Modernize the code base to C++11 standards and beyond.

Apply `clang-modernize` (based on Clang 3.6) transformations to the
codebase while making sure to support Clang>=3.4 and GCC>=4.8.

We apply the transformations in parallel to speed up the quite
time consuming process, and use our `clang-format` style file
to automatically format the code respecting our coding conventions.

We use the following self-explanatory transformations:

* AddOverride
* LoopConvert
* PassByValue
* ReplaceAutoPtr
* UseAuto
* UseNullptr

This required a `compile_commands.json` compilation database, e.g.

    ccmake .. -DCMAKE_BUILD_TYPE=Release -DCMAKE_EXPORT_COMPILE_COMMANDS=1

for CMake or check Bear for a Makefile based solution (or even Ninja).

    git ls-files -x '*.cpp|*.h' | \
      xargs -I{} -P $(nproc) clang-modernize -p build -final-syntax-check -format -style=file -summary -for-compilers=clang-3.4,gcc-4.8 -include . -exclude third_party {}

Boom!

References:

* http://clang.llvm.org/extra/clang-modernize.html
* http://clang.llvm.org/extra/ModernizerUsage.html

algorithms/bayes_classifier.hpp

@@ -31,6 +31,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 #include <cmath>
 
 #include <vector>
+#include <utility>
 
 struct NormalDistribution
 {
@@ -80,11 +81,11 @@ class BayesClassifier
     };
     using ClassificationT = std::pair<ClassLabel, double>;
 
-    BayesClassifier(const PositiveDistributionT &positive_distribution,
-                    const NegativeDistributionT &negative_distribution,
+    BayesClassifier(PositiveDistributionT positive_distribution,
+                    NegativeDistributionT negative_distribution,
                     const double positive_apriori_probability)
-        : positive_distribution(positive_distribution),
-          negative_distribution(negative_distribution),
+        : positive_distribution(std::move(positive_distribution)),
+          negative_distribution(std::move(negative_distribution)),
           positive_apriori_probability(positive_apriori_probability),
           negative_apriori_probability(1. - positive_apriori_probability)
     {

algorithms/douglas_peucker.cpp

@@ -99,8 +99,8 @@ void DouglasPeucker::Run(RandomAccessIt begin, RandomAccessIt end, const unsigne
 
     {
         BOOST_ASSERT_MSG(zoom_level < DOUGLAS_PEUCKER_THRESHOLDS.size(), "unsupported zoom level");
-        RandomAccessIt left_border = begin;
-        RandomAccessIt right_border = std::next(begin);
+        auto left_border = begin;
+        auto right_border = std::next(begin);
         // Sweep over array and identify those ranges that need to be checked
         do
         {

algorithms/graph_compressor.cpp

@@ -8,8 +8,8 @@
 
 #include "../util/simple_logger.hpp"
 
-GraphCompressor::GraphCompressor(const SpeedProfileProperties& speed_profile)
-    : speed_profile(speed_profile)
+GraphCompressor::GraphCompressor(SpeedProfileProperties speed_profile)
+    : speed_profile(std::move(speed_profile))
 {
 }
 

algorithms/graph_compressor.hpp

@@ -43,7 +43,7 @@ class GraphCompressor
     using EdgeData = NodeBasedDynamicGraph::EdgeData;
 
 public:
-    GraphCompressor(const SpeedProfileProperties& speed_profile);
+  GraphCompressor(SpeedProfileProperties speed_profile);
 
     void Compress(const std::unordered_set<NodeID>& barrier_nodes,
                   const std::unordered_set<NodeID>& traffic_lights,