diff --git a/test/Test_representative_and_match/test_Functions.py b/test/Test_representative_and_match/test_Functions.py
new file mode 100644
index 0000000000000000000000000000000000000000..72a120d1d2e6967233abd0dc2bc14607a8ef40fe
--- /dev/null
+++ b/test/Test_representative_and_match/test_Functions.py
@@ -0,0 +1,132 @@
+import pandas as pd
+import numpy as np
+import os
+
+def find_path(filename:str)->str: 
+    """Find the path to a file
+
+        Args:
+            name of a file
+
+        Returns:
+            str path of a file 
+      
+        Raises:
+            None
+    """
+    absolute_path = os.path.dirname(__file__)
+    test_file = "inputs\\" + str(filename) 
+    full_path = os.path.join(absolute_path, test_file)
+    return full_path
+
+def find_output():
+    """Find the path of the output file 
+
+        Args:
+            name of a file
+
+        Returns:
+            str path of a file 
+      
+        Raises:
+            None
+    """
+    absolute_path = os.path.dirname(__file__)
+    test_file = "ReprTrans_ExpressionLevel.tsv"
+    full_path = os.path.join(absolute_path, test_file)
+    return full_path
+
+
+def find_path_intermediateFile()->str: 
+    """Find the path to gencode.vM31.annotation_intermediat_file.txt
+
+        Args:
+            none
+
+        Returns:
+            str path of gencode.vM31.annotation_intermediat_file.txt
+      
+        Raises:
+            None
+    """ 
+    absolute_path = os.path.dirname(__file__)
+    test_file = r"inputs\test_gencode.vM31.annotation_intermediat_file.txt"
+    full_path = os.path.join(absolute_path, test_file)
+    return full_path
+
+def column_number(df :pd.DataFrame)-> int:
+
+    """Return the number of column of a df 
+
+        Args:
+            dataframe
+
+        Returns:
+            int
+      
+        Raises:
+            None
+    """ 
+    length = len(df.columns)
+    return length
+
+def column_dType(df : pd.DataFrame) -> dict[str,np.dtype]:
+    """Return the type of each column of a df in a dict 
+
+        Args:
+            Pandas dataframe
+
+        Returns:
+            dict{column:np.dtype()}
+      
+        Raises:
+            None
+    """ 
+    dtype=df.dtypes.to_dict()
+    return dtype
+
+def duplicated_rows(df: pd.DataFrame) -> pd.DataFrame:
+    """Return the sum of duplicated rows in a df 
+
+        Args:
+            Pandas dataframe
+
+        Returns:
+            int
+      
+        Raises:
+            None
+    """ 
+    df_dupl = df[df.duplicated()]
+    return df_dupl
+
+def duplicated_index(df: pd.DataFrame) -> pd.DataFrame:
+    """Return the sum of duplicated index in a df 
+
+        Args:
+            Pandas dataframe
+
+        Returns:
+            int
+      
+        Raises:
+            None
+    """ 
+    df_dupl = df[df.index.duplicated()]
+    return df_dupl
+
+def NA_value(df: pd.DataFrame) -> int: 
+    """Return the sum of NA values in a df
+
+        Args:
+            Pandas dataframe
+
+        Returns:
+            int
+      
+        Raises:
+            None
+    """ 
+    nNA = df.isna().sum().sum()
+    return nNA
+