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diff --git a/src/Spatial_searching/test/test_Spatial_tree_data_structure.cpp b/src/Spatial_searching/test/test_Spatial_tree_data_structure.cpp
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+/*    This file is part of the Gudhi Library. The Gudhi library
+ *    (Geometric Understanding in Higher Dimensions) is a generic C++
+ *    library for computational topology.
+ *
+ *    Author(s):       Clement Jamin
+ *
+ *    Copyright (C) 2016  INRIA Sophia-Antipolis (France)
+ *
+ *    This program is free software: you can redistribute it and/or modify
+ *    it under the terms of the GNU General Public License as published by
+ *    the Free Software Foundation, either version 3 of the License, or
+ *    (at your option) any later version.
+ *
+ *    This program is distributed in the hope that it will be useful,
+ *    but WITHOUT ANY WARRANTY; without even the implied warranty of
+ *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ *    GNU General Public License for more details.
+ *
+ *    You should have received a copy of the GNU General Public License
+ *    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MODULE Spatial_searching - test Spatial_tree_data_structure
+#include <boost/test/unit_test.hpp>
+
+#include <gudhi/Spatial_tree_data_structure.h>
+
+#include <CGAL/Epick_d.h>
+#include <CGAL/Random.h>
+
+#include <array>
+#include <vector>
+
+BOOST_AUTO_TEST_CASE(test_Spatial_tree_data_structure)
+{
+  typedef CGAL::Epick_d<CGAL::Dimension_tag<4> >    K;
+  typedef K::FT                                     FT;
+  typedef K::Point_d                                Point;
+  typedef std::vector<Point>                        Points;
+
+  typedef Gudhi::spatial_searching::Spatial_tree_data_structure<
+    K, Points>                                      Points_ds;
+  
+  CGAL::Random rd;
+
+  Points points;
+  for (int i = 0 ; i < 500 ; ++i)
+    points.push_back(Point(std::array<FT,4>({rd.get_double(-1.,1),rd.get_double(-1.,1),rd.get_double(-1.,1),rd.get_double(-1.,1)})));
+
+  Points_ds points_ds(points);
+
+  std::size_t closest_pt_index =
+    points_ds.query_k_nearest_neighbors(points[10], 1, false).begin()->first;
+  BOOST_CHECK(closest_pt_index == 10);
+
+  auto kns_range = points_ds.query_k_nearest_neighbors(points[20], 10, true);
+
+  FT last_dist = -1.;
+  for (auto const& nghb : kns_range)
+  {
+    BOOST_CHECK(nghb.second > last_dist);
+    last_dist = nghb.second;
+  }
+
+  auto kfs_range = points_ds.query_k_farthest_neighbors(points[20], 10, true);
+
+  last_dist = kfs_range.begin()->second;
+  for (auto const& nghb : kfs_range)
+  {
+    BOOST_CHECK(nghb.second <= last_dist);
+    last_dist = nghb.second;
+  }
+}