  Evaluator::Options evaluator_options;
+
+  // Even though using SPARSE_NORMAL_CHOLESKY requires SuiteSparse or
+  // CXSparse, here it just being used for telling the evaluator to
+  // use a SparseRowCompressedMatrix for the jacobian. This is because
+  // the Evaluator decides the storage for the Jacobian based on the
+  // type of linear solver being used.
+  evaluator_options.linear_solver_type = SPARSE_NORMAL_CHOLESKY;
+  evaluator_options.num_threads = evaluate_options.num_threads;
+
+  string error;
+  scoped_ptr<Evaluator> evaluator(
+      Evaluator::Create(evaluator_options, &program, &error));
+  if (evaluator.get() == NULL) {
+    LOG(ERROR) << "Unable to create an Evaluator object. "
+               << "Error: " << error
+               << "This is a Ceres bug; please contact the developers!";
+
+    // Make the parameter blocks that were temporarily marked
+    // constant, variable again.
+    for (int i = 0; i < variable_parameter_blocks.size(); ++i) {
+      variable_parameter_blocks[i]->SetVarying();
+    }
+    return false;
+  }
+
+  if (residuals !=NULL) {
+    residuals->resize(evaluator->NumResiduals());
+  }
+
+  if (gradient != NULL) {
+    gradient->resize(evaluator->NumEffectiveParameters());
+  }
+
+  scoped_ptr<CompressedRowSparseMatrix> tmp_jacobian;
+  if (jacobian != NULL) {
+    tmp_jacobian.reset(
+        down_cast<CompressedRowSparseMatrix*>(evaluator->CreateJacobian()));
+  }
+
+  // Point the state pointers to the user state pointers. This is
+  // needed so that we can extract a parameter vector which is then
+  // passed to Evaluator::Evaluate.
+  program.SetParameterBlockStatePtrsToUserStatePtrs();
+
+  // Copy the value of the parameter blocks into a vector, since the
+  // Evaluate::Evaluate method needs its input as such. The previous
+  // call to SetParameterBlockStatePtrsToUserStatePtrs ensures that
+  // these values are the ones corresponding to the actual state of
+  // the parameter blocks, rather than the temporary state pointer
+  // used for evaluation.
+  Vector parameters(program.NumParameters());
+  program.ParameterBlocksToStateVector(parameters.data());
+
+  double tmp_cost = 0;
+  bool status = evaluator->Evaluate(parameters.data(),
+                                    &tmp_cost,
+                                    residuals != NULL ? &(*residuals)[0] : NULL,
+                                    gradient != NULL ? &(*gradient)[0] : NULL,
+                                    tmp_jacobian.get());
+
+  // Make the parameter blocks that were temporarirly marked
+  // constant, variable again.
+  for (int i = 0; i < variable_parameter_blocks.size(); ++i) {
+    variable_parameter_blocks[i]->SetVarying();
+  }
+
+  if (status) {
+    if (cost != NULL) {
+      *cost = tmp_cost;
+    }
+    if (jacobian != NULL) {
+      tmp_jacobian->ToCRSMatrix(jacobian);
+    }
+  }
+
+  return status;
+}
+
 int ProblemImpl::NumParameterBlocks() const {
   return program_->NumParameterBlocks();
 }
diff --git a/internal/ceres/problem_impl.h b/internal/ceres/problem_impl.h
index 536e73a..ccc315d 100644
--- a/internal/ceres/problem_impl.h
+++ b/internal/ceres/problem_impl.h
@@ -53,6 +53,7 @@
 class CostFunction;
 class LossFunction;
 class LocalParameterization;
+struct CRSMatrix;
 
 namespace internal {
 
@@ -126,6 +127,13 @@
   void SetParameterBlockVariable(double* values);
   void SetParameterization(double* values,
                            LocalParameterization* local_parameterization);
+
+  bool Evaluate(const Problem::EvaluateOptions& options,
+                double* cost,
+                vector<double>* residuals,
+                vector<double>* gradient,
+                CRSMatrix* jacobian);
+
   int NumParameterBlocks() const;
   int NumParameters() const;
   int NumResidualBlocks() const;
@@ -139,6 +147,12 @@
  private:
   ParameterBlock* InternalAddParameterBlock(double* values, int size);
 
+  bool InternalEvaluate(Program* program,
+                        double* cost,
+                        vector<double>* residuals,
+                        vector<double>* gradient,
+                        CRSMatrix* jacobian);
+
   // Delete the arguments in question. These differ from the Remove* functions
   // in that they do not clean up references to the block to delete; they
   // merely delete them.
diff --git a/internal/ceres/problem_test.cc b/internal/ceres/problem_test.cc
index 55f355b..130148d 100644
--- a/internal/ceres/problem_test.cc
+++ b/internal/ceres/problem_test.cc
@@ -32,14 +32,20 @@
 #include "ceres/problem.h"
 #include "ceres/problem_impl.h"
 
-#include "gtest/gtest.h"
+#include "ceres/casts.h"
 #include "ceres/cost_function.h"
+#include "ceres/crs_matrix.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/internal/scoped_ptr.h"
 #include "ceres/local_parameterization.h"
 #include "ceres/map_util.h"
 #include "ceres/parameter_block.h"
 #include "ceres/program.h"
 #include "ceres/sized_cost_function.h"
-#include "ceres/internal/scoped_ptr.h"
+#include "ceres/sparse_matrix.h"
+#include "ceres/types.h"
+#include "gtest/gtest.h"
+
 
 namespace ceres {
 namespace internal {
@@ -695,5 +701,541 @@
                         DynamicProblem,
                         ::testing::Values(true, false));
 
+// Test for Problem::Evaluate
+
+// TODO(sameeragarwal): The following struct and function are shared
+// with evaluator_test.cc. Once things settle down, do an
+// evaluate_utils.h or some such thing to reduce code duplication. The
+// best time is perhaps when we remove the support for
+// Solver::Summary::initial_*
+struct ExpectedEvaluation {
+  int num_rows;
+  int num_cols;
+  double cost;
+  const double residuals[50];
+  const double gradient[50];
+  const double jacobian[200];
+};
+
+void CompareEvaluations(int expected_num_rows,
+                        int expected_num_cols,
+                        double expected_cost,
+                        const double* expected_residuals,
+                        const double* expected_gradient,
+                        const double* expected_jacobian,
+                        const double actual_cost,
+                        const double* actual_residuals,
+                        const double* actual_gradient,
+                        const double* actual_jacobian) {
+  EXPECT_EQ(expected_cost, actual_cost);
+
+  if (expected_residuals != NULL) {
+    ConstVectorRef expected_residuals_vector(expected_residuals,
+                                             expected_num_rows);
+    ConstVectorRef actual_residuals_vector(actual_residuals,
+                                           expected_num_rows);
+    EXPECT_TRUE((actual_residuals_vector.array() ==
+                 expected_residuals_vector.array()).all())
+        << "Actual:\n" << actual_residuals_vector
+        << "\nExpected:\n" << expected_residuals_vector;
+  }
+
+  if (expected_gradient != NULL) {
+    ConstVectorRef expected_gradient_vector(expected_gradient,
+                                            expected_num_cols);
+    ConstVectorRef actual_gradient_vector(actual_gradient,
+                                            expected_num_cols);
+
+    EXPECT_TRUE((actual_gradient_vector.array() ==
+                 expected_gradient_vector.array()).all())
+        << "Actual:\n" << actual_gradient_vector.transpose()
+        << "\nExpected:\n" << expected_gradient_vector.transpose();
+  }
+
+  if (expected_jacobian != NULL) {
+    ConstMatrixRef expected_jacobian_matrix(expected_jacobian,
+                                            expected_num_rows,
+                                            expected_num_cols);
+    ConstMatrixRef actual_jacobian_matrix(actual_jacobian,
+                                          expected_num_rows,
+                                          expected_num_cols);
+    EXPECT_TRUE((actual_jacobian_matrix.array() ==
+                 expected_jacobian_matrix.array()).all())
+        << "Actual:\n" << actual_jacobian_matrix
+        << "\nExpected:\n" << expected_jacobian_matrix;
+  }
+}
+
+// Simple cost function used for testing Problem::Evaluate.
+//
+// r_i = i - (j + 1) * x_ij^2
+template <int kNumResiduals, int kNumParameterBlocks >
+class QuadraticCostFunction : public CostFunction {
+ public:
+  QuadraticCostFunction() {
+    CHECK_GT(kNumResiduals, 0);
+    CHECK_GT(kNumParameterBlocks, 0);
+    set_num_residuals(kNumResiduals);
+    for (int i = 0; i < kNumParameterBlocks; ++i) {
+      mutable_parameter_block_sizes()->push_back(kNumResiduals);
+    }
+  }
+
+  virtual bool Evaluate(double const* const* parameters,
+                        double* residuals,
+                        double** jacobians) const {
+    for (int i = 0; i < kNumResiduals; ++i) {
+      residuals[i] = i;
+      for (int j = 0; j < kNumParameterBlocks; ++j) {
+        residuals[i] -= (j + 1.0) * parameters[j][i] * parameters[j][i];
+      }
+    }
+
+    if (jacobians == NULL) {
+      return true;
+    }
+
+    for (int j = 0; j < kNumParameterBlocks; ++j) {
+      if (jacobians[j] != NULL) {
+        MatrixRef(jacobians[j], kNumResiduals, kNumResiduals) =
+            (-2.0 * (j + 1.0) *
+             ConstVectorRef(parameters[j], kNumResiduals)).asDiagonal();
+      }
+    }
+
+    return true;
+  }
+};
+
+// Convert a CRSMatrix to a dense Eigen matrix.
+void CRSToDenseMatrix(const CRSMatrix& input, Matrix* output) {
+  Matrix& m = *CHECK_NOTNULL(output);
+  m.resize(input.num_rows, input.num_cols);
+  m.setZero();
+  for (int row = 0; row < input.num_rows; ++row) {
+    for (int j = input.rows[row]; j < input.rows[row + 1]; ++j) {
+      const int col = input.cols[j];
+      m(row, col) = input.values[j];
+    }
+  }
+}
+
+class ProblemEvaluateTest : public ::testing::Test {
+ protected:
+  void SetUp() {
+    for (int i = 0; i < 6; ++i) {
+      parameters_[i] = static_cast<double>(i + 1);
+    }
+
+    parameter_blocks_.push_back(parameters_);
+    parameter_blocks_.push_back(parameters_ + 2);
+    parameter_blocks_.push_back(parameters_ + 4);
+
+
+    CostFunction* cost_function = new QuadraticCostFunction<2, 2>;
+
+    // f(x, y)
+    residual_blocks_.push_back(
+        problem_.AddResidualBlock(cost_function,
+                                  NULL,
+                                  parameters_,
+                                  parameters_ + 2));
+    // g(y, z)
+    residual_blocks_.push_back(
+        problem_.AddResidualBlock(cost_function,
+                                  NULL, parameters_ + 2,
+                                  parameters_ + 4));
+    // h(z, x)
+    residual_blocks_.push_back(
+        problem_.AddResidualBlock(cost_function,
+                                  NULL,
+                                  parameters_ + 4,
+                                  parameters_));
+  }
+
+
+
+  void EvaluateAndCompare(const Problem::EvaluateOptions& options,
+                          const int expected_num_rows,
+                          const int expected_num_cols,
+                          const double expected_cost,
+                          const double* expected_residuals,
+                          const double* expected_gradient,
+                          const double* expected_jacobian) {
+    double cost;
+    vector<double> residuals;
+    vector<double> gradient;
+    CRSMatrix jacobian;
+
+    EXPECT_TRUE(
+        problem_.Evaluate(options,
+                          &cost,
+                          expected_residuals != NULL ? &residuals : NULL,
+                          expected_gradient != NULL ? &gradient : NULL,
+                          expected_jacobian != NULL ? &jacobian : NULL));
+
+    if (expected_residuals != NULL) {
+      EXPECT_EQ(residuals.size(), expected_num_rows);
+    }
+
+    if (expected_gradient != NULL) {
+      EXPECT_EQ(gradient.size(), expected_num_cols);
+    }
+
+    if (expected_jacobian != NULL) {
+      EXPECT_EQ(jacobian.num_rows, expected_num_rows);
+      EXPECT_EQ(jacobian.num_cols, expected_num_cols);
+    }
+
+    Matrix dense_jacobian;
+    if (expected_jacobian != NULL) {
+      CRSToDenseMatrix(jacobian, &dense_jacobian);
+    }
+
+    CompareEvaluations(expected_num_rows,
+                       expected_num_cols,
+                       expected_cost,
+                       expected_residuals,
+                       expected_gradient,
+                       expected_jacobian,
+                       cost,
+                       residuals.size() > 0 ? &residuals[0] : NULL,
+                       gradient.size() > 0 ? &gradient[0] : NULL,
+                       dense_jacobian.data());
+  }
+
+  void CheckAllEvaluationCombinations(const Problem::EvaluateOptions& options,
+                                      const ExpectedEvaluation& expected) {
+    for (int i = 0; i < 8; ++i) {
+      EvaluateAndCompare(options,
+                         expected.num_rows,
+                         expected.num_cols,
+                         expected.cost,
+                         (i & 1) ? expected.residuals : NULL,
+                         (i & 2) ? expected.gradient  : NULL,
+                         (i & 4) ? expected.jacobian  : NULL);
+    }
+  }
+
+  ProblemImpl problem_;
+  double parameters_[6];
+  vector<double*> parameter_blocks_;
+  vector<ResidualBlockId> residual_blocks_;
+};
+
+
+TEST_F(ProblemEvaluateTest, MultipleParameterAndResidualBlocks) {
+  ExpectedEvaluation expected = {
+    // Rows/columns
+    6, 6,
+    // Cost
+    7607.0,
+    // Residuals
+    { -19.0, -35.0,  // f
+      -59.0, -87.0,  // g
+      -27.0, -43.0   // h
+    },
+    // Gradient
+    {  146.0,  484.0,   // x
+       582.0, 1256.0,   // y
+      1450.0, 2604.0,   // z
+    },
+    // Jacobian
+    //                       x             y             z
+    { /* f(x, y) */ -2.0,  0.0, -12.0,   0.0,   0.0,   0.0,
+                     0.0, -4.0,   0.0, -16.0,   0.0,   0.0,
+      /* g(y, z) */  0.0,  0.0,  -6.0,   0.0, -20.0,   0.0,
+                     0.0,  0.0,   0.0,  -8.0,   0.0, -24.0,
+      /* h(z, x) */ -4.0,  0.0,   0.0,   0.0, -10.0,   0.0,
+                     0.0, -8.0,   0.0,   0.0,   0.0, -12.0
+    }
+  };
+
+  CheckAllEvaluationCombinations(Problem::EvaluateOptions(), expected);
+}
+
+TEST_F(ProblemEvaluateTest, ParameterAndResidualBlocksPassedInOptions) {
+  ExpectedEvaluation expected = {
+    // Rows/columns
+    6, 6,
+    // Cost
+    7607.0,
+    // Residuals
+    { -19.0, -35.0,  // f
+      -59.0, -87.0,  // g
+      -27.0, -43.0   // h
+    },
+    // Gradient
+    {  146.0,  484.0,   // x
+       582.0, 1256.0,   // y
+      1450.0, 2604.0,   // z
+    },
+    // Jacobian
+    //                       x             y             z
+    { /* f(x, y) */ -2.0,  0.0, -12.0,   0.0,   0.0,   0.0,
+                     0.0, -4.0,   0.0, -16.0,   0.0,   0.0,
+      /* g(y, z) */  0.0,  0.0,  -6.0,   0.0, -20.0,   0.0,
+                     0.0,  0.0,   0.0,  -8.0,   0.0, -24.0,
+      /* h(z, x) */ -4.0,  0.0,   0.0,   0.0, -10.0,   0.0,
+                     0.0, -8.0,   0.0,   0.0,   0.0, -12.0
+    }
+  };
+
+  Problem::EvaluateOptions evaluate_options;
+  evaluate_options.parameter_blocks = parameter_blocks_;
+  evaluate_options.residual_blocks = residual_blocks_;
+  CheckAllEvaluationCombinations(evaluate_options, expected);
+}
+
+TEST_F(ProblemEvaluateTest, ReorderedResidualBlocks) {
+  ExpectedEvaluation expected = {
+    // Rows/columns
+    6, 6,
+    // Cost
+    7607.0,
+    // Residuals
+    { -19.0, -35.0,  // f
+      -27.0, -43.0,  // h
+      -59.0, -87.0   // g
+    },
+    // Gradient
+    {  146.0,  484.0,   // x
+       582.0, 1256.0,   // y
+      1450.0, 2604.0,   // z
+    },
+    // Jacobian
+    //                       x             y             z
+    { /* f(x, y) */ -2.0,  0.0, -12.0,   0.0,   0.0,   0.0,
+                     0.0, -4.0,   0.0, -16.0,   0.0,   0.0,
+      /* h(z, x) */ -4.0,  0.0,   0.0,   0.0, -10.0,   0.0,
+                     0.0, -8.0,   0.0,   0.0,   0.0, -12.0,
+      /* g(y, z) */  0.0,  0.0,  -6.0,   0.0, -20.0,   0.0,
+                     0.0,  0.0,   0.0,  -8.0,   0.0, -24.0
+    }
+  };
+
+  Problem::EvaluateOptions evaluate_options;
+  evaluate_options.parameter_blocks = parameter_blocks_;
+
+  // f, h, g
+  evaluate_options.residual_blocks.push_back(residual_blocks_[0]);
+  evaluate_options.residual_blocks.push_back(residual_blocks_[2]);
+  evaluate_options.residual_blocks.push_back(residual_blocks_[1]);
+
+  CheckAllEvaluationCombinations(evaluate_options, expected);
+}
+
+TEST_F(ProblemEvaluateTest, ReorderedResidualBlocksAndReorderedParameterBlocks) {
+  ExpectedEvaluation expected = {
+    // Rows/columns
+    6, 6,
+    // Cost
+    7607.0,
+    // Residuals
+    { -19.0, -35.0,  // f
+      -27.0, -43.0,  // h
+      -59.0, -87.0   // g
+    },
+    // Gradient
+    {  1450.0, 2604.0,   // z
+        582.0, 1256.0,   // y
+        146.0,  484.0,   // x
+    },
+     // Jacobian
+    //                       z             y             x
+    { /* f(x, y) */   0.0,   0.0, -12.0,   0.0,  -2.0,   0.0,
+                      0.0,   0.0,   0.0, -16.0,   0.0,  -4.0,
+      /* h(z, x) */ -10.0,   0.0,   0.0,   0.0,  -4.0,   0.0,
+                      0.0, -12.0,   0.0,   0.0,   0.0,  -8.0,
+      /* g(y, z) */ -20.0,   0.0,  -6.0,   0.0,   0.0,   0.0,
+                      0.0, -24.0,   0.0,  -8.0,   0.0,   0.0
+    }
+  };
+
+  Problem::EvaluateOptions evaluate_options;
+  // z, y, x
+  evaluate_options.parameter_blocks.push_back(parameter_blocks_[2]);
+  evaluate_options.parameter_blocks.push_back(parameter_blocks_[1]);
+  evaluate_options.parameter_blocks.push_back(parameter_blocks_[0]);
+
+  // f, h, g
+  evaluate_options.residual_blocks.push_back(residual_blocks_[0]);
+  evaluate_options.residual_blocks.push_back(residual_blocks_[2]);
+  evaluate_options.residual_blocks.push_back(residual_blocks_[1]);
+
+  CheckAllEvaluationCombinations(evaluate_options, expected);
+}
+
+TEST_F(ProblemEvaluateTest, ConstantParameterBlock) {
+  ExpectedEvaluation expected = {
+    // Rows/columns
+    6, 6,
+    // Cost
+    7607.0,
+    // Residuals
+    { -19.0, -35.0,  // f
+      -59.0, -87.0,  // g
+      -27.0, -43.0   // h
+    },
+
+    // Gradient
+    {  146.0,  484.0,  // x
+         0.0,    0.0,  // y
+      1450.0, 2604.0,  // z
+    },
+
+    // Jacobian
+    //                       x             y             z
+    { /* f(x, y) */ -2.0,  0.0,   0.0,   0.0,   0.0,   0.0,
+                     0.0, -4.0,   0.0,   0.0,   0.0,   0.0,
+      /* g(y, z) */  0.0,  0.0,   0.0,   0.0, -20.0,   0.0,
+                     0.0,  0.0,   0.0,   0.0,   0.0, -24.0,
+      /* h(z, x) */ -4.0,  0.0,   0.0,   0.0, -10.0,   0.0,
+                     0.0, -8.0,   0.0,   0.0,   0.0, -12.0
+    }
+  };
+
+  problem_.SetParameterBlockConstant(parameters_ + 2);
+  CheckAllEvaluationCombinations(Problem::EvaluateOptions(), expected);
+}
+
+TEST_F(ProblemEvaluateTest, ExcludedAResidualBlock) {
+  ExpectedEvaluation expected = {
+    // Rows/columns
+    4, 6,
+    // Cost
+    2082.0,
+    // Residuals
+    { -19.0, -35.0,  // f
+      -27.0, -43.0   // h
+    },
+    // Gradient
+    {  146.0,  484.0,   // x
+       228.0,  560.0,   // y
+       270.0,  516.0,   // z
+    },
+    // Jacobian
+    //                       x             y             z
+    { /* f(x, y) */ -2.0,  0.0, -12.0,   0.0,   0.0,   0.0,
+                     0.0, -4.0,   0.0, -16.0,   0.0,   0.0,
+      /* h(z, x) */ -4.0,  0.0,   0.0,   0.0, -10.0,   0.0,
+                     0.0, -8.0,   0.0,   0.0,   0.0, -12.0
+    }
+  };
+
+  Problem::EvaluateOptions evaluate_options;
+  evaluate_options.residual_blocks.push_back(residual_blocks_[0]);
+  evaluate_options.residual_blocks.push_back(residual_blocks_[2]);
+
+  CheckAllEvaluationCombinations(evaluate_options, expected);
+}
+
+TEST_F(ProblemEvaluateTest, ExcludedParameterBlock) {
+  ExpectedEvaluation expected = {
+    // Rows/columns
+    6, 4,
+    // Cost
+    7607.0,
+    // Residuals
+    { -19.0, -35.0,  // f
+      -59.0, -87.0,  // g
+      -27.0, -43.0   // h
+    },
+
+    // Gradient
+    {  146.0,  484.0,  // x
+      1450.0, 2604.0,  // z
+    },
+
+    // Jacobian
+    //                       x             z
+    { /* f(x, y) */ -2.0,  0.0,   0.0,   0.0,
+                     0.0, -4.0,   0.0,   0.0,
+      /* g(y, z) */  0.0,  0.0, -20.0,   0.0,
+                     0.0,  0.0,   0.0, -24.0,
+      /* h(z, x) */ -4.0,  0.0, -10.0,   0.0,
+                     0.0, -8.0,   0.0, -12.0
+    }
+  };
+
+  Problem::EvaluateOptions evaluate_options;
+  // x, z
+  evaluate_options.parameter_blocks.push_back(parameter_blocks_[0]);
+  evaluate_options.parameter_blocks.push_back(parameter_blocks_[2]);
+  evaluate_options.residual_blocks = residual_blocks_;
+  CheckAllEvaluationCombinations(evaluate_options, expected);
+}
+
+TEST_F(ProblemEvaluateTest, ExcludedParameterBlockAndExcludedResidualBlock) {
+  ExpectedEvaluation expected = {
+    // Rows/columns
+    4, 4,
+    // Cost
+    6318.0,
+    // Residuals
+    { -19.0, -35.0,  // f
+      -59.0, -87.0,  // g
+    },
+
+    // Gradient
+    {   38.0,  140.0,  // x
+      1180.0, 2088.0,  // z
+    },
+
+    // Jacobian
+    //                       x             z
+    { /* f(x, y) */ -2.0,  0.0,   0.0,   0.0,
+                     0.0, -4.0,   0.0,   0.0,
+      /* g(y, z) */  0.0,  0.0, -20.0,   0.0,
+                     0.0,  0.0,   0.0, -24.0,
+    }
+  };
+
+  Problem::EvaluateOptions evaluate_options;
+  // x, z
+  evaluate_options.parameter_blocks.push_back(parameter_blocks_[0]);
+  evaluate_options.parameter_blocks.push_back(parameter_blocks_[2]);
+  evaluate_options.residual_blocks.push_back(residual_blocks_[0]);
+  evaluate_options.residual_blocks.push_back(residual_blocks_[1]);
+
+  CheckAllEvaluationCombinations(evaluate_options, expected);
+}
+
+TEST_F(ProblemEvaluateTest, LocalParameterization) {
+  ExpectedEvaluation expected = {
+    // Rows/columns
+    6, 5,
+    // Cost
+    7607.0,
+    // Residuals
+    { -19.0, -35.0,  // f
+      -59.0, -87.0,  // g
+      -27.0, -43.0   // h
+    },
+    // Gradient
+    {  146.0,  484.0,  // x
+      1256.0,          // y with SubsetParameterization
+      1450.0, 2604.0,  // z
+    },
+    // Jacobian
+    //                       x      y             z
+    { /* f(x, y) */ -2.0,  0.0,   0.0,   0.0,   0.0,
+                     0.0, -4.0, -16.0,   0.0,   0.0,
+      /* g(y, z) */  0.0,  0.0,   0.0, -20.0,   0.0,
+                     0.0,  0.0,  -8.0,   0.0, -24.0,
+      /* h(z, x) */ -4.0,  0.0,   0.0, -10.0,   0.0,
+                     0.0, -8.0,   0.0,   0.0, -12.0
+    }
+  };
+
+  vector<int> constant_parameters;
+  constant_parameters.push_back(0);
+  problem_.SetParameterization(parameters_ + 2,
+                               new SubsetParameterization(2,
+                                                          constant_parameters));
+
+  CheckAllEvaluationCombinations(Problem::EvaluateOptions(), expected);
+}
+
 }  // namespace internal
 }  // namespace ceres
diff --git a/internal/ceres/program_evaluator.h b/internal/ceres/program_evaluator.h
index e9640ab..a19cdf8 100644
--- a/internal/ceres/program_evaluator.h
+++ b/internal/ceres/program_evaluator.h
@@ -83,12 +83,14 @@
 #include <omp.h>
 #endif
 
+#include <map>
+#include <vector>
+#include "ceres/execution_summary.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/internal/scoped_ptr.h"
 #include "ceres/parameter_block.h"
 #include "ceres/program.h"
 #include "ceres/residual_block.h"
-#include "ceres/internal/eigen.h"
-#include "ceres/internal/scoped_ptr.h"
-#include "ceres/execution_summary.h"
 
 namespace ceres {
 namespace internal {
diff --git a/internal/ceres/rotation_test.cc b/internal/ceres/rotation_test.cc
index e18a14b..8de1bbd 100644
--- a/internal/ceres/rotation_test.cc
+++ b/internal/ceres/rotation_test.cc
@@ -967,7 +967,8 @@
 
 TEST(MatrixAdapter, RowMajor3x3ReturnTypeAndAccessIsCorrect) {
   double array[9] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
-  const float const_array[9] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f };
+  const float const_array[9] =
+      { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f };
   MatrixAdapter<double, 3, 1> A = RowMajorAdapter3x3(array);
   MatrixAdapter<const float, 3, 1> B = RowMajorAdapter3x3(const_array);
 
@@ -975,24 +976,25 @@
     for (int j = 0; j < 3; ++j) {
       // The values are integers from 1 to 9, so equality tests are appropriate
       // even for float and double values.
-      EXPECT_EQ(A(i,j), array[3*i+j]);
-      EXPECT_EQ(B(i,j), const_array[3*i+j]);
+      EXPECT_EQ(A(i, j), array[3*i+j]);
+      EXPECT_EQ(B(i, j), const_array[3*i+j]);
     }
   }
 }
 
 TEST(MatrixAdapter, ColumnMajor3x3ReturnTypeAndAccessIsCorrect) {
   double array[9] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
-  const float const_array[9] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f };
+  const float const_array[9] =
+      { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f };
   MatrixAdapter<double, 1, 3> A = ColumnMajorAdapter3x3(array);
   MatrixAdapter<const float, 1, 3> B = ColumnMajorAdapter3x3(const_array);
 
   for (int i = 0; i < 3; ++i) {
     for (int j = 0; j < 3; ++j) {
-      // The values are integers from 1 to 9, so equality tests are appropriate
-      // even for float and double values.
-      EXPECT_EQ(A(i,j), array[3*j+i]);
-      EXPECT_EQ(B(i,j), const_array[3*j+i]);
+      // The values are integers from 1 to 9, so equality tests are
+      // appropriate even for float and double values.
+      EXPECT_EQ(A(i, j), array[3*j+i]);
+      EXPECT_EQ(B(i, j), const_array[3*j+i]);
     }
   }
 }
diff --git a/internal/ceres/schur_complement_solver.h b/internal/ceres/schur_complement_solver.h
index c382f95..7e98f31 100644
--- a/internal/ceres/schur_complement_solver.h
+++ b/internal/ceres/schur_complement_solver.h
@@ -33,6 +33,7 @@
 
 #include <set>
 #include <utility>
+#include <vector>
 
 #include "ceres/block_random_access_matrix.h"
 #include "ceres/block_sparse_matrix.h"
diff --git a/internal/ceres/schur_eliminator_impl.h b/internal/ceres/schur_eliminator_impl.h
index 6120db9..339c44b 100644
--- a/internal/ceres/schur_eliminator_impl.h
+++ b/internal/ceres/schur_eliminator_impl.h
@@ -50,7 +50,6 @@
 
 #include <algorithm>
 #include <map>
-#include <glog/logging.h>
 #include "Eigen/Dense"
 #include "ceres/block_random_access_matrix.h"
 #include "ceres/block_sparse_matrix.h"
@@ -60,6 +59,7 @@
 #include "ceres/stl_util.h"
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/scoped_ptr.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/internal/ceres/solver.cc b/internal/ceres/solver.cc
index b1bd2d8..6436d2d 100644
--- a/internal/ceres/solver.cc
+++ b/internal/ceres/solver.cc
@@ -149,8 +149,6 @@
 using internal::StringAppendF;
 
 string Solver::Summary::FullReport() const {
-
-
   string report =
       "\n"
       "Ceres Solver Report\n"
@@ -181,7 +179,8 @@
   // TODO(sameeragarwal): Refactor this into separate functions.
 
   if (minimizer_type == TRUST_REGION) {
-    StringAppendF(&report, "\nMinimizer                 %19s\n", "TRUST_REGION");
+    StringAppendF(&report, "\nMinimizer                 %19s\n",
+                  "TRUST_REGION");
     if (linear_solver_type_used == SPARSE_NORMAL_CHOLESKY ||
         linear_solver_type_used == SPARSE_SCHUR ||
         (linear_solver_type_used == ITERATIVE_SCHUR &&
@@ -261,7 +260,8 @@
 
     StringAppendF(&report, "\nCost:\n");
     StringAppendF(&report, "Initial        % 30e\n", initial_cost);
-    if (termination_type != NUMERICAL_FAILURE && termination_type != USER_ABORT) {
+    if (termination_type != NUMERICAL_FAILURE &&
+        termination_type != USER_ABORT) {
       StringAppendF(&report, "Final          % 30e\n", final_cost);
       StringAppendF(&report, "Change         % 30e\n",
                     initial_cost - final_cost);
@@ -304,7 +304,8 @@
                     max_lbfgs_rank);
     } else {
       StringAppendF(&report,   "Line search direction     %19s\n",
-                    LineSearchDirectionTypeToString(line_search_direction_type));
+                    LineSearchDirectionTypeToString(
+                        line_search_direction_type));
     }
     StringAppendF(&report,   "Line search type          %19s\n",
                   LineSearchTypeToString(line_search_type));
@@ -328,13 +329,15 @@
 
     StringAppendF(&report, "\nCost:\n");
     StringAppendF(&report, "Initial        % 30e\n", initial_cost);
-    if (termination_type != NUMERICAL_FAILURE && termination_type != USER_ABORT) {
+    if (termination_type != NUMERICAL_FAILURE &&
+        termination_type != USER_ABORT) {
       StringAppendF(&report, "Final          % 30e\n", final_cost);
       StringAppendF(&report, "Change         % 30e\n",
                     initial_cost - final_cost);
     }
 
-    StringAppendF(&report, "\nNumber of iterations:    % 20ld\n", iterations.size() - 1);
+    StringAppendF(&report, "\nNumber of iterations:    % 20ld\n",
+                  iterations.size() - 1);
 
     StringAppendF(&report, "\nTime (in seconds):\n");
     StringAppendF(&report, "Preprocessor        %25.3f\n",
diff --git a/internal/ceres/solver_impl.cc b/internal/ceres/solver_impl.cc
index 803b711..7f85fbe 100644
--- a/internal/ceres/solver_impl.cc
+++ b/internal/ceres/solver_impl.cc
@@ -77,20 +77,6 @@
   double* parameters_;
 };
 
-// Macro used to evaluate initial and final residuals, gradient and
-// jacobian if requested by the user.
-//
-// We need a macro here, instead of a simple function call, since the
-// multiplexing happens on variable names.
-#define CERES_EVALUATE(which)                                           \
-  Evaluator::Evaluate(                                                  \
-      original_program,                                                 \
-      options.num_threads,                                              \
-      &summary->which ## _cost,                                         \
-      options.return_ ## which ## _residuals ? &summary->which ## _residuals : NULL, \
-      options.return_ ## which ## _gradient ? &summary->which ## _gradient : NULL, \
-      options.return_ ## which ## _jacobian ? &summary->which ## _jacobian : NULL)
-
 void SetSummaryFinalCost(Solver::Summary* summary) {
   summary->final_cost = summary->initial_cost;
   // We need the loop here, instead of just looking at the last
@@ -240,7 +226,8 @@
                                        file_logging_callback.get());
   }
 
-  TrustRegionLoggingCallback logging_callback(options.minimizer_progress_to_stdout);
+  TrustRegionLoggingCallback logging_callback(
+      options.minimizer_progress_to_stdout);
   if (options.logging_type != SILENT) {
     minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(),
                                        &logging_callback);
@@ -299,7 +286,8 @@
                                        file_logging_callback.get());
   }
 
-  LineSearchLoggingCallback logging_callback(options.minimizer_progress_to_stdout);
+  LineSearchLoggingCallback logging_callback(
+      options.minimizer_progress_to_stdout);
   if (options.logging_type != SILENT) {
     minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(),
                                        &logging_callback);
@@ -400,21 +388,6 @@
 
   event_logger.AddEvent("Init");
 
-  // Evaluate the initial cost, residual vector and the jacobian
-  // matrix if requested by the user.
-  if (options.return_initial_residuals ||
-      options.return_initial_gradient ||
-      options.return_initial_jacobian) {
-    if (!CERES_EVALUATE(initial)) {
-      summary->termination_type = NUMERICAL_FAILURE;
-      summary->error = "Unable to evaluate the initial cost.";
-      LOG(ERROR) << summary->error;
-      return;
-    }
-  }
-
-  event_logger.AddEvent("InitialEvaluate");
-
   original_program->SetParameterBlockStatePtrsToUserStatePtrs();
   event_logger.AddEvent("SetParameterBlockPtrs");
 
@@ -463,6 +436,7 @@
                                                            problem_impl,
                                                            &summary->fixed_cost,
                                                            &summary->error));
+
   event_logger.AddEvent("CreateReducedProgram");
   if (reduced_program == NULL) {
     return;
@@ -480,33 +454,21 @@
     summary->preprocessor_time_in_seconds =
         WallTimeInSeconds() - solver_start_time;
 
+    double post_process_start_time = WallTimeInSeconds();
     LOG(INFO) << "Terminating: FUNCTION_TOLERANCE reached. "
               << "No non-constant parameter blocks found.";
 
+    summary->initial_cost = summary->fixed_cost;
+    summary->final_cost = summary->fixed_cost;
+
     // FUNCTION_TOLERANCE is the right convergence here, as we know
     // that the objective function is constant and cannot be changed
     // any further.
     summary->termination_type = FUNCTION_TOLERANCE;
 
-    double post_process_start_time = WallTimeInSeconds();
-
-    // Evaluate the final cost, residual vector and the jacobian
-    // matrix if requested by the user.
-    if (options.return_final_residuals ||
-        options.return_final_gradient ||
-        options.return_final_jacobian) {
-      if (!CERES_EVALUATE(final)) {
-        summary->termination_type = NUMERICAL_FAILURE;
-        summary->error = "Unable to evaluate the final cost.";
-        LOG(ERROR) << summary->error;
-        return;
-      }
-    }
-
     // Ensure the program state is set to the user parameters on the way out.
     original_program->SetParameterBlockStatePtrsToUserStatePtrs();
 
-    event_logger.AddEvent("FinalEvaluate");
     summary->postprocessor_time_in_seconds =
         WallTimeInSeconds() - post_process_start_time;
     return;
@@ -612,42 +574,21 @@
 
   double post_process_start_time = WallTimeInSeconds();
 
-  // Push the contiguous optimized parameters back to the user's parameters.
+  // Push the contiguous optimized parameters back to the user's
+  // parameters.
   reduced_program->StateVectorToParameterBlocks(parameters.data());
   reduced_program->CopyParameterBlockStateToUserState();
 
-  // Evaluate the final cost, residual vector and the jacobian
-  // matrix if requested by the user.
-  if (options.return_final_residuals ||
-      options.return_final_gradient ||
-      options.return_final_jacobian) {
-    if (!CERES_EVALUATE(final)) {
-      // This failure requires careful handling.
-      //
-      // At this point, we have modified the user's state, but the
-      // evaluation failed and we inform him of NUMERICAL_FAILURE. Ceres
-      // guarantees that user's state is not modified if the solver
-      // returns with NUMERICAL_FAILURE. Thus, we need to restore the
-      // user's state to their original values.
-      reduced_program->StateVectorToParameterBlocks(original_parameters.data());
-      reduced_program->CopyParameterBlockStateToUserState();
-
-      summary->termination_type = NUMERICAL_FAILURE;
-      summary->error = "Unable to evaluate the final cost.";
-      LOG(ERROR) << summary->error;
-
-      event_logger.AddEvent("PostProcess");
-      return;
-    }
-  }
-
-  // Ensure the program state is set to the user parameters on the way out.
+  // Ensure the program state is set to the user parameters on the way
+  // out.
   original_program->SetParameterBlockStatePtrsToUserStatePtrs();
 
   const map<string, double>& linear_solver_time_statistics =
       linear_solver->TimeStatistics();
   summary->linear_solver_time_in_seconds =
-      FindWithDefault(linear_solver_time_statistics, "LinearSolver::Solve", 0.0);
+      FindWithDefault(linear_solver_time_statistics,
+                      "LinearSolver::Solve",
+                      0.0);
 
   const map<string, double>& evaluator_time_statistics =
       evaluator->TimeStatistics();
@@ -675,7 +616,8 @@
   *CHECK_NOTNULL(summary) = Solver::Summary();
 
   summary->minimizer_type = LINE_SEARCH;
-  summary->line_search_direction_type = original_options.line_search_direction_type;
+  summary->line_search_direction_type =
+      original_options.line_search_direction_type;
   summary->max_lbfgs_rank = original_options.max_lbfgs_rank;
   summary->line_search_type = original_options.line_search_type;
   summary->num_parameter_blocks = problem_impl->NumParameterBlocks();
@@ -738,19 +680,6 @@
     }
   }
 
-  // Evaluate the initial cost, residual vector and the jacobian
-  // matrix if requested by the user.
-  if (options.return_initial_residuals ||
-      options.return_initial_gradient ||
-      options.return_initial_jacobian) {
-    if (!CERES_EVALUATE(initial)) {
-      summary->termination_type = NUMERICAL_FAILURE;
-      summary->error = "Unable to evaluate the initial cost.";
-      LOG(ERROR) << summary->error;
-      return;
-    }
-  }
-
   original_program->SetParameterBlockStatePtrsToUserStatePtrs();
 
   // If the user requests gradient checking, construct a new
@@ -802,19 +731,6 @@
 
     SetSummaryFinalCost(summary);
 
-    // Evaluate the final cost, residual vector and the jacobian
-    // matrix if requested by the user.
-    if (options.return_final_residuals ||
-        options.return_final_gradient ||
-        options.return_final_jacobian) {
-      if (!CERES_EVALUATE(final)) {
-        summary->termination_type = NUMERICAL_FAILURE;
-        summary->error = "Unable to evaluate the final cost.";
-        LOG(ERROR) << summary->error;
-        return;
-      }
-    }
-
     // Ensure the program state is set to the user parameters on the way out.
     original_program->SetParameterBlockStatePtrsToUserStatePtrs();
     summary->postprocessor_time_in_seconds =
@@ -865,33 +781,6 @@
 
   SetSummaryFinalCost(summary);
 
-  // Evaluate the final cost, residual vector and the jacobian
-  // matrix if requested by the user.
-  if (options.return_final_residuals ||
-      options.return_final_gradient ||
-      options.return_final_jacobian) {
-    if (!CERES_EVALUATE(final)) {
-      // This failure requires careful handling.
-      //
-      // At this point, we have modified the user's state, but the
-      // evaluation failed and we inform him of NUMERICAL_FAILURE. Ceres
-      // guarantees that user's state is not modified if the solver
-      // returns with NUMERICAL_FAILURE. Thus, we need to restore the
-      // user's state to their original values.
-
-      reduced_program->StateVectorToParameterBlocks(original_parameters.data());
-      reduced_program->CopyParameterBlockStateToUserState();
-
-      summary->termination_type = NUMERICAL_FAILURE;
-      summary->error = "Unable to evaluate the final cost.";
-      LOG(ERROR) << summary->error;
-
-      summary->postprocessor_time_in_seconds =
-          WallTimeInSeconds() - post_process_start_time;
-      return;
-    }
-  }
-
   // Ensure the program state is set to the user parameters on the way out.
   original_program->SetParameterBlockStatePtrsToUserStatePtrs();
 
@@ -947,8 +836,9 @@
   return true;
 }
 
-bool SolverImpl::IsParameterBlockSetIndependent(const set<double*>& parameter_block_ptrs,
-                                                const vector<ResidualBlock*>& residual_blocks) {
+bool SolverImpl::IsParameterBlockSetIndependent(
+    const set<double*>& parameter_block_ptrs,
+    const vector<ResidualBlock*>& residual_blocks) {
   // Loop over each residual block and ensure that no two parameter
   // blocks in the same residual block are part of
   // parameter_block_ptrs as that would violate the assumption that it
@@ -1168,8 +1058,8 @@
 
   event_logger.AddEvent("AlternateSolver");
 
-  // Since the transformed program is the "active" program, and it is mutated,
-  // update the parameter offsets and indices.
+  // Since the transformed program is the "active" program, and it is
+  // mutated, update the parameter offsets and indices.
   transformed_program->SetParameterOffsetsAndIndex();
 
   event_logger.AddEvent("SetOffsets");
@@ -1292,10 +1182,11 @@
   return LinearSolver::Create(linear_solver_options);
 }
 
-bool SolverImpl::ApplyUserOrdering(const ProblemImpl::ParameterMap& parameter_map,
-                                   const ParameterBlockOrdering* ordering,
-                                   Program* program,
-                                   string* error) {
+bool SolverImpl::ApplyUserOrdering(
+    const ProblemImpl::ParameterMap& parameter_map,
+    const ParameterBlockOrdering* ordering,
+    Program* program,
+    string* error) {
   if (ordering->NumElements() != program->NumParameterBlocks()) {
     *error = StringPrintf("User specified ordering does not have the same "
                           "number of parameters as the problem. The problem"
@@ -1323,8 +1214,8 @@
           parameter_map.find(*parameter_block_ptr_it);
       if (parameter_block_it == parameter_map.end()) {
         *error = StringPrintf("User specified ordering contains a pointer "
-                              "to a double that is not a parameter block in the "
-                              "problem. The invalid double is in group: %d",
+                              "to a double that is not a parameter block in "
+                              "the problem. The invalid double is in group: %d",
                               group_it->first);
         return false;
       }
@@ -1356,9 +1247,10 @@
 // Reorder the residuals for program, if necessary, so that the residuals
 // involving each E block occur together. This is a necessary condition for the
 // Schur eliminator, which works on these "row blocks" in the jacobian.
-bool SolverImpl::LexicographicallyOrderResidualBlocks(const int num_eliminate_blocks,
-                                                      Program* program,
-                                                      string* error) {
+bool SolverImpl::LexicographicallyOrderResidualBlocks(
+    const int num_eliminate_blocks,
+    Program* program,
+    string* error) {
   CHECK_GE(num_eliminate_blocks, 1)
       << "Congratulations, you found a Ceres bug! Please report this error "
       << "to the developers.";
@@ -1435,10 +1327,11 @@
   return true;
 }
 
-Evaluator* SolverImpl::CreateEvaluator(const Solver::Options& options,
-                                       const ProblemImpl::ParameterMap& parameter_map,
-                                       Program* program,
-                                       string* error) {
+Evaluator* SolverImpl::CreateEvaluator(
+    const Solver::Options& options,
+    const ProblemImpl::ParameterMap& parameter_map,
+    Program* program,
+    string* error) {
   Evaluator::Options evaluator_options;
   evaluator_options.linear_solver_type = options.linear_solver_type;
   evaluator_options.num_eliminate_blocks =
@@ -1479,7 +1372,7 @@
     // Iterate over each group and verify that it is an independent
     // set.
     map<int, set<double*> >::const_iterator it = group_to_elements.begin();
-    for ( ;it != group_to_elements.end(); ++it) {
+    for ( ; it != group_to_elements.end(); ++it) {
       if (!IsParameterBlockSetIndependent(it->second,
                                           program.residual_blocks())) {
         summary->error =
diff --git a/internal/ceres/solver_impl.h b/internal/ceres/solver_impl.h
index c9848fb..c5f5efa 100644
--- a/internal/ceres/solver_impl.h
+++ b/internal/ceres/solver_impl.h
@@ -31,6 +31,7 @@
 #ifndef CERES_INTERNAL_SOLVER_IMPL_H_
 #define CERES_INTERNAL_SOLVER_IMPL_H_
 
+#include <set>
 #include <string>
 #include <vector>
 #include "ceres/internal/port.h"
diff --git a/internal/ceres/solver_impl_test.cc b/internal/ceres/solver_impl_test.cc
index 5cba7d7..8e443ba 100644
--- a/internal/ceres/solver_impl_test.cc
+++ b/internal/ceres/solver_impl_test.cc
@@ -240,8 +240,12 @@
 
   double expected_fixed_cost;
   ResidualBlock *expected_removed_block = program.residual_blocks()[0];
-  scoped_array<double> scratch(new double[expected_removed_block->NumScratchDoublesForEvaluate()]);
-  expected_removed_block->Evaluate(&expected_fixed_cost, NULL, NULL, scratch.get());
+  scoped_array<double> scratch(
+      new double[expected_removed_block->NumScratchDoublesForEvaluate()]);
+  expected_removed_block->Evaluate(&expected_fixed_cost,
+                                   NULL,
+                                   NULL,
+                                   scratch.get());
 
   string error;
   EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program,
@@ -755,76 +759,6 @@
   EXPECT_EQ(&w, problem.program().parameter_blocks()[3]->state());
 }
 
-#define CHECK_ARRAY(name, value)       \
-  if (options.return_ ## name) {       \
-    EXPECT_EQ(summary.name.size(), 1); \
-    EXPECT_EQ(summary.name[0], value); \
-  } else {                             \
-    EXPECT_EQ(summary.name.size(), 0); \
-  }
-
-#define CHECK_JACOBIAN(name)                  \
-  if (options.return_ ## name) {              \
-    EXPECT_EQ(summary.name.num_rows, 1);      \
-    EXPECT_EQ(summary.name.num_cols, 1);      \
-    EXPECT_EQ(summary.name.cols.size(), 2);   \
-    EXPECT_EQ(summary.name.cols[0], 0);       \
-    EXPECT_EQ(summary.name.cols[1], 1);       \
-    EXPECT_EQ(summary.name.rows.size(), 1);   \
-    EXPECT_EQ(summary.name.rows[0], 0);       \
-    EXPECT_EQ(summary.name.values.size(), 0); \
-    EXPECT_EQ(summary.name.values[0], name);  \
-  } else {                                    \
-    EXPECT_EQ(summary.name.num_rows, 0);      \
-    EXPECT_EQ(summary.name.num_cols, 0);      \
-    EXPECT_EQ(summary.name.cols.size(), 0);   \
-    EXPECT_EQ(summary.name.rows.size(), 0);   \
-    EXPECT_EQ(summary.name.values.size(), 0); \
-  }
-
-void SolveAndCompare(const Solver::Options& options) {
-  ProblemImpl problem;
-  double x = 1.0;
-
-  const double initial_residual = 5.0 - x;
-  const double initial_jacobian = -1.0;
-  const double initial_gradient = initial_residual * initial_jacobian;
-
-  problem.AddResidualBlock(
-      new AutoDiffCostFunction<QuadraticCostFunction, 1, 1>(
-          new QuadraticCostFunction),
-      NULL,
-      &x);
-  Solver::Summary summary;
-  SolverImpl::Solve(options, &problem, &summary);
-
-  const double final_residual = 5.0 - x;
-  const double final_jacobian = -1.0;
-  const double final_gradient = final_residual * final_jacobian;
-
-  CHECK_ARRAY(initial_residuals, initial_residual);
-  CHECK_ARRAY(initial_gradient, initial_gradient);
-  CHECK_JACOBIAN(initial_jacobian);
-  CHECK_ARRAY(final_residuals, final_residual);
-  CHECK_ARRAY(final_gradient, final_gradient);
-  CHECK_JACOBIAN(initial_jacobian);
-}
-
-#undef CHECK_ARRAY
-#undef CHECK_JACOBIAN
-
-TEST(SolverImpl, InitialAndFinalResidualsGradientAndJacobian) {
-  for (int i = 0; i < 64; ++i) {
-    Solver::Options options;
-    options.return_initial_residuals = (i & 1);
-    options.return_initial_gradient = (i & 2);
-    options.return_initial_jacobian = (i & 4);
-    options.return_final_residuals = (i & 8);
-    options.return_final_gradient = (i & 16);
-    options.return_final_jacobian = (i & 64);
-  }
-}
-
 TEST(SolverImpl, NoParameterBlocks) {
   ProblemImpl problem_impl;
   Solver::Options options;
@@ -845,34 +779,12 @@
   EXPECT_EQ(summary.error, "Problem contains no residual blocks.");
 }
 
-class FailingCostFunction : public SizedCostFunction<1, 1> {
- public:
-  virtual bool Evaluate(double const* const* parameters,
-                        double* residuals,
-                        double** jacobians) const {
-    return false;
-  }
-};
-
-TEST(SolverImpl, InitialCostEvaluationFails) {
-  ProblemImpl problem_impl;
-  Solver::Options options;
-  Solver::Summary summary;
-  double x;
-  options.return_initial_residuals = true;
-  problem_impl.AddResidualBlock(new FailingCostFunction, NULL, &x);
-  SolverImpl::Solve(options, &problem_impl, &summary);
-  EXPECT_EQ(summary.termination_type, NUMERICAL_FAILURE);
-  EXPECT_EQ(summary.error, "Unable to evaluate the initial cost.");
-}
 
 TEST(SolverImpl, ProblemIsConstant) {
   ProblemImpl problem_impl;
   Solver::Options options;
   Solver::Summary summary;
   double x = 1;
-  options.return_initial_residuals = true;
-  options.return_final_residuals = true;
   problem_impl.AddResidualBlock(new UnaryIdentityCostFunction, NULL, &x);
   problem_impl.SetParameterBlockConstant(&x);
   SolverImpl::Solve(options, &problem_impl, &summary);
diff --git a/internal/ceres/sparse_normal_cholesky_solver.cc b/internal/ceres/sparse_normal_cholesky_solver.cc
index 6fae204..dd05f0c 100644
--- a/internal/ceres/sparse_normal_cholesky_solver.cc
+++ b/internal/ceres/sparse_normal_cholesky_solver.cc
@@ -132,7 +132,7 @@
   // off of Jt to compute the Cholesky factorization of the normal
   // equations.
   cs_di* A2 = cs_transpose(&At, 1);
-  cs_di* AtA = cs_multiply(&At,A2);
+  cs_di* AtA = cs_multiply(&At, A2);
 
   cxsparse_.Free(A2);
   if (per_solve_options.D != NULL) {
diff --git a/internal/ceres/stl_util.h b/internal/ceres/stl_util.h
index b23e7c1..08f15ec 100644
--- a/internal/ceres/stl_util.h
+++ b/internal/ceres/stl_util.h
@@ -31,6 +31,8 @@
 #ifndef CERES_INTERNAL_STL_UTIL_H_
 #define CERES_INTERNAL_STL_UTIL_H_
 
+#include <algorithm>
+
 namespace ceres {
 
 // STLDeleteContainerPointers()
diff --git a/internal/ceres/stringprintf.h b/internal/ceres/stringprintf.h
index f2f907a..cd1be14 100644
--- a/internal/ceres/stringprintf.h
+++ b/internal/ceres/stringprintf.h
@@ -65,17 +65,17 @@
 // Return a C++ string.
 extern string StringPrintf(const char* format, ...)
     // Tell the compiler to do printf format string checking.
-    CERES_PRINTF_ATTRIBUTE(1,2);
+    CERES_PRINTF_ATTRIBUTE(1, 2);
 
 // Store result into a supplied string and return it.
 extern const string& SStringPrintf(string* dst, const char* format, ...)
     // Tell the compiler to do printf format string checking.
-    CERES_PRINTF_ATTRIBUTE(2,3);
+    CERES_PRINTF_ATTRIBUTE(2, 3);
 
 // Append result to a supplied string.
 extern void StringAppendF(string* dst, const char* format, ...)
     // Tell the compiler to do printf format string checking.
-    CERES_PRINTF_ATTRIBUTE(2,3);
+    CERES_PRINTF_ATTRIBUTE(2, 3);
 
 // Lower-level routine that takes a va_list and appends to a specified string.
 // All other routines are just convenience wrappers around it.
diff --git a/internal/ceres/suitesparse.cc b/internal/ceres/suitesparse.cc
index cf3c48f..d200aeb 100644
--- a/internal/ceres/suitesparse.cc
+++ b/internal/ceres/suitesparse.cc
@@ -135,10 +135,11 @@
   return AnalyzeCholeskyWithUserOrdering(A, ordering);
 }
 
-cholmod_factor* SuiteSparse::AnalyzeCholeskyWithUserOrdering(cholmod_sparse* A,
-                                                             const vector<int>& ordering) {
+cholmod_factor* SuiteSparse::AnalyzeCholeskyWithUserOrdering(
+    cholmod_sparse* A,
+    const vector<int>& ordering) {
   CHECK_EQ(ordering.size(), A->nrow);
-  cc_.nmethods = 1 ;
+  cc_.nmethods = 1;
   cc_.method[0].ordering = CHOLMOD_GIVEN;
   cholmod_factor* factor  =
       cholmod_analyze_p(A, const_cast<int*>(&ordering[0]), NULL, 0, &cc_);
diff --git a/internal/ceres/suitesparse.h b/internal/ceres/suitesparse.h
index eb691c0..3fe7908 100644
--- a/internal/ceres/suitesparse.h
+++ b/internal/ceres/suitesparse.h
@@ -39,9 +39,9 @@
 #include <string>
 #include <vector>
 
-#include <glog/logging.h>
-#include "cholmod.h"
 #include "ceres/internal/port.h"
+#include "cholmod.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/internal/ceres/system_test.cc b/internal/ceres/system_test.cc
index 597c7ef..095b51e 100644
--- a/internal/ceres/system_test.cc
+++ b/internal/ceres/system_test.cc
@@ -121,7 +121,7 @@
                                  const double max_abs_difference) {
   int num_configurations = configurations.size();
   vector<SystemTestProblem*> problems;
-  vector<Solver::Summary> summaries(num_configurations);
+  vector<vector<double> > final_residuals(num_configurations);
 
   for (int i = 0; i < num_configurations; ++i) {
     SystemTestProblem* system_test_problem = new SystemTestProblem();
@@ -135,7 +135,6 @@
     options.preconditioner_type = config.preconditioner_type;
     options.num_threads = config.num_threads;
     options.num_linear_solver_threads = config.num_threads;
-    options.return_final_residuals = true;
 
     if (config.use_automatic_ordering) {
       delete options.linear_solver_ordering;
@@ -145,11 +144,20 @@
     LOG(INFO) << "Running solver configuration: "
               << config.ToString();
 
+    Solver::Summary summary;
     Solve(options,
           system_test_problem->mutable_problem(),
-          &summaries[i]);
+          &summary);
 
-    CHECK_NE(summaries[i].termination_type, ceres::NUMERICAL_FAILURE)
+    system_test_problem
+        ->mutable_problem()
+        ->Evaluate(Problem::EvaluateOptions(),
+                   NULL,
+                   &final_residuals[i],
+                   NULL,
+                   NULL);
+
+    CHECK_NE(summary.termination_type, ceres::NUMERICAL_FAILURE)
         << "Solver configuration " << i << " failed.";
     problems.push_back(system_test_problem);
 
@@ -161,8 +169,8 @@
     // the same residuals at two completely different positions in
     // parameter space.
     if (i > 0) {
-      const vector<double>& reference_residuals = summaries[0].final_residuals;
-      const vector<double>& current_residuals = summaries[i].final_residuals;
+      const vector<double>& reference_residuals = final_residuals[0];
+      const vector<double>& current_residuals = final_residuals[i];
 
       for (int j = 0; j < reference_residuals.size(); ++j) {
         EXPECT_NEAR(current_residuals[j],
diff --git a/internal/ceres/trust_region_minimizer.cc b/internal/ceres/trust_region_minimizer.cc
index fc405f5..981c60a 100644
--- a/internal/ceres/trust_region_minimizer.cc
+++ b/internal/ceres/trust_region_minimizer.cc
@@ -189,7 +189,7 @@
       + summary->preprocessor_time_in_seconds;
   summary->iterations.push_back(iteration_summary);
 
-   int num_consecutive_invalid_steps = 0;
+  int num_consecutive_invalid_steps = 0;
   while (true) {
     if (!RunCallbacks(options.callbacks, iteration_summary, summary)) {
       return;
@@ -323,9 +323,9 @@
           options.inner_iteration_minimizer->Minimize(options,
                                                       inner_iteration_x.data(),
                                                       &inner_iteration_summary);
-          if(!evaluator->Evaluate(inner_iteration_x.data(),
-                                  &new_cost,
-                                  NULL, NULL, NULL)) {
+          if (!evaluator->Evaluate(inner_iteration_x.data(),
+                                   &new_cost,
+                                   NULL, NULL, NULL)) {
             VLOG(2) << "Inner iteration failed.";
             new_cost = x_plus_delta_cost;
           } else {
@@ -422,7 +422,8 @@
                                NULL,
                                jacobian)) {
         summary->termination_type = NUMERICAL_FAILURE;
-        summary->error = "Terminating: Residual and Jacobian evaluation failed.";
+        summary->error =
+            "Terminating: Residual and Jacobian evaluation failed.";
         LOG(WARNING) << summary->error;
         return;
       }
@@ -435,7 +436,8 @@
         summary->termination_type = GRADIENT_TOLERANCE;
         VLOG(1) << "Terminating: Gradient tolerance reached."
                 << "Relative gradient max norm: "
-                << iteration_summary.gradient_max_norm / initial_gradient_max_norm
+                << (iteration_summary.gradient_max_norm /
+                    initial_gradient_max_norm)
                 << " <= " << options_.gradient_tolerance;
         return;
       }
diff --git a/internal/ceres/trust_region_minimizer.h b/internal/ceres/trust_region_minimizer.h
index 173b0f3..9a02284 100644
--- a/internal/ceres/trust_region_minimizer.h
+++ b/internal/ceres/trust_region_minimizer.h
@@ -52,10 +52,10 @@
  private:
   void Init(const Minimizer::Options& options);
   void EstimateScale(const SparseMatrix& jacobian, double* scale) const;
-  bool MaybeDumpLinearLeastSquaresProblem( const int iteration,
-                                           const SparseMatrix* jacobian,
-                                           const double* residuals,
-                                           const double* step) const;
+  bool MaybeDumpLinearLeastSquaresProblem(const int iteration,
+                                          const SparseMatrix* jacobian,
+                                          const double* residuals,
+                                          const double* step) const;
 
   Minimizer::Options options_;
 };
diff --git a/internal/ceres/trust_region_minimizer_test.cc b/internal/ceres/trust_region_minimizer_test.cc
index a82dea7..4bc9409 100644
--- a/internal/ceres/trust_region_minimizer_test.cc
+++ b/internal/ceres/trust_region_minimizer_test.cc
@@ -258,7 +258,8 @@
 }
 
 TEST(TrustRegionMinimizer, PowellsSingularFunctionUsingDogleg) {
-  // The following two cases are excluded because they encounter a local minimum.
+  // The following two cases are excluded because they encounter a
+  // local minimum.
   //
   //  IsTrustRegionSolveSuccessful<true, true, false, true >(kStrategy);
   //  IsTrustRegionSolveSuccessful<true,  true,  true,  true >(kStrategy);
diff --git a/internal/ceres/trust_region_strategy.cc b/internal/ceres/trust_region_strategy.cc
index 89bc19d..c68269d 100644
--- a/internal/ceres/trust_region_strategy.cc
+++ b/internal/ceres/trust_region_strategy.cc
@@ -1,3 +1,35 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012, 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)
+//         keir@google.com (Keir Mierle)
+
 #include "ceres/trust_region_strategy.h"
 #include "ceres/dogleg_strategy.h"
 #include "ceres/levenberg_marquardt_strategy.h"
diff --git a/internal/ceres/trust_region_strategy.h b/internal/ceres/trust_region_strategy.h
index 391da97..f150594 100644
--- a/internal/ceres/trust_region_strategy.h
+++ b/internal/ceres/trust_region_strategy.h
@@ -52,7 +52,7 @@
 // radius to scale the damping term, which controls the step size, but
 // does not set a hard limit on its size.
 class TrustRegionStrategy {
-public:
+ public:
   struct Options {
     Options()
         : trust_region_strategy_type(LEVENBERG_MARQUARDT),
diff --git a/internal/ceres/wall_time.h b/internal/ceres/wall_time.h
index 1dbd6e9..45f65ca 100644
--- a/internal/ceres/wall_time.h
+++ b/internal/ceres/wall_time.h
@@ -72,7 +72,7 @@
 //     Total:  time3  time1 + time2 + time3;
 class EventLogger {
  public:
-  EventLogger(const string& logger_name);
+  explicit EventLogger(const string& logger_name);
   ~EventLogger();
   void AddEvent(const string& event_name);