Improve selection sort doctests and documentation

- Add detailed algorithm description explaining the approach
- Document time complexity O(n²) and space complexity O(1)
- Add 11 comprehensive doctest examples covering:
  - Basic cases (already covered)
  - Edge cases (single element, empty list)
  - Sorted/reverse-sorted inputs
  - Lists with duplicates
  - Verification against standard library sorted() function

These improvements help new learners understand the algorithm better and verify correctness across diverse inputs.

Author: 23f3003167

sorts/selection_sort.py

@@ -2,8 +2,15 @@ def selection_sort(collection: list[int]) -> list[int]:
     """
     Sorts a list in ascending order using the selection sort algorithm.
 
-    :param collection: A list of integers to be sorted.
-    :return: The sorted list.
+    Selection sort divides the input list into a sorted and unsorted region.
+    It repeatedly finds the minimum element from the unsorted region and
+    places it at the end of the sorted region.
+
+    Time Complexity: O(n²) in all cases
+    Space Complexity: O(1)
+
+    :param collection: A list of comparable items to be sorted.
+    :return: The same list sorted in ascending order.
 
     Examples:
     >>> selection_sort([0, 5, 3, 2, 2])
@@ -14,6 +21,30 @@ def selection_sort(collection: list[int]) -> list[int]:
 
     >>> selection_sort([-2, -5, -45])
     [-45, -5, -2]
+
+    >>> selection_sort([1])
+    [1]
+
+    >>> selection_sort([5, 4, 3, 2, 1])
+    [1, 2, 3, 4, 5]
+
+    >>> selection_sort([1, 2, 3, 4, 5])
+    [1, 2, 3, 4, 5]
+
+    >>> selection_sort([3, 3, 3, 3])
+    [3, 3, 3, 3]
+
+    >>> selection_sort([0])
+    [0]
+
+    >>> selection_sort([2, -3, 0, 5, -1])
+    [-3, -1, 0, 2, 5]
+
+    >>> selection_sort([0, 5, 3, 2, 2]) == sorted([0, 5, 3, 2, 2])
+    True
+
+    >>> selection_sort([-2, -5, -45]) == sorted([-2, -5, -45])
+    True
     """
 
     length = len(collection)