diff --git a/market_trade/tests/test_decision.py b/market_trade/tests/test_decision.py
index de5b98a..6d1d249 100644
--- a/market_trade/tests/test_decision.py
+++ b/market_trade/tests/test_decision.py
@@ -1,63 +1,64 @@
-from market_trade.core.decisionManager_v2 import *
-from market_trade.core.indicators_v2 import *
-from market_trade.core.signals_v2 import *
+from market_trade.core.decisionManager_v2 import DecisionManager
+from market_trade.core.indicators_v2 import ind_BB
+from market_trade.core.signals_v2 import sig_BB
 import market_trade.data.dataloader
 
 
-sigAgrReq = {
-    'sig_BB':{
-        'className':sig_BB,
-        'params':{'source':'close','target':'close'},
-        'indicators':{
-            'ind_BB':{
-                'className':ind_BB,
-                'params':{'MeanType':'SMA','window':30,'valueType':'close','kDev':2.5}
+sig_agr_req = {
+    'sig_BB': {
+        'className': sig_BB,
+        'params': {'source': 'close', 'target': 'close'},
+        'indicators': {
+            'ind_BB': {
+                'className': ind_BB,
+                'params': {'MeanType': 'SMA', 'window': 30, 'valueType': 'close', 'kDev': 2.5}
             }
         }
     },
-    'sig_BB_2':{
-        'className':sig_BB,
-        'params':{'source':'close','target':'close'},
-        'indicators':{
-            'ind_BB':{
-                'className':ind_BB,
-                'params':{'MeanType':'SMA','window':30,'valueType':'close','kDev':2}
+    'sig_BB_2': {
+        'className': sig_BB,
+        'params': {'source': 'close', 'target': 'close'},
+        'indicators': {
+            'ind_BB': {
+                'className': ind_BB,
+                'params': {'MeanType': 'SMA', 'window': 30, 'valueType': 'close', 'kDev': 2}
             }
         }
     }
 }
 
-test = decsionManager('Pipa', sigAgrReq)
+test = DecisionManager('Pipa', sig_agr_req)
 
 
 import pandas as pd
 
 df_candle = pd.read_csv("../../data/EURUSD_price_candlestick.csv")
 df_candle["date"] = df_candle["timestamp"]
-sigAgrRetroTemplate = {
-    'sig_BB':{
+
+sig_agr_retro_template = {
+    'sig_BB': {
         'signalData': None,
-        'indicatorData' :{'ind_BB': None}
+        'indicatorData': {'ind_BB': None}
     },
-    'sig_BB_2':{
+    'sig_BB_2': {
         'signalData': None,
-        'indicatorData' :{'ind_BB': None}
+        'indicatorData': {'ind_BB': None}
     }
 }
 
-retroAns = test.getRetroTrendAns(sigAgrRetroTemplate,df_candle[5000:6000].reset_index(drop=True),40)
+retro_ans = test.get_retro_trend_answer(sig_agr_retro_template, df_candle[5000:6000].reset_index(drop=True), 40)
 
-test.generateMatrixProbabilityFromDict(retroAns)
+test.generate_matrix_probability_from_dict(retro_ans)
 
-sigAgrData = {
-    'sig_BB':{
+sig_agr_data = {
+    'sig_BB': {
         'signalData': df_candle[990:1000],
-        'indicatorData' :{'ind_BB': df_candle[:1000]}
+        'indicatorData': {'ind_BB': df_candle[:1000]}
     },
-    'sig_BB_2':{
+    'sig_BB_2': {
         'signalData': df_candle[990:1000],
-        'indicatorData' :{'ind_BB': df_candle[:1000]}
+        'indicatorData': {'ind_BB': df_candle[:1000]}
     }
 }
 
-test.getOnlineAns(sigAgrData, 0.0)
\ No newline at end of file
+test.get_online_answer(sig_agr_data, 0.0)