diff --git a/pkg/algorithms/cmr/cmr.py b/pkg/algorithms/cmr/cmr.py
index 7959af6..d72f35a 100644
--- a/pkg/algorithms/cmr/cmr.py
+++ b/pkg/algorithms/cmr/cmr.py
@@ -26,8 +26,8 @@ def _analyze(self):
             series: data series that contains attributes and full dataframe
             change_points_by_metric: list of ChangePoints
         """
-        logger_instance = SingletonLogger.getLogger("Orion")
-        logger_instance.info("Starting analysis using CMR")
+        self.logger_instance = SingletonLogger.getLogger("Orion")
+        self.logger_instance.info("Starting analysis using CMR")
         self.dataframe["timestamp"] = pd.to_datetime(self.dataframe["timestamp"])
         self.dataframe["timestamp"] = self.dataframe["timestamp"].astype(int) // 10**9
 
@@ -62,14 +62,8 @@ def run_cmr(self, tolerancy: int, dataframe_list: pd.DataFrame):
         change_points_by_metric={ k:[] for k in metric_columns }
         max_date_time = pd.Timestamp.max.to_pydatetime()
         max_time = max_date_time.timestamp()
-        # difference = ["difference", max_time]
-        # pass_fail_list = ["Pass/Fail", max_time]
+
         for column in metric_columns:
-            pct_change_result = dataframe_list[column].pct_change()
-            single_pct_diff = round(pct_change_result.iloc[[-1]].values[0] * 100)
-            pass_fail = "Pass"
-            if single_pct_diff > tolerancy:
-                pass_fail = "Fail"
 
             change_point = ChangePoint(metric=column,
                                             index=1,
@@ -82,13 +76,6 @@ def run_cmr(self, tolerancy: int, dataframe_list: pd.DataFrame):
                                                 pvalue=1
                                             ))
             change_points_by_metric[column].append(change_point)
-            # difference.append(single_pct_diff)
-            # pass_fail_list.append(pass_fail)
-        # difference.append("none")
-        # pass_fail_list.append("none")
-        # dataframe_list.loc[len(dataframe_list.index)] = difference
-        #dataframe_list.loc[len(dataframe_list.index)] = pass_fail_list
-        # logger_instance.info("final data frame " + str(dataframe_list))
 
         # based on change point generate pass/fail
         return dataframe_list, change_points_by_metric
diff --git a/pkg/runTest.py b/pkg/runTest.py
index b24026c..3f09599 100644
--- a/pkg/runTest.py
+++ b/pkg/runTest.py
@@ -9,7 +9,16 @@
 import pkg.constants as cnsts
 from pkg.utils import get_datasource, process_test, get_subtracted_timestamp
 
-
+def get_algorithm_type(kwargs):
+    if kwargs["hunter_analyze"]:
+        algorithm_name = cnsts.EDIVISIVE
+    elif kwargs["anomaly_detection"]:
+        algorithm_name = cnsts.ISOLATION_FOREST
+    elif kwargs['cmr']:
+        algorithm_name = cnsts.CMR
+    else: 
+        algorithm_name = None
+    return algorithm_name
 
 def run(**kwargs: dict[str, Any]) -> dict[str, Any]: #pylint: disable = R0914
     """run method to start the tests
@@ -48,13 +57,8 @@ def run(**kwargs: dict[str, Any]) -> dict[str, Any]: #pylint: disable = R0914
         if fingerprint_matched_df is None:
             sys.exit(3) # No data present
 
-        if kwargs["hunter_analyze"]:
-            algorithm_name = cnsts.EDIVISIVE
-        elif kwargs["anomaly_detection"]:
-            algorithm_name = cnsts.ISOLATION_FOREST
-        elif kwargs['cmr']:
-            algorithm_name = cnsts.CMR
-        else:
+        algorithm_name = get_algorithm_type(kwargs)
+        if algorithm_name is None:
             return None, None
 
         algorithmFactory = AlgorithmFactory()