⚡️ Speed up function sorter by 172,414%

[codeflash-ai]

📄 172,414% (1,724.14x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 3.37 seconds → 1.95 milliseconds (best of 529 runs)

📝 Explanation and details

Here’s an optimized version of the program using Python's built-in sort which is significantly faster than the bubble sort logic.
All existing comments are preserved; no comments are present in the given code, so none are changed.

Explanation:

• The nested for-loops implementing bubble sort are replaced with the arr.sort() in-place method, which runs in O(n log n) time, much faster than the O(n²) of bubble sort.
• The return value and print output remain unchanged.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 20 Passed
🌀 Generated Regression Tests	✅ 59 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Existing Unit Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
benchmarks/test_benchmark_bubble_sort.py::test_sort2	7.04ms	16.4μs	✅42804%
test_bubble_sort.py::test_sort	826ms	140μs	✅586370%
test_bubble_sort_conditional.py::test_sort	5.79μs	3.17μs	✅82.9%
test_bubble_sort_import.py::test_sort	834ms	142μs	✅586851%
test_bubble_sort_in_class.py::TestSorter.test_sort_in_pytest_class	829ms	144μs	✅572485%
test_bubble_sort_parametrized.py::test_sort_parametrized	506ms	142μs	✅355949%
test_bubble_sort_parametrized_loop.py::test_sort_loop_parametrized	97.9μs	21.0μs	✅366%

🌀 Generated Regression Tests and Runtime

import random  # used for generating large scale test data
import string  # used for string sorting tests
import sys  # used for edge case with large/small numbers

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort import sorter

# unit tests

# -------------------------
# BASIC TEST CASES
# -------------------------

def test_sorter_sorted_list():
    # Already sorted list should remain unchanged
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.42μs -> 3.08μs (75.7% faster)

def test_sorter_reverse_sorted_list():
    # Reverse sorted list should be sorted in ascending order
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.04μs -> 2.92μs (72.8% faster)

def test_sorter_unsorted_list():
    # Unsorted list should be sorted in ascending order
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.38μs -> 3.08μs (41.9% faster)

def test_sorter_with_duplicates():
    # List with duplicate elements should be sorted, duplicates preserved
    arr = [4, 2, 2, 3, 1, 4]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.58μs -> 3.08μs (48.6% faster)

def test_sorter_with_negative_numbers():
    # List with negative numbers should be sorted correctly
    arr = [-3, -1, -2, 0, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.46μs -> 3.17μs (40.8% faster)

def test_sorter_with_floats():
    # List with floats should be sorted correctly
    arr = [3.2, 1.5, 2.8, 1.2, 2.2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.17μs -> 3.75μs (64.4% faster)

def test_sorter_with_mixed_int_float():
    # List with ints and floats should be sorted correctly
    arr = [3, 1.5, 2, 1.2, 2.0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.46μs -> 3.62μs (50.6% faster)

def test_sorter_with_strings():
    # List of strings should be sorted lexicographically
    arr = ["banana", "apple", "cherry", "date"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.42μs -> 3.29μs (34.2% faster)

def test_sorter_with_single_element():
    # Single element list should remain unchanged
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.29μs -> 2.88μs (14.5% faster)

def test_sorter_with_two_elements():
    # Two element list should be sorted
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.54μs -> 2.88μs (23.2% faster)

# -------------------------
# EDGE TEST CASES
# -------------------------

def test_sorter_empty_list():
    # Empty list should return empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.04μs -> 2.75μs (10.6% faster)

def test_sorter_all_identical_elements():
    # All identical elements should remain unchanged
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.92μs -> 2.96μs (32.4% faster)

def test_sorter_large_and_small_numbers():
    # List with very large and very small numbers
    arr = [sys.maxsize, -sys.maxsize-1, 0, 1, -1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.33μs -> 3.42μs (56.1% faster)

def test_sorter_with_nan_and_inf():
    # List with float('nan'), float('inf'), float('-inf')
    arr = [3, float('nan'), 2, float('inf'), -1, float('-inf')]
    # Sorting with NaN is tricky: NaN is not equal to, less than, or greater than anything, even itself.
    # Python's built-in sort puts NaNs at the end.
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.92μs -> 3.67μs (61.3% faster)

def test_sorter_with_unicode_strings():
    # List of unicode strings should be sorted lexicographically
    arr = ["éclair", "apple", "Éclair", "banana"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.33μs -> 3.42μs (56.1% faster)

def test_sorter_with_empty_strings():
    # List with empty strings and normal strings
    arr = ["", "banana", "", "apple"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.38μs -> 3.21μs (36.4% faster)

def test_sorter_with_nested_lists():
    # List with nested lists should raise TypeError (lists are not comparable)
    arr = [3, [1, 2], 2]
    with pytest.raises(TypeError):
        sorter(arr.copy()) # 2.88μs -> 1.92μs (50.0% faster)

def test_sorter_with_none():
    # List with None and ints should raise TypeError (None is not comparable)
    arr = [None, 2, 1]
    with pytest.raises(TypeError):
        sorter(arr.copy()) # 2.75μs -> 1.88μs (46.7% faster)

def test_sorter_with_mixed_types():
    # List with mixed types (e.g., int and string) should raise TypeError
    arr = [1, "two", 3]
    with pytest.raises(TypeError):
        sorter(arr.copy()) # 2.08μs -> 1.71μs (22.0% faster)

# -------------------------
# LARGE SCALE TEST CASES
# -------------------------

def test_sorter_large_random_integers():
    # Large list of random integers (size: 1000)
    arr = random.sample(range(-10000, -9000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 28.0ms -> 60.2μs (46392% faster)

def test_sorter_large_sorted_list():
    # Large already sorted list (size: 1000)
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 18.8ms -> 29.9μs (62608% faster)

def test_sorter_large_reverse_sorted_list():
    # Large reverse sorted list (size: 1000)
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 30.8ms -> 30.0μs (102555% faster)

def test_sorter_large_duplicates():
    # Large list with many duplicates
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 24.6ms -> 49.0μs (50107% faster)

def test_sorter_large_strings():
    # Large list of random strings
    arr = [
        ''.join(random.choices(string.ascii_letters + string.digits, k=8))
        for _ in range(1000)
    ]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 30.3ms -> 101μs (29883% faster)

def test_sorter_large_negative_numbers():
    # Large list of negative numbers
    arr = [random.randint(-10000, -1) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 27.6ms -> 63.7μs (43311% faster)

def test_sorter_large_floats():
    # Large list of random floats
    arr = [random.uniform(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 27.1ms -> 285μs (9401% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import random  # used for generating large scale random test data
import string  # used for string sorting tests
import sys  # used for maxsize in edge cases

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort import sorter

# unit tests

# 1. BASIC TEST CASES

def test_sorter_sorted_input():
    """Test that a sorted list remains sorted."""
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.58μs -> 3.21μs (74.1% faster)

def test_sorter_reverse_sorted_input():
    """Test that a reverse-sorted list is sorted correctly."""
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.42μs -> 3.08μs (75.6% faster)

def test_sorter_unsorted_input():
    """Test that an unsorted list is sorted correctly."""
    arr = [3, 1, 4, 2, 5]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.29μs -> 2.96μs (45.1% faster)

def test_sorter_with_duplicates():
    """Test that duplicates are handled and sorted correctly."""
    arr = [4, 2, 5, 2, 3, 4]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.62μs -> 3.08μs (50.0% faster)

def test_sorter_single_element():
    """Test that a single-element list is returned as-is."""
    arr = [42]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 3.67μs -> 2.92μs (25.7% faster)

def test_sorter_two_elements():
    """Test that a two-element list is sorted correctly."""
    arr = [2, 1]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.17μs -> 2.96μs (40.9% faster)

def test_sorter_all_equal_elements():
    """Test that a list with all equal elements is unchanged."""
    arr = [7, 7, 7, 7]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 3.92μs -> 2.92μs (34.2% faster)

def test_sorter_negative_numbers():
    """Test sorting with negative numbers."""
    arr = [0, -1, -3, 2, 1]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.50μs -> 3.08μs (45.9% faster)

def test_sorter_mixed_positive_and_negative():
    """Test sorting with a mix of negative and positive numbers."""
    arr = [-2, 3, 0, -1, 2]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.46μs -> 3.04μs (46.5% faster)

def test_sorter_floats():
    """Test sorting with float numbers."""
    arr = [3.1, 2.4, 5.6, 1.2]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 6.33μs -> 3.54μs (78.8% faster)

def test_sorter_mixed_int_and_float():
    """Test sorting with mixed int and float."""
    arr = [3, 1.5, 2, 4.0]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.50μs -> 3.54μs (55.3% faster)

def test_sorter_strings():
    """Test sorting with strings."""
    arr = ["banana", "apple", "cherry"]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.88μs -> 3.08μs (58.1% faster)

def test_sorter_empty_list():
    """Test that an empty list returns an empty list."""
    arr = []
    codeflash_output = sorter(arr[:]); result = codeflash_output # 3.54μs -> 2.79μs (26.8% faster)

# 2. EDGE TEST CASES

def test_sorter_large_integers():
    """Test sorting with very large integers."""
    arr = [sys.maxsize, -sys.maxsize, 0, 999999999, -999999999]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 6.29μs -> 3.54μs (77.6% faster)

def test_sorter_small_integers():
    """Test sorting with very small integers (including negative maxsize)."""
    arr = [-sys.maxsize-1, sys.maxsize, 0]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.21μs -> 3.21μs (31.2% faster)

def test_sorter_unicode_strings():
    """Test sorting with unicode strings."""
    arr = ["éclair", "apple", "Éclair", "banana"]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.71μs -> 3.38μs (69.1% faster)

def test_sorter_empty_strings():
    """Test sorting with empty strings included."""
    arr = ["", "a", "", "b"]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.04μs -> 3.08μs (63.5% faster)

def test_sorter_single_characters():
    """Test sorting with single character strings."""
    arr = ["d", "a", "c", "b"]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.33μs -> 3.04μs (42.4% faster)

def test_sorter_already_sorted_strings():
    """Test that already sorted strings remain sorted."""
    arr = ["a", "b", "c"]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 3.67μs -> 3.00μs (22.2% faster)

def test_sorter_nested_lists():
    """Test sorting with nested lists (should raise TypeError)."""
    arr = [[1, 2], [1, 1], [2, 2]]
    # Lists are comparable if they have comparable elements
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.96μs -> 3.67μs (35.2% faster)

def test_sorter_mixed_types():
    """Test sorting with mixed types (should raise TypeError in Python 3)."""
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr[:]) # 2.71μs -> 1.83μs (47.7% faster)

def test_sorter_none_elements():
    """Test sorting with None included (should raise TypeError)."""
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sorter(arr[:]) # 2.38μs -> 1.83μs (29.5% faster)

def test_sorter_boolean_values():
    """Test sorting with boolean values (True/False are ints in Python)."""
    arr = [True, False, 1, 0]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.79μs -> 3.21μs (49.4% faster)

def test_sorter_large_identical_elements():
    """Test sorting with a large number of identical elements."""
    arr = [42] * 1000
    codeflash_output = sorter(arr[:]); result = codeflash_output # 18.1ms -> 27.7μs (65160% faster)

# 3. LARGE SCALE TEST CASES

def test_sorter_large_random_integers():
    """Test sorting a large list of random integers."""
    arr = random.sample(range(-1000000, -999000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr[:]); result = codeflash_output # 28.0ms -> 62.1μs (45053% faster)

def test_sorter_large_sorted_input():
    """Test sorting a large already-sorted list."""
    arr = list(range(1000))
    codeflash_output = sorter(arr[:]); result = codeflash_output # 18.4ms -> 29.0μs (63298% faster)

def test_sorter_large_reverse_sorted_input():
    """Test sorting a large reverse-sorted list."""
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr[:]); result = codeflash_output # 30.5ms -> 29.2μs (104464% faster)

def test_sorter_large_strings():
    """Test sorting a large list of random strings."""
    arr = [''.join(random.choices(string.ascii_letters, k=5)) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr[:]); result = codeflash_output # 29.5ms -> 93.6μs (31433% faster)

def test_sorter_large_floats():
    """Test sorting a large list of random floats."""
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr[:]); result = codeflash_output # 26.0ms -> 290μs (8855% faster)

def test_sorter_large_duplicates():
    """Test sorting a large list with many duplicates."""
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr[:]); result = codeflash_output # 25.0ms -> 51.0μs (48875% faster)

# Additional edge: ensure in-place mutation does not affect input reference
def test_sorter_does_not_modify_original():
    """Test that sorter does not modify the original list when passed a copy."""
    arr = [3, 2, 1]
    arr_copy = arr[:]
    sorter(arr_copy) # 5.12μs -> 3.21μs (59.7% faster)

# Edge: sorting with negative zero and positive zero (floats)
def test_sorter_negative_and_positive_zero():
    """Test sorting with -0.0 and 0.0 (should be equal in sort order)."""
    arr = [-0.0, 0.0, 1.0, -1.0]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.12μs -> 3.38μs (51.9% faster)

# Edge: sorting with very small and very large floats
def test_sorter_extreme_floats():
    """Test sorting with extreme float values."""
    arr = [1e-308, 1e308, -1e308, -1e-308, 0.0]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 9.25μs -> 5.38μs (72.1% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-sorter-md9f7cpc and push.