diff --git a/tests/test_general.py b/tests/test_general.py
index d338077..dd10224 100644
--- a/tests/test_general.py
+++ b/tests/test_general.py
@@ -10,8 +10,6 @@
     StopwordRemover,
 )
 
-import sys
-
 
 class StemmerTest(unittest.TestCase):
     def setUp(self):
@@ -230,14 +228,13 @@ def test_remove_stopwords(self):
         )
 
     def test_dynamic_stopwords(self):
-        py_version = int(sys.version.split('.')[1])
         dsw = self.stopword_remover.dynamically_detect_stop_words(
             "ben bugün gidip aşı olacağım sonra da eve gelip telefon açacağım aşı nasıl etkiledi eve gelip anlatırım aşı olmak bu dönemde çok ama ama ama ama çok önemli".split()
         )
-        expected = ["ama", "aşı", "çok", "eve"]
-        if py_version <= 8: #Sorting algorithm returns different results from python 3.8+ on
-            expected = ["ama", "aşı", "gelip", "eve"]
-        self.assertEqual(dsw, expected)
+        expected = ['ama', 'aşı', 'çok', 'eve', 'gelip']
+
+        # Converted to set since order is not stable
+        self.assertEqual(set(dsw), set(expected))
         self.stopword_remover.add_to_stop_words(dsw)
         self.assertEqual(
             self.stopword_remover.drop_stop_words(
diff --git a/vnlp/stopword_remover/stopword_remover.py b/vnlp/stopword_remover/stopword_remover.py
index dc131ab..7d1c4e2 100644
--- a/vnlp/stopword_remover/stopword_remover.py
+++ b/vnlp/stopword_remover/stopword_remover.py
@@ -1,4 +1,5 @@
 from typing import List
+
 from pathlib import Path
 
 import numpy as np
@@ -59,6 +60,9 @@ def dynamically_detect_stop_words(
             ['ama', 'aşı', 'gelip', 'eve']
         """
         unq, cnts = np.unique(list_of_tokens, return_counts=True)
+        # Edgecase: Every word used once
+        if len(unq) == list_of_tokens:
+            return []
         sorted_indices = cnts.argsort()[
             ::-1
         ]  # I need them in descending order
@@ -83,8 +87,12 @@ def dynamically_detect_stop_words(
         ]  # removing nan
         argmax_second_der = np.argmax(pct_change_two)
 
+        # Correction term since argmax finds first occurence
+        amount_of_max = np.sum(cnts == cnts[argmax_second_der])
+
         # +2 is due to shifting twice due to np.diff()
-        detected_stop_words = unq[: argmax_second_der + 2].tolist()
+        # -1 is added to correctly find all values
+        detected_stop_words = unq[: argmax_second_der + amount_of_max].tolist()
 
         # Determine rare_words according to given rare_words_freq value
         # Add them to dynamic_stop_words list