diff --git a/hyppopy/plugins/hyperopt_solver_plugin.py b/hyppopy/plugins/hyperopt_solver_plugin.py
index 4c5a5bc..fe3d011 100644
--- a/hyppopy/plugins/hyperopt_solver_plugin.py
+++ b/hyppopy/plugins/hyperopt_solver_plugin.py
@@ -1,80 +1,82 @@
 # DKFZ
 #
 #
 # Copyright (c) German Cancer Research Center,
 # Division of Medical and Biological Informatics.
 # All rights reserved.
 #
 # This software is distributed WITHOUT ANY WARRANTY; without
 # even the implied warranty of MERCHANTABILITY or FITNESS FOR
 # A PARTICULAR PURPOSE.
 #
 # See LICENSE.txt or http://www.mitk.org for details.
 #
 # Author: Sven Wanner (s.wanner@dkfz.de)
 
 import os
 import logging
 from hyppopy.globals import DEBUGLEVEL
 LOG = logging.getLogger(os.path.basename(__file__))
 LOG.setLevel(DEBUGLEVEL)
 
 from pprint import pformat
 from hyperopt import fmin, tpe, hp, STATUS_OK, STATUS_FAIL, Trials
 from yapsy.IPlugin import IPlugin
 
 
 from hyppopy.projectmanager import ProjectManager
 from hyppopy.solverpluginbase import SolverPluginBase
 
 
 class hyperopt_Solver(SolverPluginBase, IPlugin):
     trials = None
     best = None
 
     def __init__(self):
         SolverPluginBase.__init__(self)
         LOG.debug("initialized")
 
     def blackbox_function(self, params):
+        status = STATUS_FAIL
         try:
             loss = self.blackbox_function_template(self.data, params)
-            status = STATUS_OK
+            if loss is not None:
+                status = STATUS_OK
         except Exception as e:
             LOG.error("execution of self.loss(self.data, params) failed due to:\n {}".format(e))
             status = STATUS_FAIL
         return {'loss': loss, 'status': status}
 
     def execute_solver(self, parameter):
         LOG.debug("execute_solver using solution space:\n\n\t{}\n".format(pformat(parameter)))
         self.trials = Trials()
 
         try:
             self.best = fmin(fn=self.blackbox_function,
                              space=parameter,
                              algo=tpe.suggest,
                              max_evals=ProjectManager.max_iterations,
                              trials=self.trials)
         except Exception as e:
             msg = "internal error in hyperopt.fmin occured. {}".format(e)
             LOG.error(msg)
             raise BrokenPipeError(msg)
 
     def convert_results(self):
         # currently converting results in a way that this function returns a dict
         # keeping all useful parameter as key/list item. This will be automatically
         # converted to a pandas dataframe in the solver class
         results = {'duration': [], 'losses': []}
         pset = self.trials.trials[0]['misc']['vals']
         for p in pset.keys():
             results[p] = []
 
         for n, trial in enumerate(self.trials.trials):
             t1 = trial['book_time']
             t2 = trial['refresh_time']
             results['duration'].append((t2 - t1).microseconds/1000.0)
             results['losses'].append(trial['result']['loss'])
             pset = trial['misc']['vals']
             for p in pset.items():
                 results[p[0]].append(p[1][0])
         return results, self.best
diff --git a/hyppopy/solverpluginbase.py b/hyppopy/solverpluginbase.py
index 7e3ddc4..e67f52e 100644
--- a/hyppopy/solverpluginbase.py
+++ b/hyppopy/solverpluginbase.py
@@ -1,92 +1,95 @@
 # DKFZ
 #
 #
 # Copyright (c) German Cancer Research Center,
 # Division of Medical and Biological Informatics.
 # All rights reserved.
 #
 # This software is distributed WITHOUT ANY WARRANTY; without
 # even the implied warranty of MERCHANTABILITY or FITNESS FOR
 # A PARTICULAR PURPOSE.
 #
 # See LICENSE.txt or http://www.mitk.org for details.
 #
 # Author: Sven Wanner (s.wanner@dkfz.de)
 
 import abc
 
 import os
 import logging
 from hyppopy.globals import DEBUGLEVEL
 from hyppopy.settingspluginbase import SettingsPluginBase
 
 LOG = logging.getLogger(os.path.basename(__file__))
 LOG.setLevel(DEBUGLEVEL)
 
 
 class SolverPluginBase(object):
     _data = None
     _blackbox_function_template = None
     _settings = None
     _name = None
 
     def __init__(self):
         pass
 
     @abc.abstractmethod
     def blackbox_function(self, params):
         raise NotImplementedError('users must define loss_func to use this base class')
 
     @abc.abstractmethod
     def execute_solver(self):
         raise NotImplementedError('users must define execute_solver to use this base class')
 
     @abc.abstractmethod
     def convert_results(self):
         raise NotImplementedError('users must define convert_results to use this base class')
 
     def set_data(self, data):
         self._data = data
 
     def set_blackbox_function(self, func):
         self._blackbox_function_template = func
 
     def get_results(self):
         return self.convert_results()
 
     def run(self):
-        self.execute_solver(self.settings.get_hyperparameter())
+        try:
+            self.execute_solver(self.settings.get_hyperparameter())
+        except Exception as e:
+            raise e
 
     @property
     def data(self):
         return self._data
 
     @property
     def blackbox_function_template(self):
         return self._blackbox_function_template
 
     @property
     def name(self):
         return self._name
 
     @name.setter
     def name(self, value):
         if not isinstance(value, str):
             msg = "Invalid input, str type expected for value, got {} instead".format(type(value))
             LOG.error(msg)
             raise IOError(msg)
         self._name = value
 
     @property
     def settings(self):
         return self._settings
 
     @settings.setter
     def settings(self, value):
         if not isinstance(value, SettingsPluginBase):
             msg = "Invalid input, SettingsPluginBase type expected for value, got {} instead".format(type(value))
             LOG.error(msg)
             raise IOError(msg)
         self._settings = value