diff --git a/main_package/classes/estimators/structure_constraint_based_estimator.py b/main_package/classes/estimators/structure_constraint_based_estimator.py
index fba11e9..174ebf9 100644
--- a/main_package/classes/estimators/structure_constraint_based_estimator.py
+++ b/main_package/classes/estimators/structure_constraint_based_estimator.py
@@ -19,6 +19,8 @@ import structure_graph.sample_path as sp
 import structure_graph.structure as st
 import optimizers.constraint_based_optimizer as optimizer
 
+import concurrent.futures
+
 from utility.decorators import timing,timing_write
 
 import multiprocessing
@@ -243,11 +245,11 @@ class StructureConstraintBasedEstimator(se.StructureEstimator):
 
         'Estimate the best parents for each node'
         #with multiprocessing.Pool(processes=cpu_count) as pool:
-        with get_context("spawn").Pool(processes=cpu_count) as pool:
-        
-            list_edges_partial = pool.starmap(ctpc_algo, zip(
+        #with get_context("spawn").Pool(processes=cpu_count) as pool:
+        with concurrent.futures.ProcessPoolExecutor(max_workers=cpu_count) as executor:
+            list_edges_partial = executor.map(ctpc_algo,
                                                                  self.nodes,
-                                                                 total_vars_numb_array))
+                                                                 total_vars_numb_array)
             #list_edges_partial = [ctpc_algo(n,total_vars_numb) for n in self.nodes]
 
         return set(itertools.chain.from_iterable(list_edges_partial))
diff --git a/main_package/tests/estimators/test_structure_constraint_based_estimator_server.py b/main_package/tests/estimators/test_structure_constraint_based_estimator_server.py
new file mode 100644
index 0000000..1f37831
--- /dev/null
+++ b/main_package/tests/estimators/test_structure_constraint_based_estimator_server.py
@@ -0,0 +1,76 @@
+import sys
+sys.path.append("../../classes/")
+import glob
+import math
+import os
+import unittest
+
+import networkx as nx
+import numpy as np
+import psutil
+from line_profiler import LineProfiler
+
+import utility.cache as ch
+import structure_graph.sample_path as sp
+import estimators.structure_constraint_based_estimator as se
+import utility.json_importer as ji
+
+from multiprocessing import set_start_method
+
+import copy
+
+
+class TestStructureConstraintBasedEstimator(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        pass
+
+    def test_structure(self):
+        #cls.read_files = glob.glob(os.path.join('../../data', "*.json"))
+        self.importer = ji.JsonImporter("/home/alessandro/Documents/ctbn_cba/data/networks_and_trajectories_ternary_data_15.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
+        self.s1 = sp.SamplePath(self.importer)
+        self.s1.build_trajectories()
+        self.s1.build_structure()
+
+        true_edges = copy.deepcopy(self.s1.structure.edges)
+        true_edges = set(map(tuple, true_edges))
+
+        
+        se1 = se.StructureConstraintBasedEstimator(self.s1,0.1,0.1)
+        edges = se1.estimate_structure(
+                                    max_parents = None,
+                                    iterations_number = 100,
+                                    patience = 35,
+                                    tabu_length = 15,
+                                    tabu_rules_duration = 15,
+                                    optimizer = 'tabu',
+                                    disable_multiprocessing=False
+                                    )
+
+
+        self.importer = ji.JsonImporter("/home/alessandro/Documents/ctbn_cba/data/networks_and_trajectories_ternary_data_15.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
+        self.s1 = sp.SamplePath(self.importer)
+        self.s1.build_trajectories()
+        self.s1.build_structure()
+
+        true_edges = copy.deepcopy(self.s1.structure.edges)
+        true_edges = set(map(tuple, true_edges))
+
+        
+        se1 = se.StructureConstraintBasedEstimator(self.s1,0.1,0.1)
+        edges = se1.estimate_structure(
+                                    max_parents = None,
+                                    iterations_number = 100,
+                                    patience = 35,
+                                    tabu_length = 15,
+                                    tabu_rules_duration = 15,
+                                    optimizer = 'tabu',
+                                    disable_multiprocessing=True
+                                    )
+        
+        
+
+        self.assertEqual(edges, true_edges)
+
+if __name__ == '__main__':
+    unittest.main()