⚡️ Speed up function sorter by 82%

[codeflash-ai]

📄 82% (0.82x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 3.33 seconds → 1.83 seconds (best of 5 runs)

📝 Explanation and details

Here's an optimized version of your function. Your original code uses bubble sort with no exit condition if the list is already sorted and redundant use of len(arr) inside loops. To speed things up while preserving the exact return/output behavior, I'll.

• Replace the sort with Python's built-in list.sort(), which is highly optimized (Timsort, O(n log n)).
• Keep the print statements in the same order.
• Ensure the return value is preserved and the debug output unchanged.

If you must use a manual method (and can't use sort()), at least add an early exit for already-sorted lists and avoid redundant len() calls.

But, using arr.sort() is the fastest and best solution for Python. The first version is recommended unless you're required to write your own sorting logic.
Both versions keep output and function signature/return value unchanged.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 20 Passed
🌀 Generated Regression Tests	✅ 54 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Existing Unit Tests Details

- benchmarks/test_benchmark_bubble_sort.py
    - $\color{green}test_sort2: 7.01ms \rightarrow 4.31ms$

- test_bubble_sort.py
    - $\color{green}test_sort: 834ms \rightarrow 556ms$

- test_bubble_sort_conditional.py
    - $\color{green}test_sort: 5.67μs \rightarrow 5.29μs$

- test_bubble_sort_import.py
    - $\color{green}test_sort: 823ms \rightarrow 558ms$

- test_bubble_sort_in_class.py
    - $\color{green}TestSorter.test_sort_in_pytest_class: 833ms \rightarrow 557ms$

- test_bubble_sort_parametrized.py
    - $\color{green}test_sort_parametrized: 502ms \rightarrow 246μs$

- test_bubble_sort_parametrized_loop.py
    - $\color{green}test_sort_loop_parametrized: 98.4μs \rightarrow 27.9μs$

🌀 Generated Regression Tests Details

import random  # used for generating large random lists
import string  # used for testing sorting of strings

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

# unit tests

# --------------------
# Basic Test Cases
# --------------------

def test_empty_list():
    # Should return an empty list when input is empty
    codeflash_output = sorter([])

def test_single_element():
    # Should return the same list when only one element
    codeflash_output = sorter([42])

def test_sorted_list():
    # Already sorted list should remain unchanged
    codeflash_output = sorter([1, 2, 3, 4, 5])

def test_reverse_sorted_list():
    # Reverse sorted list should be sorted ascending
    codeflash_output = sorter([5, 4, 3, 2, 1])

def test_unsorted_integers():
    # Unsorted list of positive integers
    codeflash_output = sorter([3, 1, 4, 2, 5])

def test_negative_integers():
    # List with negative integers
    codeflash_output = sorter([-3, -1, -4, -2, -5])

def test_mixed_integers():
    # List with both negative and positive integers
    codeflash_output = sorter([0, -1, 3, -2, 2, 1])

def test_floats():
    # List with float numbers
    codeflash_output = sorter([3.2, 1.5, 4.8, 2.1])

def test_mixed_ints_and_floats():
    # List with both ints and floats
    codeflash_output = sorter([3, 1.1, 2, 0.5, 1])

def test_strings():
    # List of strings
    codeflash_output = sorter(["banana", "apple", "cherry", "date"])

def test_duplicate_elements():
    # List with duplicate elements
    codeflash_output = sorter([2, 3, 2, 1, 3, 1])

def test_all_equal_elements():
    # List where all elements are equal
    codeflash_output = sorter([7, 7, 7, 7])

# --------------------
# Edge Test Cases
# --------------------

def test_large_negative_and_positive():
    # List with large negative and positive numbers
    arr = [999999999, -999999999, 0, 123456789, -123456789]
    codeflash_output = sorter(arr)

def test_strings_case_sensitivity():
    # List of strings with different cases (should sort ASCIIbetically)
    arr = ["Banana", "apple", "Cherry", "banana"]
    codeflash_output = sorter(arr)

def test_unicode_strings():
    # List with unicode strings
    arr = ["café", "cafe", "cafè", "càfe"]
    codeflash_output = sorter(arr)

def test_list_with_none():
    # List containing None should raise TypeError (not comparable)
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sorter(arr)

def test_list_with_uncomparable_types():
    # List with uncomparable types (int and str)
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr)

def test_input_not_a_list():
    # Input is not a list (should raise TypeError)
    for nonlist in (123, "abc", (1,2,3), {1,2,3}, None):
        with pytest.raises(TypeError):
            sorter(nonlist)


def test_list_with_nan():
    # List with float('nan') values (nan is not comparable)
    arr = [1.0, float('nan'), 2.0]
    # Python's sort keeps nan at the end, but our function may not
    # We check that no exception is raised and nan is present in output
    codeflash_output = sorter(arr[:]); result = codeflash_output

def test_list_with_inf():
    # List with float('inf') and float('-inf')
    arr = [1, float('inf'), -1, float('-inf')]
    codeflash_output = sorter(arr[:]); result = codeflash_output

# --------------------
# Large Scale Test Cases
# --------------------

def test_large_sorted_list():
    # Already sorted large list
    arr = list(range(1000))
    codeflash_output = sorter(arr[:])

def test_large_reverse_sorted_list():
    # Large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr[:])

def test_large_random_list():
    # Large random list of integers
    arr = random.sample(range(-10000, -9000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr[:])

def test_large_list_with_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[:])

def test_large_list_of_strings():
    # 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[:])

def test_large_list_all_equal():
    # Large list where all elements are the same
    arr = [42] * 1000
    codeflash_output = sorter(arr[:])

def test_large_list_negative_and_positive_floats():
    # Large list of floats, both negative and positive
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr[:])

# --------------------
# Mutation Testing: Ensure stability and correctness
# --------------------

def test_stability_of_sort():
    # Sort should be stable: equal elements retain original order
    class StableObj:
        def __init__(self, val, tag):
            self.val = val
            self.tag = tag
        def __lt__(self, other):
            return self.val < other.val
        def __gt__(self, other):
            return self.val > other.val
        def __eq__(self, other):
            return self.val == other.val and self.tag == other.tag
        def __repr__(self):
            return f"StableObj({self.val},{self.tag})"
    # List with duplicate values but different tags
    arr = [StableObj(1, 'a'), StableObj(2, 'b'), StableObj(1, 'c')]
    codeflash_output = sorter(arr[:]); sorted_arr = codeflash_output

def test_sort_does_not_return_new_list():
    # Ensure sorter sorts in-place and returns the same object
    arr = [3, 2, 1]
    arr_id = id(arr)
    codeflash_output = sorter(arr); result = codeflash_output
# 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 random lists
import string  # used for string test cases

# 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

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

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

def test_sorter_list_with_duplicates():
    # List with duplicate values
    arr = [4, 2, 5, 2, 3, 4]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_single_element():
    # List with a single element should remain unchanged
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_two_elements_sorted():
    # Two elements, already sorted
    arr = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_two_elements_unsorted():
    # Two elements, unsorted
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

# --------------------------
# Edge Test Cases
# --------------------------

def test_sorter_empty_list():
    # Sorting an empty list should return an empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_all_identical_elements():
    # All elements are the same
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_negative_numbers():
    # List with negative numbers
    arr = [-3, -1, -4, -2, 0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_mixed_positive_negative():
    # List with both negative and positive numbers
    arr = [3, -2, 5, 0, -1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_floats():
    # List with float values
    arr = [2.5, 3.1, 1.0, 4.8, 2.5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_and_small_numbers():
    # List with very large and very small numbers
    arr = [1e10, -1e10, 0, 5, -5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_strings():
    # List of strings should be sorted lexicographically
    arr = ['banana', 'apple', 'cherry', 'date']
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_strings_case_sensitivity():
    # List of strings with different cases
    arr = ['banana', 'Apple', 'cherry', 'Date']
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_unicode_strings():
    # List of unicode strings
    arr = ['éclair', 'apple', 'Éclair', 'banana']
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_custom_objects_raises():
    # List of objects that are not directly comparable should raise TypeError
    class Dummy:
        pass
    arr = [Dummy(), Dummy()]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_mixed_types_raises():
    # List with mixed types should raise TypeError
    arr = [1, 'two', 3]
    with pytest.raises(TypeError):
        sorter(arr.copy())

# --------------------------
# Large Scale Test Cases
# --------------------------

def test_sorter_large_random_int_list():
    # Sorting a large list of random integers
    arr = random.sample(range(-10000, -9000), 1000)  # 1000 unique random ints
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_identical_elements():
    # Large list where all elements are the same
    arr = [7] * 1000
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_sorted_list():
    # Large list that is already sorted
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_reverse_sorted_list():
    # Large list that is reverse sorted
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_floats():
    # Large list of floats
    arr = [random.uniform(-1000, 1000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_strings():
    # Large list of random strings
    arr = [
        ''.join(random.choices(string.ascii_letters, k=8))
        for _ in range(1000)
    ]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output
# 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-mc117d8w and push.