diff --git a/src/data/roadmaps/computer-science/content/103-asymptotic-notation/103-common-runtimes/105-factorial.md b/src/data/roadmaps/computer-science/content/103-asymptotic-notation/103-common-runtimes/105-factorial.md
index df4743887..6fd689d37 100644
--- a/src/data/roadmaps/computer-science/content/103-asymptotic-notation/103-common-runtimes/105-factorial.md
+++ b/src/data/roadmaps/computer-science/content/103-asymptotic-notation/103-common-runtimes/105-factorial.md
@@ -3,9 +3,24 @@
 Factorial complexity algorithms have a runtime of `O(n!)`. This is the worst case scenario for an algorithm. Factorial complexity algorithms are very inefficient and should be avoided.
 
 ```python
-def factorial(n):
-    if n == 0:
-        return 1
-    else:
-        return n * factorial(n-1)
+def generate_permutations(s):
+    # Base case: If the string length is 1, return a list containing the string
+    if len(s) == 1:
+        return [s]
+
+    # Initialize the result list
+    permutations = []
+
+    # Recursively generate all permutations
+    for i in range(len(s)):
+        # Current character
+        current_char = s[i]
+        # Remaining characters
+        remaining_chars = s[:i] + s[i+1:]
+        # Generate all permutations of the remaining characters
+        for perm in generate_permutations(remaining_chars):
+            # Add the current character to the front of each generated permutation
+            permutations.append(current_char + perm)
+
+    return permutations
 ```