chore(algorithms, triangle): minor fixes

Author: BrianLusina

algorithms/dynamic_programming/min_path_sum/README.md

@@ -52,4 +52,4 @@ grows quadratically.
 
 ### Space Complexity
 
-The space complexity is O(n) since we only maintain a single working array `dp` with on entry per row.
+The space complexity is O(n) since we only maintain a single working array `dp` with one entry per row.

algorithms/dynamic_programming/min_path_sum/__init__.py

@@ -41,7 +41,7 @@ def min_path_sum_2(triangle: List[List[int]]) -> int:
     Complexity:
     Time Complexity results in O(n^2), since we visit every number in the triangle exactly once. For n rows, there are
     roughtl n^2/2 elements.
-    Space Complexity is O(1) since the triangle input array is updated in place
+    Space Complexity is O(n) since the triangle input array's last row is copied over
 
     Args:
         triangle(list): A list of lists of integers representing the triangle

algorithms/dynamic_programming/min_path_sum/test_min_path_sum.py

@@ -1,4 +1,5 @@
 import unittest
+import copy
 from typing import List
 from parameterized import parameterized
 from algorithms.dynamic_programming.min_path_sum import min_path_sum, min_path_sum_2
@@ -15,12 +16,14 @@
 class MinPathSumInTriangleTestCase(unittest.TestCase):
     @parameterized.expand(TEST_CASES)
     def test_min_path_sum_in_triangle(self, triangle: List[List[int]], expected: int):
-        actual = min_path_sum(triangle)
+        input_triangle = copy.deepcopy(triangle)
+        actual = min_path_sum(input_triangle)
         self.assertEqual(expected, actual)
 
     @parameterized.expand(TEST_CASES)
     def test_min_path_sum_2_in_triangle(self, triangle: List[List[int]], expected: int):
-        actual = min_path_sum_2(triangle)
+        input_triangle = copy.deepcopy(triangle)
+        actual = min_path_sum_2(input_triangle)
         self.assertEqual(expected, actual)